From 22c18691308d342d01a94d2f8cf228264d8c91dc Mon Sep 17 00:00:00 2001 From: perdelt Date: Mon, 5 Aug 2024 11:34:44 +0200 Subject: [PATCH 1/6] DBMS: PostgreSQL with PGBouncer test --- k8s/deploymenttemplate-PGBouncer.yml | 227 +++++++++++++++++++++++++++ 1 file changed, 227 insertions(+) create mode 100644 k8s/deploymenttemplate-PGBouncer.yml diff --git a/k8s/deploymenttemplate-PGBouncer.yml b/k8s/deploymenttemplate-PGBouncer.yml new file mode 100644 index 00000000..397bead6 --- /dev/null +++ b/k8s/deploymenttemplate-PGBouncer.yml @@ -0,0 +1,227 @@ +apiVersion: v1 +kind: PersistentVolumeClaim +metadata: + labels: {app: bexhoma, component: sut, configuration: default, experiment: default} + name: bexhoma-storage +spec: + accessModes: + - ReadWriteOnce + resources: + requests: + storage: 20Gi + storageClassName: shared +--- +apiVersion: v1 +kind: Service +metadata: + labels: {app: bexhoma, component: sut, configuration: default, experiment: default} + name: bexhoma-service +spec: + ports: + - {port: 9091, protocol: TCP, name: port-dbms, targetPort: 5432} + - {port: 9300, protocol: TCP, name: port-monitoring, targetPort: 9300} + selector: {app: bexhoma, component: sut, configuration: default, experiment: default} +--- +apiVersion: apps/v1 +kind: Deployment +metadata: + labels: {app: bexhoma, component: sut, configuration: default, experiment: default} + name: bexhoma-deployment-postgres +spec: + replicas: 1 + selector: + matchLabels: {app: bexhoma, component: sut, configuration: default, experiment: default} + template: + metadata: + labels: {app: bexhoma, component: sut, configuration: default, experiment: default} + spec: + automountServiceAccountToken: false + imagePullSecrets: + - {name: dockerhub} + nodeSelector: + tolerations: + #- key: "nvidia.com/gpu" + # effect: "NoSchedule" + terminationGracePeriodSeconds: 180 + containers: + - name: pool + image: edoburu/pgbouncer + env: + - name: DB_USER + value: postgres + - name: DB_PASSWORD + value: postgres + - name: DB_HOST + value: localhost + - name: DB_PORT + value: 5433 + - name: AUTH_TYPE + value: scram-sha-256 # remove/comment this line if using postgres:13 and lower + - name: POOL_MODE + value: transaction + - name: ADMIN_USERS + value: postgres,dbuser + readinessProbe: + exec: + command: + - pg_isready + - -U + - postgres + initialDelaySeconds: 15 + periodSeconds: 60 + ports: + - {containerPort: 5432} + - name: dbms + image: postgres:16.1 + env: + - name: POSTGRES_HOST_AUTH_METHOD + value: trust + - name: PGDATA + value: /var/lib/postgresql/data/pgdata + - name: PGPORT + value: 5433 # remove/comment this line for default ports + # pg_ctl: cannot be run as root + lifecycle: + postStart: + exec: + command: ["/bin/sh", "-c", "echo 'Hello from the postStart handler' > /usr/share/message && cat /usr/share/message"] + preStop: + exec: + #command: ["/bin/sh", "-c", "gosu postgres pg_ctl stop -D /var/lib/postgresql/data -m fast"] + #command: ["/bin/sh", "-c", "gosu postgres pg_ctl stop -m fast"] + #command: ["echo 'PRESTOP' ;", "/bin/sh", "-c", "gosu postgres pg_ctl stop -m smart -t 120"] + #command: ["/bin/sh", "-c", "echo 'Hello from the preStop handler'; gosu postgres pg_ctl stop -m smart -t 120"] + #command: ["gosu postgres", "pg_ctl stop -m smart -t 120"] + #command: ["/bin/sh", "-c"] + #args: ["gosu postgres pg_ctl stop -m smart -t 120"] + #command: ["/bin/sh", "-c", "gosu postgres 'pg_ctl stop -m smart -t 120'"] + #command: ["/bin/sh", "-c", "gosu postgres '/usr/lib/postgresql/16/bin/pg_ctl stop -m smart -t 120'"] + #command: ["/bin/sh -c 'gosu postgres /usr/lib/postgresql/16/bin/pg_ctl stop -m smart -t 120'"] + command: ["/bin/sh", "-c", "gosu postgres /usr/lib/postgresql/16/bin/pg_ctl stop -m smart -t 120"] + #command: ["/bin/sh", "-c", "echo 'Hello from the preStop handler' > /usr/share/message && cat /usr/share/message"] + #command: ["sh", "-c", "trap 'gosu postgres pg_ctl stop -m smart' SIGTERM; gosu postgres postgres"] # trap: SIGTERM: bad trap + readinessProbe: + exec: + command: + - pg_isready + - -U + - postgres + initialDelaySeconds: 15 + periodSeconds: 60 + ports: + - {containerPort: 5433} + securityContext: + allowPrivilegeEscalation: false + #runAsNonRoot: true + #runAsUser: 1000 + #runAsGroup: 1000 + #capabilities: + # drop: + # - ALL + #readOnlyRootFilesystem: true #could not create lock file "/var/run/postgresql/.s.PGSQL.5432.lock": Read-only file system + resources: + limits: {cpu: 16000m, memory: 128Gi} + requests: {cpu: 1000m, memory: 1Gi} + #, ephemeral-storage: "1536Gi"} + volumeMounts: + - {mountPath: /data, name: benchmark-data-volume} + - {mountPath: /dev/shm, name: dshm} + - {mountPath: /var/lib/postgresql/data, name: benchmark-storage-volume} + args: [ + "-c", "max_worker_processes=64", + "-c", "max_parallel_workers=64", + "-c", "max_parallel_workers_per_gather=64", + "-c", "max_parallel_maintenance_workers=64", # only for PostgreSQL > 10 (?) + "-c", "max_wal_size=32GB", + "-c", "shared_buffers=64GB", + #"-c", "shared_memory_size=32GB", # read-only + "-c", "max_connections=2048", + "-c", "autovacuum_max_workers=10", + "-c", "autovacuum_vacuum_cost_limit=3000", + "-c", "vacuum_cost_limit=1000", + "-c", "checkpoint_completion_target=0.9", + "-c", "cpu_tuple_cost=0.03", + "-c", "effective_cache_size=64GB", + "-c", "maintenance_work_mem=2GB", + #"-c", "max_connections=1700", + #"-c", "random_page_cost=1.1", + "-c", "wal_buffers=1GB", + "-c", "work_mem=32GB", + #"-c", "huge_pages=on", + "-c", "temp_buffers=4GB", + "-c", "autovacuum_work_mem=-1", + "-c", "max_stack_depth=7MB", + "-c", "max_files_per_process=4000", + "-c", "effective_io_concurrency=32", + "-c", "wal_level=minimal", + "-c", "max_wal_senders=0", + "-c", "synchronous_commit=off", + "-c", "checkpoint_timeout=1h", + "-c", "checkpoint_warning=0", + "-c", "autovacuum=off", + "-c", "max_locks_per_transaction=64", + "-c", "max_pred_locks_per_transaction=64", + "-c", "default_statistics_target=1000", + "-c", "random_page_cost=60" + ] + # , "-c", "listen_addresses='*'", "-c", "logging_collector=on" + # , "-c", "pg_stat_statements.save=off", "-c", "pg_stat_statements.track=all", "-c", "shared_preload_libraries='pg_stat_statements'" + - name: cadvisor + image: gcr.io/cadvisor/cadvisor:v0.47.0 + args: ["--port", "9300", "--storage_duration", "20m0s", "--docker_only", "true", "--disable_metrics", "disk,network,tcp,advtcp,udp,sched,process,hugetlb", "--application_metrics_count_limit", "30", "--housekeeping_interval", "5s"] + ports: + - containerPort: 9300 + #hostPort: 9300 + name: http + protocol: TCP + securityContext: + allowPrivilegeEscalation: false + #runAsNonRoot: true + #runAsUser: 1000 + #runAsGroup: 1000 + #capabilities: + # drop: + # - ALL + readOnlyRootFilesystem: true + resources: + requests: {cpu: 150m, memory: 200Mi} + limits: {cpu: 16000m, memory: 128Gi} + volumeMounts: + - name: rootfs + mountPath: /rootfs + readOnly: true + - name: var-run + mountPath: /var/run + readOnly: true + - name: sys + mountPath: /sys + readOnly: true + - name: docker + mountPath: /var/lib/docker + readOnly: true + - name: disk + mountPath: /dev/disk + readOnly: true + volumes: + - name: benchmark-data-volume + persistentVolumeClaim: {claimName: bexhoma-data} + - name: benchmark-storage-volume + persistentVolumeClaim: {claimName: bexhoma-storage} + - name: rootfs + hostPath: + path: / + - name: var-run + hostPath: + path: /var/run + - name: sys + hostPath: + path: /sys + - name: docker + hostPath: + path: /var/lib/docker + - name: disk + hostPath: + path: /dev/disk + - name: dshm + emptyDir: + medium: Memory From dbd79c72c958ba69ae2d8f63c780da4c3e6427ea Mon Sep 17 00:00:00 2001 From: perdelt Date: Mon, 5 Aug 2024 14:06:38 +0200 Subject: [PATCH 2/6] Test Cases: Cleaned and unified --- docs/TestCases.md | 190 ++++++++++++++++++++++++-- test-docs.sh | 49 +++++++ test.sh | 336 +++++++++++++++++++++++++++++++++++++++------- 3 files changed, 517 insertions(+), 58 deletions(-) create mode 100644 test-docs.sh diff --git a/docs/TestCases.md b/docs/TestCases.md index c5ce8c4a..668419e7 100644 --- a/docs/TestCases.md +++ b/docs/TestCases.md @@ -1,5 +1,12 @@ # Test Cases +There is a variety of combination of options to be tested. + +We here list some more basic use cases to test the functionality of bexhoma. + +See [repository](https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/blob/master/test.sh) for implementations. +You will have to change the node selectors there. + ## TPC-H @@ -7,8 +14,11 @@ `python tpch.py -dt -nlp 8 -nlt 8 -sf 1 -ii -ic -is -dbms PostgreSQL run` -* SF=1, loaded by 8 pods, indexed, into PostgreSQL -* 1 execution stream (power test) +* SF = 1 +* PostgreSQL 8 loader, indexed +* 1x(1) benchmarker = 1 execution stream (power test) +* no persistent storage +* no monitoring yields (after ca. 10 minutes) something like @@ -88,8 +98,12 @@ PostgreSQL-BHT-8-1 1 1 1 30 1 1 `python tpch.py -dt -nlp 8 -nlt 8 -sf 1 -ii -ic -is -dbms PostgreSQL -m -mc run` -* SF=1, loaded by 8 pods, indexed, into PostgreSQL -* 1 execution stream (power test) +* SF = 1 +* PostgreSQL 8 loader, indexed +* 1x(1) benchmarker = 1 execution stream (power test) +* no persistent storage +* no monitoring +* monitoring all components yields (after ca. 10 minutes) something like @@ -181,6 +195,17 @@ PostgreSQL-BHT-8-1 0 0 0.0 0.0 ``` +### TPC-H Throughput Test + +`python tpch.py -dt -nlp 8 -nlt 8 -sf 1 -ii -ic -is -dbms PostgreSQL -m -mc -rst shared -rss 100Gi run` + +* SF = 1 +* PostgreSQL 8 loader, indexed +* 2x(1,2) benchmarker = 1 and 2 execution streams +* persistent storage of class shared +* monitoring all components + +yields (after ca. 10 minutes) something like @@ -240,6 +265,7 @@ PostgreSQL-BHT-1-1 253.0 1.0 1.0 227.667984 * 16 terminals in 1 pod * target is 16384 ops * monitoring of all components activated +* no persistent storage yields (after ca. 10 minutes) something like @@ -293,17 +319,65 @@ PostgreSQL-BHT-1-1 280.62 0 4.22 5.95 PostgreSQL-BHT-1-1 193.35 0 1.41 1.41 ``` +### Benchbase Complex + +`python benchbase.py -ltf 16 -dbms PostgreSQL -nvu 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run` + +* 16 warehouses +* 16 terminals in 1 pod and 16 terminals in 2 pods (8 each) +* target is 16384 ops +* data is stored persistently in a PV of type shared and size 30Gi +* monitoring of all components activated + +yields (after ca. 10 minutes) something like + +``` +## Show Summary + +### Workload + Benchbase Workload SF=16 (warehouses for TPC-C) + This includes no queries. Benchbase runs the benchmark + This experiment compares run time and resource consumption of Benchbase queries in different DBMS. Benchbase data is generated and loaded using several threads. Benchmark is limited to DBMS PostgreSQL. Benchmark is tpcc. + +### Connections +PostgreSQL-BHT-1-1 uses docker image postgres:16.1 + RAM:541031743488 + CPU:AMD Opteron(tm) Processor 6378 + Cores:64 + host:5.4.0-105-generic + node:cl-worker13 + disk:1386631412 + datadisk:4409168 + requests_cpu:4 + requests_memory:16Gi + +### Execution + experiment_run terminals target pod_count time Throughput (requests/second) Latency Distribution.95th Percentile Latency (microseconds) Latency Distribution.Average Latency (microseconds) +PostgreSQL-BHT-1-1 1 16 16384 1 60.0 2421.65 11612.0 6561.0 + +Warehouses: 16 + +### Workflow +DBMS PostgreSQL-BHT-1 - Pods [[1]] + +### Loading + time_load terminals pods Imported warehouses [1/h] +PostgreSQL-BHT-1-1 253.0 1.0 1.0 227.667984 + +``` + ## HammerDB ### HammerDB Simple -`python hammerdb.py -dbms PostgreSQL -nvu "8" -su 16 -sf 16 -nbp 2 run` +`python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 run` * 16 warehouses * 16 threads used for loading -* 8 terminals in 2 pod +* 8 terminals in 1 pod +* no persistent storage yields (after ca. 10 minutes) @@ -344,12 +418,13 @@ PostgreSQL-BHT-16-2-1 94.0 16.0 2.0 612.765957 ### HammerDB Monitoring -`python hammerdb.py -dbms PostgreSQL -nvu "8" -su 16 -sf 16 -nbp 2 -m -mc run` +`python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -m -mc run` * 16 warehouses * 16 threads used for loading -* 8 terminals in 2 pod +* 8 terminals in 1 pod * monitoring of all components activated +* no persistent storage yields (after ca. 10 minutes) @@ -403,15 +478,109 @@ PostgreSQL-BHT-16-2-1 15336.25 36.38 5.02 5.6 PostgreSQL-BHT-16-2-1 7.32 0.01 0.05 0.05 ``` +### HammerDB Complex + +`python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run` + +* 16 warehouses +* 16 threads used for loading +* 8 terminals in 1 pod and in 2 pods (4 each) +* data is stored persistently in a PV of type shared and size 30Gi +* monitoring of all components activated + +yields (after ca. 10 minutes) + +``` +## Show Summary + +### Workload + HammerDB Workload SF=16 (warehouses for TPC-C) + This includes no queries. HammerDB runs the benchmark + This experiment compares run time and resource consumption of TPC-C queries in different DBMS. TPC-C data is generated and loaded using several threads. Benchmark is limited to DBMS PostgreSQL. + +### Connections +PostgreSQL-BHT-16-2-1 uses docker image postgres:16.1 + RAM:541037633536 + CPU:AMD Opteron(tm) Processor 6378 + Cores:64 + host:5.4.0-81-generic + node:cl-worker11 + disk:450769736 + datadisk:3376936 + requests_cpu:4 + requests_memory:16Gi + +### Execution + experiment_run vusers client pod_count NOPM TPM duration errors +PostgreSQL-BHT-16-2-1 1 8 1 2 9728.0 30066.0 5 0 + +Warehouses: 16 + +### Workflow +DBMS PostgreSQL-BHT-16-2 - Pods [[2]] + +### Loading + time_load terminals pods Imported warehouses [1/h] +PostgreSQL-BHT-16-2-1 94.0 16.0 2.0 612.765957 +``` + + + ## YCSB +### YCSB Loader Test for Persistency + +`python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a -ne 1,2 -nc 2 -rst shared -rss 100Gi run` + +* SF = 1 (1 million rows and operations) +* PostgreSQL +* Workload A +* 64 loader threads, split into 8 parallel pods +* persistent storage of class shared +* 64 execution threads, split into 8 parallel pods +* [1,2] execute (64 threads in 8 pods and 128 threads in 16 pods) +* target is 16384 ops +* run twice + +yields (after ca. 10 minutes) something like + +``` +## Show Summary + +### Workload + YCSB SF=1 + This includes no queries. YCSB runs the benchmark + This experiment compares run time and resource consumption of YCSB queries. YCSB is performed using several threads and processes. Benchmark is limited to DBMS ['PostgreSQL']. YCSB data is loaded using several processes. Benchmark is limited to DBMS PostgreSQL. + +### Connections +PostgreSQL-64-8-16384-1 uses docker image postgres:16.1 + RAM:541037633536 + CPU:AMD Opteron(tm) Processor 6378 + Cores:64 + host:5.4.0-81-generic + node:cl-worker11 + disk:449814036 + datadisk:2455656 + requests_cpu:4 + requests_memory:16Gi + +### Loading + experiment_run threads target pod_count [OVERALL].Throughput(ops/sec) [OVERALL].RunTime(ms) [INSERT].Return=OK [INSERT].99thPercentileLatency(us) +PostgreSQL-64-8-16384 1 64 16384 8 16336.733043 61226.0 1000000 1075.375 + +### Execution + experiment_run threads target pod_count [OVERALL].Throughput(ops/sec) [OVERALL].RunTime(ms) [READ].Return=OK [READ].99thPercentileLatency(us) [UPDATE].Return=OK [UPDATE].99thPercentileLatency(us) +PostgreSQL-64-8-16384-1 1 64 16384 8 16334.03 61253.0 499897 549.88 500103 730.0 +``` + ### YCSB Execution `python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a run` -* 1 million rows and operations +* python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a -m -mc run +* SF = 1 (1 million rows and operations) * workload A * 64 loader threads, split into 8 parallel pods * 64 execution threads, split into 8 parallel pods @@ -452,7 +621,7 @@ PostgreSQL-64-8-16384-1 1 64 16384 8 `python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a -m -mc run` -* 1 million rows and operations +* SF = 1 (1 million rows and operations) * workload A * 64 loader threads, split into 8 parallel pods * 64 execution threads, split into 8 parallel pods @@ -511,7 +680,6 @@ PostgreSQL-64-8-16384-1 13.6 0 0.32 0.33 - ## Preinstalled YugabyteDB ### YCSB Execution diff --git a/test-docs.sh b/test-docs.sh new file mode 100644 index 00000000..6aff0592 --- /dev/null +++ b/test-docs.sh @@ -0,0 +1,49 @@ +#!/bin/bash + +mkdir -p ./logs/ + +BEXHOMA_NODE_SUT="cl-worker11" +BEXHOMA_NODE_LOAD="cl-worker19" +BEXHOMA_NODE_BENCHMARK="cl-worker19" + + + + +#### YCSB Loader Test for docs +# SF = 1 +# PostgreSQL 1 and 8 loader +# [1,2,3,4,5,6,7,8] times 16384 = target +# monitoring all components +# no persistent storage +nohup python ycsb.py -ms 1 -m -mc --workload a -tr \ + -dbms PostgreSQL \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + run &>logs/test_ycsb_docs_1.log & + + watch -n 30 tail -n 50 logs/test_ycsb_docs_1.log + + +#### Wait so that experiments receive different codes +sleep 5 + + +#### TPC-H Power Test - compare DBMS for docs +# SF = 1 +# PostgreSQL 8 loader +# MonetDB 8 loader +# MySQL 8 loader threads +# 1x(1) benchmarker +# monitoring all components +# no persistent storage +nohup python tpch.py -ms 1 -m -mc -dt -sf 1 -ii -ic -is \ + -nlp 8 -nlt 8 \ + -nc 1 -ne 1 \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -t 1200 \ + run &>logs/test_tpch_docs_1.log & + +# watch -n 30 tail -n 50 logs/test_tpch_docs_1.log + + +#### Wait so that experiments receive different codes +sleep 5 diff --git a/test.sh b/test.sh index 19de12bc..81bd8c6d 100644 --- a/test.sh +++ b/test.sh @@ -7,85 +7,174 @@ BEXHOMA_NODE_LOAD="cl-worker19" BEXHOMA_NODE_BENCHMARK="cl-worker19" +#### YCSB Loader Test for Persistency (TestCases.md) +# SF = 1 (1 million rows and operations) +# PostgreSQL +# Workload A +# 64 loader threads, split into 8 parallel pods +# persistent storage of class shared +# 64 execution threads, split into 8 parallel pods +# [1,2] execute (64 threads in 8 pods and 128 threads in 16 pods) +# target is 16384 ops +# run twice +nohup python ycsb.py -ms 1 -tr \ + --workload a \ + -nlp 8 \ + -dbms PostgreSQL \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -ne 1,2 \ + -nc 2 \ + -ltf 1 \ + -rst shared -rss 100Gi \ + run &>logs/test_ycsb_testcase_1.log & + +#watch -n 30 tail -n 50 logs/test_ycsb_testcase_1.log + + +#### Wait so that experiments receive different codes +sleep 5 -#### YCSB Loader Test for docs +#### YCSB Execution Test # SF = 1 -# PostgreSQL 1 and 8 loader -# [1,2,3,4,5,6,7,8] times 16384 = target -nohup python ycsb.py -ms 1 -m --workload a -tr \ +# PostgreSQL 1 loader +# 2x(1,2) benchmarker +# persistent storage of class shared +#nohup python ycsb.py -ms 1 -m --workload a -tr \ +# -nlp 1 \ +# -dbms PostgreSQL \ +# -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ +# -ne 1,2 \ +# -nc 2 \ +# -ltf 2 \ +# -rst shared -rss 100Gi \ +# run &>logs/test_ycsb_testcase_2.log & + +# watch -n 30 tail -n 50 logs/test_ycsb_testcase_2.log + + +#### Wait so that experiments receive different codes +#sleep 5 + + +#### YCSB Execution Test (TestCases.md) +# python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a run +# SF = 1 (1 million rows and operations) +# workload A +# 64 loader threads, split into 8 parallel pods +# 64 execution threads, split into 8 parallel pods +# target is 16384 ops +nohup python ycsb.py -ms 1 --workload a -tr \ + -nlp 8 -su 64 \ -dbms PostgreSQL \ -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ - run &>logs/test_ycsb_1.log & + -ne 1 \ + -nc 1 \ + -ltf 1 \ + run &>logs/test_ycsb_testcase_3.log & -# watch -n 30 tail -n 50 logs/test_ycsb_1.log +# watch -n 30 tail -n 50 logs/test_ycsb_testcase_3.log #### Wait so that experiments receive different codes sleep 5 -#### YCSB Loader Test for persistency -# SF = 1 -# PostgreSQL 8 loader -# 16384 = target -# run twice -# [1,2] execute -# persistent storage of class shared -nohup python ycsb.py -ms 1 -m --workload a -tr \ - -nlp 8 \ +#### YCSB Execution Monitoring (TestCases.md) +# python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a -m -mc run +# SF = 1 (1 million rows and operations) +# workload A +# 64 loader threads, split into 8 parallel pods +# 64 execution threads, split into 8 parallel pods +# target is 16384 ops +# monitoring of all components activated +nohup python ycsb.py -ms 1 --workload a -tr \ + -nlp 8 -su 64 \ -dbms PostgreSQL \ -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ - -ne 1,2 \ - -nc 2 \ + -ne 1 \ + -nc 1 \ -ltf 1 \ - -rst shared -rss 100Gi \ - run &>logs/test_ycsb_2.log & + -m -mc \ + run &>logs/test_ycsb_testcase_4.log & -# watch -n 30 tail -n 50 logs/test_ycsb_2.log +# watch -n 30 tail -n 50 logs/test_ycsb_testcase_4.log #### Wait so that experiments receive different codes sleep 5 -#### YCSB Execution Test -# SF = 1 -# PostgreSQL 1 loader +#### YCSB Execution Complex (TestCases.md) +# python ycsb.py -ltf 1 -nlp 8 -su 64 -sf 1 -dbms PostgreSQL -wl a -rst shared -rss 30Gi -m -mc -ne 1,2 -nc 2 run +# SF = 1 (1 million rows and operations) +# workload A +# 64 loader threads, split into 8 parallel pods +# 64 execution threads, split into 8 parallel pods +# target is 16384 ops +# data is stored persistently in a PV of type shared and size 30Gi # 2x(1,2) benchmarker -# persistent storage of class shared -nohup python ycsb.py -ms 1 -m --workload a -tr \ - -nlp 1 \ - -dbms PostgreSQL \ +# monitoring of all components activated +#nohup python ycsb.py -ms 1 --workload a -tr \ +# -nlp 8 -su 64 \ +# -dbms PostgreSQL \ +# -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ +# -ne 1,2 \ +# -nc 2 \ +# -ltf 1 \ +# -m -mc \ +# -rst shared -rss 30Gi \ +# run &>logs/test_ycsb_testcase_5.log & + +# watch -n 30 tail -n 50 logs/test_ycsb_testcase_5.log + + +#### Wait so that experiments receive different codes +#sleep 5 + + + + + +#### TPC-H Power Test - only PostgreSQL (TestCases.md) +# python tpch.py -dt -nlp 8 -nlt 8 -sf 1 -ii -ic -is -dbms PostgreSQL run +# SF = 1 +# PostgreSQL 8 loader, indexed +# 1x(1) benchmarker = 1 execution stream (power test) +# no persistent storage +# no monitoring +nohup python tpch.py -ms 1 -dt -sf 1 -ii -ic -is \ + -nlp 8 -nlt 8 \ + -nc 1 -ne 1 \ -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ - -ne 1,2 \ - -nc 2 \ - -ltf 2 \ - -rst shared -rss 100Gi \ - run &>logs/test_ycsb_3.log & + -t 1200 \ + -dbms PostgreSQL \ + run &>logs/test_tpch_testcase_1.log & -# watch -n 30 tail -n 50 logs/test_ycsb_3.log +# watch -n 30 tail -n 50 logs/test_tpch_testcase_1.log #### Wait so that experiments receive different codes sleep 5 -#### TPC-H Power Test +#### TPC-H Monitoring Test (TestCases.md) +# python tpch.py -dt -nlp 8 -nlt 8 -sf 1 -ii -ic -is -dbms PostgreSQL -m -mc run # SF = 1 -# PostgreSQL 8 loader -# MonetDB 8 loader -# MySQL 8 loader threads -# 1x(1) benchmarker +# PostgreSQL 8 loader, indexed +# 1x(1) benchmarker = 1 execution stream (power test) # no persistent storage -nohup python tpch.py -ms 1 -m -dt -sf 1 -ii -ic -is \ +# monitoring all components +nohup python tpch.py -ms 1 -dt -sf 1 -ii -ic -is \ -nlp 8 -nlt 8 \ -nc 1 -ne 1 \ -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ -t 1200 \ - run &>logs/test_tpch_1.log & + -dbms PostgreSQL \ + -m -mc \ + run &>logs/test_tpch_testcase_2.log & -# watch -n 30 tail -n 50 logs/test_tpch_1.log +# watch -n 30 tail -n 50 logs/test_tpch_testcase_2.log #### Wait so that experiments receive different codes @@ -93,17 +182,170 @@ sleep 5 #### TPC-H Throughput Test +# python tpch.py -dt -nlp 8 -nlt 8 -sf 1 -ii -ic -is -dbms PostgreSQL -m -mc -rst shared -rss 100Gi run # SF = 1 -# PostgreSQL 8 loader -# 2x(1,2) benchmarker +# PostgreSQL 8 loader, indexed +# 2x(1,2) benchmarker = 1 and 2 execution streams # persistent storage of class shared -nohup python tpch.py -ms 1 -m -dt -sf 1 -ii -ic -is \ +# monitoring all components +nohup python tpch.py -ms 1 -dt -sf 1 -ii -ic -is \ -nlp 8 -nlt 8 \ -nc 2 -ne 1,2 \ -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ - -dbms PostgreSQL -t 1200 \ + -t 1200 \ + -dbms PostgreSQL \ + -m -mc \ -rst shared -rss 100Gi \ - run &>logs/test_tpch_2.log & + run &>logs/test_tpch_testcase_3.log & + +# watch -n 30 tail -n 50 logs/test_tpch_testcase_3.log + + +#### Wait so that experiments receive different codes +sleep 5 + + + + + + +#### Benchbase Simple +# python benchbase.py -ltf 16 -dbms PostgreSQL -nvu 16 -sf 16 -nbp 1 run +# 16 warehouses +# 16 terminals in 1 pod +# target is 16384 ops +# no persistent storage +nohup python benchbase.py \ + -sf 16 \ + -ltf 16 \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -dbms PostgreSQL \ + -nvu 16 \ + -nbp 1 \ + run &>logs/test_benchbase_testcase_1.log & + +# watch -n 30 tail -n 50 logs/test_benchbase_testcase_1.log + + +#### Wait so that experiments receive different codes +sleep 5 + + +#### Benchbase Monitoring +# python benchbase.py -ltf 16 -dbms PostgreSQL -nvu 16 -sf 16 -nbp 1 -m -mc run +# 16 warehouses +# 16 terminals in 1 pod +# target is 16384 ops +# monitoring of all components activated +# no persistent storage +nohup python benchbase.py \ + -sf 16 \ + -ltf 16 \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -dbms PostgreSQL \ + -nvu 16 \ + -nbp 1 \ + -m -mc \ + run &>logs/test_benchbase_testcase_2.log & + +# watch -n 30 tail -n 50 logs/test_benchbase_testcase_2.log + + +#### Wait so that experiments receive different codes +sleep 5 + + +#### Benchbase Complex +# python benchbase.py -ltf 16 -dbms PostgreSQL -nvu 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run +# 16 warehouses +# 16 terminals in 1 pod and 16 terminals in 2 pods (8 each) +# target is 16384 ops +# data is stored persistently in a PV of type shared and size 30Gi +# monitoring of all components activated +# run twice +nohup python benchbase.py \ + -sf 16 \ + -ltf 16 \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -dbms PostgreSQL \ + -nvu 16 \ + -nbp 1,2 \ + -m -mc \ + -rst shared -rss 30Gi \ + -nc 2 \ + run &>logs/test_benchbase_testcase_3.log & + +# watch -n 30 tail -n 50 logs/test_benchbase_testcase_3.log + + +#### Wait so that experiments receive different codes +sleep 5 + + -# watch -n 30 tail -n 50 logs/test_tpch_2.log +#### HammerDB Simple +# python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 run +# 16 warehouses +# 16 threads used for loading +# 8 terminals in 1 pod +# no persistent storage +nohup python hammerdb.py \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -dbms PostgreSQL \ + -nvu '8' \ + -su 16 \ + -sf 16 \ + -nbp 1 \ + run &>logs/test_hammerdb_testcase_1.log & + +# watch -n 30 tail -n 50 logs/test_hammerdb_testcase_1.log + + +#### Wait so that experiments receive different codes +sleep 5 + + +#### HammerDB Monitoring +# python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -m -mc run +# 16 warehouses +# 16 threads used for loading +# 8 terminals in 1 pod +# monitoring of all components activated +# no persistent storage +nohup python hammerdb.py \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -dbms PostgreSQL \ + -nvu '8' \ + -su 16 \ + -sf 16 \ + -nbp 1 \ + -m -mc \ + run &>logs/test_hammerdb_testcase_2.log & + +# watch -n 30 tail -n 50 logs/test_hammerdb_testcase_2.log + + +#### Wait so that experiments receive different codes +sleep 5 + + +#### HammerDB Complex +# python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run +# 16 warehouses +# 16 threads used for loading +# 8 terminals in 1 pod and in 2 pods (4 each) +# data is stored persistently in a PV of type shared and size 30Gi +# monitoring of all components activated +nohup python hammerdb.py \ + -rnn $BEXHOMA_NODE_SUT -rnl $BEXHOMA_NODE_LOAD -rnb $BEXHOMA_NODE_BENCHMARK \ + -dbms PostgreSQL \ + -nvu '8' \ + -su 16 \ + -sf 16 \ + -nbp 1 \ + -m -mc \ + -rst shared -rss 30Gi \ + run &>logs/test_hammerdb_testcase_3.log & + +# watch -n 30 tail -n 50 logs/test_hammerdb_testcase_3.log From bf4357793047c3289afed996b7ad30866bd657b6 Mon Sep 17 00:00:00 2001 From: perdelt Date: Mon, 5 Aug 2024 17:11:27 +0200 Subject: [PATCH 3/6] Docs: More about HammerDB --- docs/Example-HammerDB.md | 301 + docs/TestCases.md | 6 +- hammerdb.py | 4 +- .../notebooks/Evaluate-Benchbase.html | 9987 +++++++++++++++ .../notebooks/Evaluate-Benchbase.ipynb | 2875 +++++ .../notebooks/Evaluate-HammerDB.html | 10447 ++++++++++++++++ .../notebooks/Evaluate-HammerDB.ipynb | 3002 +++++ test.sh | 6 +- 8 files changed, 26621 insertions(+), 7 deletions(-) create mode 100644 docs/Example-HammerDB.md create mode 100644 images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html create mode 100644 images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.ipynb create mode 100644 images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.html create mode 100644 images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.ipynb diff --git a/docs/Example-HammerDB.md b/docs/Example-HammerDB.md new file mode 100644 index 00000000..ea33e2b6 --- /dev/null +++ b/docs/Example-HammerDB.md @@ -0,0 +1,301 @@ +# Example: HammerDB + + + +About the benchmark [1]: +> The TPC-C specification on which TPROC-C is based implements a computer system to fulfil orders from customers to supply products from a company. The company sells 100,000 items and keeps its stock in warehouses. Each warehouse has 10 sales districts and each district serves 3000 customers. The customers call the company whose operators take the order, each order containing a number of items. Orders are usually satisfied from the local warehouse however a small number of items are not in stock at a particular point in time and are supplied by an alternative warehouse. It is important to note that the size of the company is not fixed and can add Warehouses and sales districts as the company grows. For this reason your test schema can be as small or large as you wish with a larger schema requiring a more powerful computer system to process the increased level of transactions. The TPROC-C schema is shown below, in particular note how the number of rows in all of the tables apart from the ITEM table which is fixed is dependent upon the number of warehouses you choose to create your schema. + +drawing + +About the metrics [2]: +> HammerDB workloads produce 2 statistics to compare systems called **TPM** and NOPM respectively. NOPM value is based on a metric captured from within the test schema itself. As such **NOPM (New Orders per minute)** as a performance metric independent of any particular database implementation is the recommended primary metric to use. + +References +1. https://www.hammerdb.com/docs/ch03s05.html +1. https://www.hammerdb.com/docs/ch03s04.html +1. https://www.hammerdb.com/docs/ch03.html + +## Perform Benchmark + +For performing the experiment we can run the [hammerdb file](https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/blob/master/hammerdb.py). + +Example: `python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -sd 5 run` + +This +* starts a clean instance of PostgreSQL (`-dbms`) + * data directory inside a Docker container +* starts 1 loader pod (per DBMS) that + * creates TPC-C schema in the database + * imports data for 16 (`-sf`) warehouses into the DBMS + * using 16 (`-su`) threads +* runs 1 (`-nbp`) streams of TPC-C queries (per DBMS) + * running for 5 (`-sd`) minutes + * each stream (pod) having 8 threads (`-nvu`) to simulate 8 users +* with a maximum of 1 DBMS per time (`-ms`) +* tests if results match workflow (`-tr`) +* shows a summary + +### Status + +You can watch the status while benchmark is running via `bexperiments status` + +``` +Dashboard: Running +Message Queue: Running +Data directory: Running +Result directory: Running ++------------------------+--------------+--------------+-------------+--------------+ +| 1706264335 | sut | loaded [s] | loading | monitoring | ++========================+==============+==============+=============+==============+ +| PostgreSQL-64-1-131072 | (1. Running) | 0.64 | (1 Running) | (Running) | ++------------------------+--------------+--------------+-------------+--------------+ +``` + +The code `1706264335` is the unique identifier of the experiment. +You can find the number also in the output of `hammerdb.py`. + +### Cleanup + +The script is supposed to clean up and remove everything from the cluster that is related to the experiment after finishing. +If something goes wrong, you can also clean up manually with `bexperiment stop` (removes everything) or `bexperiment stop -e 1706264335` (removes everything that is related to experiment `1706264335`). + +## Evaluate Results + +At the end of a benchmark you will see a summary like + +```bash +### Loading + threads target pod_count [OVERALL].Throughput(ops/sec) [OVERALL].RunTime(ms) [INSERT].Return=OK [INSERT].99thPercentileLatency(us) +PostgreSQL-64-1-16384 64 16384 1 16285.849226 61403.0 1000000 1283.00 +PostgreSQL-64-8-16384 64 16384 8 16189.808395 62334.0 1000000 1029.25 +PostgreSQL-64-1-32768 64 32768 1 32334.206357 30927.0 1000000 2993.00 +PostgreSQL-64-8-32768 64 32768 8 32487.310483 30788.0 1000000 2362.50 +PostgreSQL-64-1-49152 64 49152 1 47429.330298 21084.0 1000000 4343.00 +PostgreSQL-64-8-49152 64 49152 8 48401.920774 20850.0 1000000 3848.50 +PostgreSQL-64-1-65536 64 65536 1 63881.436055 15654.0 1000000 6127.00 +PostgreSQL-64-8-65536 64 65536 8 64436.143011 15540.0 1000000 4843.00 +PostgreSQL-64-1-81920 64 81920 1 71078.257161 14069.0 1000000 6219.00 +PostgreSQL-64-8-81920 64 81920 8 72415.868804 14361.0 1000000 5296.00 +PostgreSQL-64-1-98304 64 98304 1 81586.032471 12257.0 1000000 5027.00 +PostgreSQL-64-8-98304 64 98304 8 86657.160474 11681.0 1000000 5571.00 +PostgreSQL-64-1-114688 64 114688 1 74693.755602 13388.0 1000000 5923.00 +PostgreSQL-64-8-114688 64 114688 8 80616.643342 13037.0 1000000 5275.50 +PostgreSQL-64-1-131072 64 131072 1 81766.148814 12230.0 1000000 6087.00 +PostgreSQL-64-8-131072 64 131072 8 80708.979092 12469.0 1000000 5656.00 + +### Execution + threads target pod_count [OVERALL].Throughput(ops/sec) [OVERALL].RunTime(ms) [READ].Return=OK [READ].99thPercentileLatency(us) [UPDATE].Return=OK [UPDATE].99thPercentileLatency(us) +PostgreSQL-64-1-16384-1 64 16384 1 16281.61 61419.0 499663 540.00 500337 743.00 +PostgreSQL-64-8-16384-1 64 16384 8 16313.68 61310.0 500621 544.75 499379 759.38 +PostgreSQL-64-1-32768-1 64 32768 1 32171.93 31083.0 500316 570.00 499684 925.00 +PostgreSQL-64-8-32768-1 64 32768 8 32481.38 30794.0 500704 594.88 499296 839.75 +PostgreSQL-64-1-49152-1 64 49152 1 48351.22 20682.0 499465 808.00 500535 1395.00 +PostgreSQL-64-8-49152-1 64 49152 8 48521.04 20624.0 500275 946.75 499725 1554.88 +PostgreSQL-64-1-65536-1 64 65536 1 62468.77 16008.0 499253 1069.00 500747 1656.00 +PostgreSQL-64-8-65536-1 64 65536 8 64434.09 15541.0 500305 1056.00 499695 1617.00 +PostgreSQL-64-1-81920-1 64 81920 1 78659.64 12713.0 500203 1313.00 499797 2055.00 +PostgreSQL-64-8-81920-1 64 81920 8 79285.81 12740.0 500409 1337.38 499591 2126.25 +PostgreSQL-64-1-98304-1 64 98304 1 89421.44 11183.0 499133 1425.00 500867 2767.00 +PostgreSQL-64-8-98304-1 64 98304 8 87541.47 11748.0 500122 1363.75 499878 2414.00 +PostgreSQL-64-1-114688-1 64 114688 1 101770.81 9826.0 500000 1351.00 500000 2213.00 +PostgreSQL-64-8-114688-1 64 114688 8 104663.23 9835.0 500450 1515.62 499550 2866.25 +PostgreSQL-64-1-131072-1 64 131072 1 88354.83 11318.0 499788 1566.00 500212 3451.00 +PostgreSQL-64-8-131072-1 64 131072 8 115356.26 9250.0 500084 1526.75 499916 3356.75 +``` + +We can see that the overall throughput is close to the target and that scaled-out drivers (8 pods with 8 threads each) have similar results as a monolithic driver (1 pod with 64 thread). +The runtime is between 8 seconds and 1 minute. + +To see the summary of experiment `1706264335` you can simply call `python hammerdb.py -e 1706264335 summary`. + +### Detailed Evaluation + +Results are transformed into pandas DataFrames and can be inspected in detail. +See for example +* [Jupyter Notebooks](https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/images/evaluator_dbmsbenchmarker/notebooks/) + +You can connect to an evaluation server in the cluster by `bexperiments dashboard`. +This forwards ports, so you have +* a Jupyter notebook server at http://localhost:8888 + +You can connect to an evaluation server locally by `bexperiments jupyter`. +This forwards ports, so you have +* a Jupyter notebook server at http://localhost:8888 + +## Adjust Parameters + +The script supports +* exact repetitions for statistical confidence +* variations to scan a large parameters space +* combine results for easy evaluation + +There are various ways to change parameters. + +### Manifests + +The YAML manifests for the components can be found in https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/k8s + +### Dockerfiles + +The Dockerfiles for the components can be found in https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/images/hammerdb + +### Command line + +You maybe want to adjust some of the parameters that are set in the file: `python hammerdb.py -h` + +```bash +usage: ycsb.py [-h] [-aws] [-dbms {PostgreSQL,MySQL}] [-db] [-cx CONTEXT] [-e EXPERIMENT] [-m] [-mc] [-ms MAX_SUT] [-nc NUM_CONFIG] [-ne NUM_QUERY_EXECUTORS] [-nl NUM_LOADING] [-nlp NUM_LOADING_PODS] [-wl {a,b,c,e,f}] [-sf SCALING_FACTOR] [-sfo SCALING_FACTOR_OPERATIONS] [-su SCALING_USERS] + [-sbs SCALING_BATCHSIZE] [-ltf LIST_TARGET_FACTORS] [-tb TARGET_BASE] [-t TIMEOUT] [-rr REQUEST_RAM] [-rc REQUEST_CPU] [-rct REQUEST_CPU_TYPE] [-rg REQUEST_GPU] [-rgt REQUEST_GPU_TYPE] [-rst {None,,local-hdd,shared}] [-rss REQUEST_STORAGE_SIZE] [-rnn REQUEST_NODE_NAME] [-rnl REQUEST_NODE_LOADING] + [-rnb REQUEST_NODE_BENCHMARKING] [-tr] + {run,start,load,summary} + +Perform YCSB benchmarks in a Kubernetes cluster. Number of rows and operations is SF*1,000,000. This installs a clean copy for each target and split of the driver. Optionally monitoring is activated. + +positional arguments: + {run,start,load,summary} + import YCSB data or run YCSB queries + +options: + -h, --help show this help message and exit + -aws, --aws fix components to node groups at AWS + -dbms {PostgreSQL,MySQL}, --dbms {PostgreSQL,MySQL} + DBMS to load the data + -db, --debug dump debug informations + -cx CONTEXT, --context CONTEXT + context of Kubernetes (for a multi cluster environment), default is current context + -e EXPERIMENT, --experiment EXPERIMENT + sets experiment code for continuing started experiment + -m, --monitoring activates monitoring for sut + -mc, --monitoring-cluster + activates monitoring for all nodes of cluster + -ms MAX_SUT, --max-sut MAX_SUT + maximum number of parallel DBMS configurations, default is no limit + -nc NUM_CONFIG, --num-config NUM_CONFIG + number of runs per configuration + -ne NUM_QUERY_EXECUTORS, --num-query-executors NUM_QUERY_EXECUTORS + comma separated list of number of parallel clients + -nl NUM_LOADING, --num-loading NUM_LOADING + number of parallel loaders per configuration + -nlp NUM_LOADING_PODS, --num-loading-pods NUM_LOADING_PODS + total number of loaders per configuration + -wl {a,b,c,e,f}, --workload {a,b,c,e,f} + YCSB default workload + -sf SCALING_FACTOR, --scaling-factor SCALING_FACTOR + scaling factor (SF) = number of rows in millions + -sfo SCALING_FACTOR_OPERATIONS, --scaling-factor-operations SCALING_FACTOR_OPERATIONS + scaling factor = number of operations in millions (=SF if not set) + -su SCALING_USERS, --scaling-users SCALING_USERS + scaling factor = number of total threads + -sbs SCALING_BATCHSIZE, --scaling-batchsize SCALING_BATCHSIZE + batch size + -ltf LIST_TARGET_FACTORS, --list-target-factors LIST_TARGET_FACTORS + comma separated list of factors of 16384 ops as target - default range(1,9) + -tb TARGET_BASE, --target-base TARGET_BASE + ops as target, base for factors - default 16384 = 2**14 + -t TIMEOUT, --timeout TIMEOUT + timeout for a run of a query + -rr REQUEST_RAM, --request-ram REQUEST_RAM + request ram for sut, default 16Gi + -rc REQUEST_CPU, --request-cpu REQUEST_CPU + request cpus for sut, default 4 + -rct REQUEST_CPU_TYPE, --request-cpu-type REQUEST_CPU_TYPE + request node for sut to have node label cpu= + -rg REQUEST_GPU, --request-gpu REQUEST_GPU + request number of gpus for sut + -rgt REQUEST_GPU_TYPE, --request-gpu-type REQUEST_GPU_TYPE + request node for sut to have node label gpu= + -rst {None,,local-hdd,shared}, --request-storage-type {None,,local-hdd,shared} + request persistent storage of certain type + -rss REQUEST_STORAGE_SIZE, --request-storage-size REQUEST_STORAGE_SIZE + request persistent storage of certain size + -rnn REQUEST_NODE_NAME, --request-node-name REQUEST_NODE_NAME + request a specific node for sut + -rnl REQUEST_NODE_LOADING, --request-node-loading REQUEST_NODE_LOADING + request a specific node for loading pods + -rnb REQUEST_NODE_BENCHMARKING, --request-node-benchmarking REQUEST_NODE_BENCHMARKING + request a specific node for benchmarking pods + -tr, --test-result test if result fulfills some basic requirements +``` + +## Monitoring + +[Monitoring](Monitoring.html) can be activated for DBMS only (`-m`) or for all components (`-mc`). + +If monitoring is activated, the summary also contains a section like + +```bash +### Ingestion + SUT - CPU of Ingestion (via counter) [CPUs] SUT - Max RAM of Ingestion [Gb] +PostgreSQL-64-1-16384-1 211.08 3.56 +PostgreSQL-64-1-32768-1 208.34 3.51 +PostgreSQL-64-1-49152-1 43.55 2.78 +PostgreSQL-64-1-65536-1 95.57 3.16 +PostgreSQL-64-1-81920-1 224.71 3.50 +PostgreSQL-64-1-98304-1 208.72 3.50 +PostgreSQL-64-1-114688-1 39.80 2.74 +PostgreSQL-64-1-131072-1 142.15 3.47 +PostgreSQL-64-8-16384-1 192.93 3.51 +PostgreSQL-64-8-32768-1 185.90 3.50 +PostgreSQL-64-8-49152-1 191.40 3.81 +PostgreSQL-64-8-65536-1 189.31 3.77 +PostgreSQL-64-8-81920-1 141.00 3.46 +PostgreSQL-64-8-98304-1 117.22 3.28 +PostgreSQL-64-8-114688-1 209.95 3.50 +PostgreSQL-64-8-131072-1 208.55 3.50 + +### Execution + SUT - CPU of Execution (via counter) [CPUs] SUT - Max RAM of Execution [Gb] +PostgreSQL-64-1-16384-1 158.03 4.02 +PostgreSQL-64-1-32768-1 171.52 4.02 +PostgreSQL-64-1-49152-1 131.15 3.98 +PostgreSQL-64-1-65536-1 185.56 3.68 +PostgreSQL-64-1-81920-1 0.00 3.50 +PostgreSQL-64-1-98304-1 0.00 3.50 +PostgreSQL-64-1-114688-1 0.00 3.50 +PostgreSQL-64-1-131072-1 0.00 3.50 +PostgreSQL-64-8-16384-1 122.51 3.98 +PostgreSQL-64-8-32768-1 110.22 3.97 +PostgreSQL-64-8-49152-1 163.70 4.00 +PostgreSQL-64-8-65536-1 0.00 3.50 +PostgreSQL-64-8-81920-1 169.54 4.00 +PostgreSQL-64-8-98304-1 66.88 3.92 +PostgreSQL-64-8-114688-1 190.45 3.69 +PostgreSQL-64-8-131072-1 146.15 4.02 +``` + +This gives a survey about CPU (in CPU seconds) and RAM usage (in Gb) during loading and execution of the benchmark. + +In this example, metrics are very instable. Metrics are fetched every 30 seconds. +This is too coarse for such a quick example. + + +## Use Persistent Storage + +The default behaviour of bexhoma is that the database is stored inside the ephemeral storage of the Docker container. +If your cluster allows dynamic provisioning of volumes, you might request a persistent storage of a certain type (storageClass) and size. + +Example: `python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -sd 5 -nc 2 -rst local-hdd -rss 50Gi run` + +The following status shows we have two volumes of type `local-hdd`. Every experiment running HammerDB's TPC-C of SF=16 (warehouses) will take the databases from these volumes and skip loading. +In this example `-nc` is set to two, that is the complete experiment is repeated twice for statistical confidence. +The first instance of PostgreSQL mounts the volume and generates the data. +All other instances just use the database without generating and loading data. + +``` ++------------------------------------+-----------------+--------------+--------------+-------------------+------------+----------------------+-----------+----------+--------+--------+ +| Volumes | configuration | experiment | loaded [s] | timeLoading [s] | dbms | storage_class_name | storage | status | size | used | ++====================================+=================+==============+==============+===================+============+======================+===========+==========+========+========+ +| bexhoma-storage-postgresql-ycsb-1 | postgresql | ycsb-1 | True | 64 | PostgreSQL | shared | 50Gi | Bound | 50G | 2.1G | ++------------------------------------+-----------------+--------------+--------------+-------------------+------------+----------------------+-----------+----------+--------+--------+ ++------------------+--------------+--------------+--------------------------+ + ++------------------+--------------+--------------+--------------+---------------+ +| 1706957093 | sut | loaded [s] | monitoring | benchmarker | ++==================+==============+==============+==============+===============+ +| MySQL-64-1-16384 | (2. Running) | 2398.11 | (Running) | (1. Running) | ++------------------+--------------+--------------+--------------+---------------+ +``` + + + + diff --git a/docs/TestCases.md b/docs/TestCases.md index 668419e7..7ab19379 100644 --- a/docs/TestCases.md +++ b/docs/TestCases.md @@ -372,7 +372,7 @@ PostgreSQL-BHT-1-1 253.0 1.0 1.0 227.667984 ### HammerDB Simple -`python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 run` +`python hammerdb.py -tr -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 run` * 16 warehouses * 16 threads used for loading @@ -418,7 +418,7 @@ PostgreSQL-BHT-16-2-1 94.0 16.0 2.0 612.765957 ### HammerDB Monitoring -`python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -m -mc run` +`python hammerdb.py -tr -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -m -mc run` * 16 warehouses * 16 threads used for loading @@ -480,7 +480,7 @@ PostgreSQL-BHT-16-2-1 7.32 0.01 0.05 0.05 ### HammerDB Complex -`python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run` +`python hammerdb.py -tr -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run` * 16 warehouses * 16 threads used for loading diff --git a/hammerdb.py b/hammerdb.py index a45601f8..96df169f 100644 --- a/hammerdb.py +++ b/hammerdb.py @@ -29,7 +29,7 @@ """ # argparse parser = argparse.ArgumentParser(description=description) - parser.add_argument('mode', help='start sut, also load data or also run the TPC-C queries', choices=['run', 'start', 'load']) + parser.add_argument('mode', help='start sut, also load data or also run the TPC-C queries', choices=['run', 'start', 'load', 'summary']) parser.add_argument('-aws', '--aws', help='fix components to node groups at AWS', action='store_true', default=False) parser.add_argument('-dbms', help='DBMS to load the data', choices=['PostgreSQL', 'MonetDB', 'SingleStore', 'CockroachDB', 'MySQL', 'MariaDB', 'YugabyteDB', 'Kinetica']) parser.add_argument('-db', '--debug', help='dump debug informations', action='store_true') @@ -302,6 +302,8 @@ end = default_timer() end_datetime = str(datetime.datetime.now()) duration_experiment = end - start + elif args.mode == 'summary': + experiment.show_summary() else: # configure number of clients per config #list_clients = args.num_query_executors.split(",") diff --git a/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html new file mode 100644 index 00000000..055943bc --- /dev/null +++ b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html @@ -0,0 +1,9987 @@ + + + + + +Evaluate-Benchbase-Result + + + + + + + + + + + + +
+ + + + + + + + + + + + + + + + + +
+ + diff --git a/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.ipynb b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.ipynb new file mode 100644 index 00000000..160480e1 --- /dev/null +++ b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.ipynb @@ -0,0 +1,2875 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Evaluate Benchbase Result\n", + "\n", + "About the benchmark:\n", + "> The Twitter workload is inspired by the popular micro-blogging website. In order to provide a realistic benchmark, we obtained an anonymized snapshot of the Twitter social graph from August 2009 that contains 51 million users and almost 2 billion “follows” relationships [14]. We created a synthetic workload generator that is based on an approximation of the queries/transactions needed to support the application functionalities as we observe them by using the web site, along with information derived from a data set of 200,000 tweets. Although we do not claim that this is a precise representation of Twitter’s system, it still reflects its important characteristics, such as heavily skewed many-to-many relationships.\n", + "\n", + "\"drawing\"\n", + "\n", + "References:\n", + "1. https://github.com/cmu-db/benchbase/wiki/Twitter\n", + "1. http://www.vldb.org/pvldb/vol7/p277-difallah.pdf\n", + "\n", + "## Import Packages" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import os\n", + "import re\n", + "import matplotlib.pyplot as plt\n", + "import pickle\n", + "# Some nice output\n", + "pd.set_option(\"display.max_rows\", None)\n", + "pd.set_option('display.max_colwidth', None)\n", + "from IPython.display import display, Markdown\n", + "%matplotlib inline\n", + "\n", + "import evaluator" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prepare Result\n", + "\n", + "### Pick Result" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "code = \"1674056386\"\n", + "path = \"./\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Start Evaluation" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation = evaluator.benchbase(code=code, path=path)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Transform all Benchmarking Log Files to DataFrames\n", + "\n", + "We also pick the first log file to be an example for later" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "filename_example = \"\"\n", + "\n", + "directory = os.fsencode(path+\"/\"+code)\n", + "for file in os.listdir(directory):\n", + " filename = os.fsdecode(file)\n", + " if filename.startswith(\"bexhoma-benchmarker\") and filename.endswith(\".log\"):\n", + " #print(\"filename:\", filename)\n", + " pod_name = filename[filename.rindex(\"-\")+1:-len(\".log\")]\n", + " #print(\"pod_name:\", pod_name)\n", + " jobname = filename[len(\"bexhoma-benchmarker-\"):-len(\"-\"+pod_name+\".log\")]\n", + " #print(\"jobname:\", jobname)\n", + " evaluation.end_benchmarking(jobname)\n", + " filename_example = filename" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Show a DataFrame for single Pod as Example" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ".//1674056386/bexhoma-benchmarker-postgresql-24-1-8192-1674056386-1-2-knmk6.log.df.pickle\n" + ] + }, + { + "data": { + "text/html": [ + "
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PostgreSQL-24-1-8192-2
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" + ], + "text/plain": [ + " connection configuration \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "\n", + " experiment_run client pod pod_count bench \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 1 2 knmk6 2 twitter \n", + "\n", + " profile target time ... \\\n", + "PostgreSQL-24-1-8192-2 ... \n", + "0 postgres 8192 60 ... \n", + "\n", + " Throughput (requests/second) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 8195.028745 \n", + "\n", + " Latency Distribution.95th Percentile Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 488 \n", + "\n", + " Latency Distribution.Maximum Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 1121505 \n", + "\n", + " Latency Distribution.Median Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 305 \n", + "\n", + " Latency Distribution.Minimum Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 157 \n", + "\n", + " Latency Distribution.25th Percentile Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 274 \n", + "\n", + " Latency Distribution.90th Percentile Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 422 \n", + "\n", + " Latency Distribution.99th Percentile Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 816 \n", + "\n", + " Latency Distribution.75th Percentile Latency (microseconds) \\\n", + "PostgreSQL-24-1-8192-2 \n", + "0 351 \n", + "\n", + " Latency Distribution.Average Latency (microseconds) \n", + "PostgreSQL-24-1-8192-2 \n", + "0 377 \n", + "\n", + "[1 rows x 32 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "filename = path+\"/\"+code+\"/\"+filename_example+\".df.pickle\"\n", + "print(filename)\n", + "df = pd.read_pickle(filename)\n", + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Transform all DataFrames into single Result DataFrame" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation.evaluate_results()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Get Benchmarking Result" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connection_pod
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" + ], + "text/plain": [ + " connection configuration \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 MySQL-24-1-8192-1 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2-1 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2-2 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-1-1 PostgreSQL-24-1-8192-1 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2-1 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2-2 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "\n", + " experiment_run client pod pod_count bench \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1 1 888k8 1 twitter \n", + "MySQL-24-1-8192-2-1 1 2 rq47v 2 twitter \n", + "MySQL-24-1-8192-2-2 1 2 x6ccb 2 twitter \n", + "PostgreSQL-24-1-8192-1-1 1 1 tcmm6 1 twitter \n", + "PostgreSQL-24-1-8192-2-1 1 2 c55nz 2 twitter \n", + "PostgreSQL-24-1-8192-2-2 1 2 knmk6 2 twitter \n", + "\n", + " profile target time ... \\\n", + "connection_pod ... \n", + "MySQL-24-1-8192-1-1 mysql 8192 60 ... \n", + "MySQL-24-1-8192-2-1 mysql 8192 60 ... \n", + "MySQL-24-1-8192-2-2 mysql 8192 60 ... \n", + "PostgreSQL-24-1-8192-1-1 postgres 8192 60 ... \n", + "PostgreSQL-24-1-8192-2-1 postgres 8192 60 ... \n", + "PostgreSQL-24-1-8192-2-2 postgres 8192 60 ... \n", + "\n", + " Throughput (requests/second) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 8169.239439 \n", + "MySQL-24-1-8192-2-1 8192.148440 \n", + "MySQL-24-1-8192-2-2 8192.153750 \n", + "PostgreSQL-24-1-8192-1-1 8194.124865 \n", + "PostgreSQL-24-1-8192-2-1 8194.278354 \n", + "PostgreSQL-24-1-8192-2-2 8195.028745 \n", + "\n", + " Latency Distribution.95th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 582 \n", + "MySQL-24-1-8192-2-1 576 \n", + "MySQL-24-1-8192-2-2 455 \n", + "PostgreSQL-24-1-8192-1-1 239 \n", + "PostgreSQL-24-1-8192-2-1 276 \n", + "PostgreSQL-24-1-8192-2-2 488 \n", + "\n", + " Latency Distribution.Maximum Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1662909 \n", + "MySQL-24-1-8192-2-1 920932 \n", + "MySQL-24-1-8192-2-2 922579 \n", + "PostgreSQL-24-1-8192-1-1 732040 \n", + "PostgreSQL-24-1-8192-2-1 1365207 \n", + "PostgreSQL-24-1-8192-2-2 1121505 \n", + "\n", + " Latency Distribution.Median Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 407 \n", + "MySQL-24-1-8192-2-1 347 \n", + "MySQL-24-1-8192-2-2 286 \n", + "PostgreSQL-24-1-8192-1-1 116 \n", + "PostgreSQL-24-1-8192-2-1 120 \n", + "PostgreSQL-24-1-8192-2-2 305 \n", + "\n", + " Latency Distribution.Minimum Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 198 \n", + "MySQL-24-1-8192-2-1 166 \n", + "MySQL-24-1-8192-2-2 116 \n", + "PostgreSQL-24-1-8192-1-1 58 \n", + "PostgreSQL-24-1-8192-2-1 57 \n", + "PostgreSQL-24-1-8192-2-2 157 \n", + "\n", + " Latency Distribution.25th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 381 \n", + "MySQL-24-1-8192-2-1 320 \n", + "MySQL-24-1-8192-2-2 259 \n", + "PostgreSQL-24-1-8192-1-1 103 \n", + "PostgreSQL-24-1-8192-2-1 107 \n", + "PostgreSQL-24-1-8192-2-2 274 \n", + "\n", + " Latency Distribution.90th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 502 \n", + "MySQL-24-1-8192-2-1 460 \n", + "MySQL-24-1-8192-2-2 375 \n", + "PostgreSQL-24-1-8192-1-1 188 \n", + "PostgreSQL-24-1-8192-2-1 215 \n", + "PostgreSQL-24-1-8192-2-2 422 \n", + "\n", + " Latency Distribution.99th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1107 \n", + "MySQL-24-1-8192-2-1 2287 \n", + "MySQL-24-1-8192-2-2 1358 \n", + "PostgreSQL-24-1-8192-1-1 411 \n", + "PostgreSQL-24-1-8192-2-1 570 \n", + "PostgreSQL-24-1-8192-2-2 816 \n", + "\n", + " Latency Distribution.75th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 442 \n", + "MySQL-24-1-8192-2-1 385 \n", + "MySQL-24-1-8192-2-2 320 \n", + "PostgreSQL-24-1-8192-1-1 139 \n", + "PostgreSQL-24-1-8192-2-1 149 \n", + "PostgreSQL-24-1-8192-2-2 351 \n", + "\n", + " Latency Distribution.Average Latency (microseconds) \n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 746 \n", + "MySQL-24-1-8192-2-1 865 \n", + "MySQL-24-1-8192-2-2 752 \n", + "PostgreSQL-24-1-8192-1-1 175 \n", + "PostgreSQL-24-1-8192-2-1 185 \n", + "PostgreSQL-24-1-8192-2-2 377 \n", + "\n", + "[6 rows x 32 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = evaluation.get_df_benchmarking()\n", + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Reconstruct workflow out of result" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'MySQL-24-1-8192': [[1, 2]], 'PostgreSQL-24-1-8192': [[1, 2]]}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation.reconstruct_workflow(df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot Results\n", + "\n", + "#### Set data types for plotting" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countbenchprofiletargettime...Throughput (requests/second)Latency Distribution.95th Percentile Latency (microseconds)Latency Distribution.Maximum Latency (microseconds)Latency Distribution.Median Latency (microseconds)Latency Distribution.Minimum Latency (microseconds)Latency Distribution.25th Percentile Latency (microseconds)Latency Distribution.90th Percentile Latency (microseconds)Latency Distribution.99th Percentile Latency (microseconds)Latency Distribution.75th Percentile Latency (microseconds)Latency Distribution.Average Latency (microseconds)
connection_pod
MySQL-24-1-8192-1-1MySQL-24-1-8192-1MySQL-24-1-819211888k81twittermysql819260.0...8169.239439582.01662909.0407.0198.0381.0502.01107.0442.0746.0
MySQL-24-1-8192-2-1MySQL-24-1-8192-2MySQL-24-1-819212rq47v2twittermysql819260.0...8192.148440576.0920932.0347.0166.0320.0460.02287.0385.0865.0
MySQL-24-1-8192-2-2MySQL-24-1-8192-2MySQL-24-1-819212x6ccb2twittermysql819260.0...8192.153750455.0922579.0286.0116.0259.0375.01358.0320.0752.0
PostgreSQL-24-1-8192-1-1PostgreSQL-24-1-8192-1PostgreSQL-24-1-819211tcmm61twitterpostgres819260.0...8194.124865239.0732040.0116.058.0103.0188.0411.0139.0175.0
PostgreSQL-24-1-8192-2-1PostgreSQL-24-1-8192-2PostgreSQL-24-1-819212c55nz2twitterpostgres819260.0...8194.278354276.01365207.0120.057.0107.0215.0570.0149.0185.0
PostgreSQL-24-1-8192-2-2PostgreSQL-24-1-8192-2PostgreSQL-24-1-819212knmk62twitterpostgres819260.0...8195.028745488.01121505.0305.0157.0274.0422.0816.0351.0377.0
\n", + "

6 rows × 32 columns

\n", + "
" + ], + "text/plain": [ + " connection configuration \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 MySQL-24-1-8192-1 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2-1 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2-2 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-1-1 PostgreSQL-24-1-8192-1 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2-1 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2-2 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "\n", + " experiment_run client pod pod_count bench \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1 1 888k8 1 twitter \n", + "MySQL-24-1-8192-2-1 1 2 rq47v 2 twitter \n", + "MySQL-24-1-8192-2-2 1 2 x6ccb 2 twitter \n", + "PostgreSQL-24-1-8192-1-1 1 1 tcmm6 1 twitter \n", + "PostgreSQL-24-1-8192-2-1 1 2 c55nz 2 twitter \n", + "PostgreSQL-24-1-8192-2-2 1 2 knmk6 2 twitter \n", + "\n", + " profile target time ... \\\n", + "connection_pod ... \n", + "MySQL-24-1-8192-1-1 mysql 8192 60.0 ... \n", + "MySQL-24-1-8192-2-1 mysql 8192 60.0 ... \n", + "MySQL-24-1-8192-2-2 mysql 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-1-1 postgres 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-2-1 postgres 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-2-2 postgres 8192 60.0 ... \n", + "\n", + " Throughput (requests/second) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 8169.239439 \n", + "MySQL-24-1-8192-2-1 8192.148440 \n", + "MySQL-24-1-8192-2-2 8192.153750 \n", + "PostgreSQL-24-1-8192-1-1 8194.124865 \n", + "PostgreSQL-24-1-8192-2-1 8194.278354 \n", + "PostgreSQL-24-1-8192-2-2 8195.028745 \n", + "\n", + " Latency Distribution.95th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 582.0 \n", + "MySQL-24-1-8192-2-1 576.0 \n", + "MySQL-24-1-8192-2-2 455.0 \n", + "PostgreSQL-24-1-8192-1-1 239.0 \n", + "PostgreSQL-24-1-8192-2-1 276.0 \n", + "PostgreSQL-24-1-8192-2-2 488.0 \n", + "\n", + " Latency Distribution.Maximum Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1662909.0 \n", + "MySQL-24-1-8192-2-1 920932.0 \n", + "MySQL-24-1-8192-2-2 922579.0 \n", + "PostgreSQL-24-1-8192-1-1 732040.0 \n", + "PostgreSQL-24-1-8192-2-1 1365207.0 \n", + "PostgreSQL-24-1-8192-2-2 1121505.0 \n", + "\n", + " Latency Distribution.Median Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 407.0 \n", + "MySQL-24-1-8192-2-1 347.0 \n", + "MySQL-24-1-8192-2-2 286.0 \n", + "PostgreSQL-24-1-8192-1-1 116.0 \n", + "PostgreSQL-24-1-8192-2-1 120.0 \n", + "PostgreSQL-24-1-8192-2-2 305.0 \n", + "\n", + " Latency Distribution.Minimum Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 198.0 \n", + "MySQL-24-1-8192-2-1 166.0 \n", + "MySQL-24-1-8192-2-2 116.0 \n", + "PostgreSQL-24-1-8192-1-1 58.0 \n", + "PostgreSQL-24-1-8192-2-1 57.0 \n", + "PostgreSQL-24-1-8192-2-2 157.0 \n", + "\n", + " Latency Distribution.25th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 381.0 \n", + "MySQL-24-1-8192-2-1 320.0 \n", + "MySQL-24-1-8192-2-2 259.0 \n", + "PostgreSQL-24-1-8192-1-1 103.0 \n", + "PostgreSQL-24-1-8192-2-1 107.0 \n", + "PostgreSQL-24-1-8192-2-2 274.0 \n", + "\n", + " Latency Distribution.90th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 502.0 \n", + "MySQL-24-1-8192-2-1 460.0 \n", + "MySQL-24-1-8192-2-2 375.0 \n", + "PostgreSQL-24-1-8192-1-1 188.0 \n", + "PostgreSQL-24-1-8192-2-1 215.0 \n", + "PostgreSQL-24-1-8192-2-2 422.0 \n", + "\n", + " Latency Distribution.99th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1107.0 \n", + "MySQL-24-1-8192-2-1 2287.0 \n", + "MySQL-24-1-8192-2-2 1358.0 \n", + "PostgreSQL-24-1-8192-1-1 411.0 \n", + "PostgreSQL-24-1-8192-2-1 570.0 \n", + "PostgreSQL-24-1-8192-2-2 816.0 \n", + "\n", + " Latency Distribution.75th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 442.0 \n", + "MySQL-24-1-8192-2-1 385.0 \n", + "MySQL-24-1-8192-2-2 320.0 \n", + "PostgreSQL-24-1-8192-1-1 139.0 \n", + "PostgreSQL-24-1-8192-2-1 149.0 \n", + "PostgreSQL-24-1-8192-2-2 351.0 \n", + "\n", + " Latency Distribution.Average Latency (microseconds) \n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 746.0 \n", + "MySQL-24-1-8192-2-1 865.0 \n", + "MySQL-24-1-8192-2-2 752.0 \n", + "PostgreSQL-24-1-8192-1-1 175.0 \n", + "PostgreSQL-24-1-8192-2-1 185.0 \n", + "PostgreSQL-24-1-8192-2-2 377.0 \n", + "\n", + "[6 rows x 32 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_plot = evaluation.benchmarking_set_datatypes(df)\n", + "\n", + "df_plot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Restrict result to specific part" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countbenchprofiletargettime...Throughput (requests/second)Latency Distribution.95th Percentile Latency (microseconds)Latency Distribution.Maximum Latency (microseconds)Latency Distribution.Median Latency (microseconds)Latency Distribution.Minimum Latency (microseconds)Latency Distribution.25th Percentile Latency (microseconds)Latency Distribution.90th Percentile Latency (microseconds)Latency Distribution.99th Percentile Latency (microseconds)Latency Distribution.75th Percentile Latency (microseconds)Latency Distribution.Average Latency (microseconds)
connection_pod
MySQL-24-1-8192-1-1MySQL-24-1-8192-1MySQL-24-1-819211888k81twittermysql819260.0...8169.239439582.01662909.0407.0198.0381.0502.01107.0442.0746.0
MySQL-24-1-8192-2-1MySQL-24-1-8192-2MySQL-24-1-819212rq47v2twittermysql819260.0...8192.148440576.0920932.0347.0166.0320.0460.02287.0385.0865.0
MySQL-24-1-8192-2-2MySQL-24-1-8192-2MySQL-24-1-819212x6ccb2twittermysql819260.0...8192.153750455.0922579.0286.0116.0259.0375.01358.0320.0752.0
PostgreSQL-24-1-8192-1-1PostgreSQL-24-1-8192-1PostgreSQL-24-1-819211tcmm61twitterpostgres819260.0...8194.124865239.0732040.0116.058.0103.0188.0411.0139.0175.0
PostgreSQL-24-1-8192-2-1PostgreSQL-24-1-8192-2PostgreSQL-24-1-819212c55nz2twitterpostgres819260.0...8194.278354276.01365207.0120.057.0107.0215.0570.0149.0185.0
PostgreSQL-24-1-8192-2-2PostgreSQL-24-1-8192-2PostgreSQL-24-1-819212knmk62twitterpostgres819260.0...8195.028745488.01121505.0305.0157.0274.0422.0816.0351.0377.0
\n", + "

6 rows × 32 columns

\n", + "
" + ], + "text/plain": [ + " connection configuration \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 MySQL-24-1-8192-1 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2-1 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2-2 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-1-1 PostgreSQL-24-1-8192-1 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2-1 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2-2 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "\n", + " experiment_run client pod pod_count bench \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1 1 888k8 1 twitter \n", + "MySQL-24-1-8192-2-1 1 2 rq47v 2 twitter \n", + "MySQL-24-1-8192-2-2 1 2 x6ccb 2 twitter \n", + "PostgreSQL-24-1-8192-1-1 1 1 tcmm6 1 twitter \n", + "PostgreSQL-24-1-8192-2-1 1 2 c55nz 2 twitter \n", + "PostgreSQL-24-1-8192-2-2 1 2 knmk6 2 twitter \n", + "\n", + " profile target time ... \\\n", + "connection_pod ... \n", + "MySQL-24-1-8192-1-1 mysql 8192 60.0 ... \n", + "MySQL-24-1-8192-2-1 mysql 8192 60.0 ... \n", + "MySQL-24-1-8192-2-2 mysql 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-1-1 postgres 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-2-1 postgres 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-2-2 postgres 8192 60.0 ... \n", + "\n", + " Throughput (requests/second) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 8169.239439 \n", + "MySQL-24-1-8192-2-1 8192.148440 \n", + "MySQL-24-1-8192-2-2 8192.153750 \n", + "PostgreSQL-24-1-8192-1-1 8194.124865 \n", + "PostgreSQL-24-1-8192-2-1 8194.278354 \n", + "PostgreSQL-24-1-8192-2-2 8195.028745 \n", + "\n", + " Latency Distribution.95th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 582.0 \n", + "MySQL-24-1-8192-2-1 576.0 \n", + "MySQL-24-1-8192-2-2 455.0 \n", + "PostgreSQL-24-1-8192-1-1 239.0 \n", + "PostgreSQL-24-1-8192-2-1 276.0 \n", + "PostgreSQL-24-1-8192-2-2 488.0 \n", + "\n", + " Latency Distribution.Maximum Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1662909.0 \n", + "MySQL-24-1-8192-2-1 920932.0 \n", + "MySQL-24-1-8192-2-2 922579.0 \n", + "PostgreSQL-24-1-8192-1-1 732040.0 \n", + "PostgreSQL-24-1-8192-2-1 1365207.0 \n", + "PostgreSQL-24-1-8192-2-2 1121505.0 \n", + "\n", + " Latency Distribution.Median Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 407.0 \n", + "MySQL-24-1-8192-2-1 347.0 \n", + "MySQL-24-1-8192-2-2 286.0 \n", + "PostgreSQL-24-1-8192-1-1 116.0 \n", + "PostgreSQL-24-1-8192-2-1 120.0 \n", + "PostgreSQL-24-1-8192-2-2 305.0 \n", + "\n", + " Latency Distribution.Minimum Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 198.0 \n", + "MySQL-24-1-8192-2-1 166.0 \n", + "MySQL-24-1-8192-2-2 116.0 \n", + "PostgreSQL-24-1-8192-1-1 58.0 \n", + "PostgreSQL-24-1-8192-2-1 57.0 \n", + "PostgreSQL-24-1-8192-2-2 157.0 \n", + "\n", + " Latency Distribution.25th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 381.0 \n", + "MySQL-24-1-8192-2-1 320.0 \n", + "MySQL-24-1-8192-2-2 259.0 \n", + "PostgreSQL-24-1-8192-1-1 103.0 \n", + "PostgreSQL-24-1-8192-2-1 107.0 \n", + "PostgreSQL-24-1-8192-2-2 274.0 \n", + "\n", + " Latency Distribution.90th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 502.0 \n", + "MySQL-24-1-8192-2-1 460.0 \n", + "MySQL-24-1-8192-2-2 375.0 \n", + "PostgreSQL-24-1-8192-1-1 188.0 \n", + "PostgreSQL-24-1-8192-2-1 215.0 \n", + "PostgreSQL-24-1-8192-2-2 422.0 \n", + "\n", + " Latency Distribution.99th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 1107.0 \n", + "MySQL-24-1-8192-2-1 2287.0 \n", + "MySQL-24-1-8192-2-2 1358.0 \n", + "PostgreSQL-24-1-8192-1-1 411.0 \n", + "PostgreSQL-24-1-8192-2-1 570.0 \n", + "PostgreSQL-24-1-8192-2-2 816.0 \n", + "\n", + " Latency Distribution.75th Percentile Latency (microseconds) \\\n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 442.0 \n", + "MySQL-24-1-8192-2-1 385.0 \n", + "MySQL-24-1-8192-2-2 320.0 \n", + "PostgreSQL-24-1-8192-1-1 139.0 \n", + "PostgreSQL-24-1-8192-2-1 149.0 \n", + "PostgreSQL-24-1-8192-2-2 351.0 \n", + "\n", + " Latency Distribution.Average Latency (microseconds) \n", + "connection_pod \n", + "MySQL-24-1-8192-1-1 746.0 \n", + "MySQL-24-1-8192-2-1 865.0 \n", + "MySQL-24-1-8192-2-2 752.0 \n", + "PostgreSQL-24-1-8192-1-1 175.0 \n", + "PostgreSQL-24-1-8192-2-1 185.0 \n", + "PostgreSQL-24-1-8192-2-2 377.0 \n", + "\n", + "[6 rows x 32 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#df_plot = df_plot[df_plot[\"experiment_run\"]==\"1\"]\n", + "#df_plot = df_plot[df_plot[\"client\"] == 1]\n", + "df_plot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "\n", + "column = \"profile\"\n", + "x = \"target\"\n", + "y = \"Throughput (requests/second)\"\n", + "plot_by = \"experiment_run\"\n", + "\n", + "evaluation.plot(df_plot, column=column, x=x, y=y, plot_by=plot_by)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "column = \"profile\"\n", + "x = \"target\"\n", + "y = \"Latency Distribution.95th Percentile Latency (microseconds)\"\n", + "evaluation.plot(df_plot, column=column, x=x, y=y, plot_by=\"experiment_run\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Aggregate by parallel pods" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countbenchprofiletargettime...Throughput (requests/second)Latency Distribution.95th Percentile Latency (microseconds)Latency Distribution.Maximum Latency (microseconds)Latency Distribution.Median Latency (microseconds)Latency Distribution.Minimum Latency (microseconds)Latency Distribution.25th Percentile Latency (microseconds)Latency Distribution.90th Percentile Latency (microseconds)Latency Distribution.99th Percentile Latency (microseconds)Latency Distribution.75th Percentile Latency (microseconds)Latency Distribution.Average Latency (microseconds)
MySQL-24-1-8192-1MySQL-24-1-8192-1MySQL-24-1-819211888k81twittermysql819260.0...8169.239439582.01662909.0407.0198.0381.0502.01107.0442.0746.0
MySQL-24-1-8192-2MySQL-24-1-8192-2MySQL-24-1-819212rq47vx6ccb2twittermysql1638460.0...16384.302191576.0922579.0347.0116.0320.0460.02287.0385.0808.5
PostgreSQL-24-1-8192-1PostgreSQL-24-1-8192-1PostgreSQL-24-1-819211tcmm61twitterpostgres819260.0...8194.124865239.0732040.0116.058.0103.0188.0411.0139.0175.0
PostgreSQL-24-1-8192-2PostgreSQL-24-1-8192-2PostgreSQL-24-1-819212c55nzknmk62twitterpostgres1638460.0...16389.307099488.01365207.0305.057.0274.0422.0816.0351.0281.0
\n", + "

4 rows × 32 columns

\n", + "
" + ], + "text/plain": [ + " connection configuration \\\n", + "MySQL-24-1-8192-1 MySQL-24-1-8192-1 MySQL-24-1-8192 \n", + "MySQL-24-1-8192-2 MySQL-24-1-8192-2 MySQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-1 PostgreSQL-24-1-8192-1 PostgreSQL-24-1-8192 \n", + "PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192-2 PostgreSQL-24-1-8192 \n", + "\n", + " experiment_run client pod pod_count \\\n", + "MySQL-24-1-8192-1 1 1 888k8 1 \n", + "MySQL-24-1-8192-2 1 2 rq47vx6ccb 2 \n", + "PostgreSQL-24-1-8192-1 1 1 tcmm6 1 \n", + "PostgreSQL-24-1-8192-2 1 2 c55nzknmk6 2 \n", + "\n", + " bench profile target time ... \\\n", + "MySQL-24-1-8192-1 twitter mysql 8192 60.0 ... \n", + "MySQL-24-1-8192-2 twitter mysql 16384 60.0 ... \n", + "PostgreSQL-24-1-8192-1 twitter postgres 8192 60.0 ... \n", + "PostgreSQL-24-1-8192-2 twitter postgres 16384 60.0 ... \n", + "\n", + " Throughput (requests/second) \\\n", + "MySQL-24-1-8192-1 8169.239439 \n", + "MySQL-24-1-8192-2 16384.302191 \n", + "PostgreSQL-24-1-8192-1 8194.124865 \n", + "PostgreSQL-24-1-8192-2 16389.307099 \n", + "\n", + " Latency Distribution.95th Percentile Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 582.0 \n", + "MySQL-24-1-8192-2 576.0 \n", + "PostgreSQL-24-1-8192-1 239.0 \n", + "PostgreSQL-24-1-8192-2 488.0 \n", + "\n", + " Latency Distribution.Maximum Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 1662909.0 \n", + "MySQL-24-1-8192-2 922579.0 \n", + "PostgreSQL-24-1-8192-1 732040.0 \n", + "PostgreSQL-24-1-8192-2 1365207.0 \n", + "\n", + " Latency Distribution.Median Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 407.0 \n", + "MySQL-24-1-8192-2 347.0 \n", + "PostgreSQL-24-1-8192-1 116.0 \n", + "PostgreSQL-24-1-8192-2 305.0 \n", + "\n", + " Latency Distribution.Minimum Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 198.0 \n", + "MySQL-24-1-8192-2 116.0 \n", + "PostgreSQL-24-1-8192-1 58.0 \n", + "PostgreSQL-24-1-8192-2 57.0 \n", + "\n", + " Latency Distribution.25th Percentile Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 381.0 \n", + "MySQL-24-1-8192-2 320.0 \n", + "PostgreSQL-24-1-8192-1 103.0 \n", + "PostgreSQL-24-1-8192-2 274.0 \n", + "\n", + " Latency Distribution.90th Percentile Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 502.0 \n", + "MySQL-24-1-8192-2 460.0 \n", + "PostgreSQL-24-1-8192-1 188.0 \n", + "PostgreSQL-24-1-8192-2 422.0 \n", + "\n", + " Latency Distribution.99th Percentile Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 1107.0 \n", + "MySQL-24-1-8192-2 2287.0 \n", + "PostgreSQL-24-1-8192-1 411.0 \n", + "PostgreSQL-24-1-8192-2 816.0 \n", + "\n", + " Latency Distribution.75th Percentile Latency (microseconds) \\\n", + "MySQL-24-1-8192-1 442.0 \n", + "MySQL-24-1-8192-2 385.0 \n", + "PostgreSQL-24-1-8192-1 139.0 \n", + "PostgreSQL-24-1-8192-2 351.0 \n", + "\n", + " Latency Distribution.Average Latency (microseconds) \n", + "MySQL-24-1-8192-1 746.0 \n", + "MySQL-24-1-8192-2 808.5 \n", + "PostgreSQL-24-1-8192-1 175.0 \n", + "PostgreSQL-24-1-8192-2 281.0 \n", + "\n", + "[4 rows x 32 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = evaluation.get_df_benchmarking()\n", + "df_plot = evaluation.benchmarking_set_datatypes(df)\n", + "df_aggregated = evaluation.benchmarking_aggregate_by_parallel_pods(df_plot)\n", + "df_aggregated" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "column = \"experiment_run\"\n", + "x = \"target\"\n", + "y = \"Throughput (requests/second)\"\n", + "evaluation.plot(df_aggregated, column=column, x=x, y=y, plot_by=\"configuration\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "column = \"experiment_run\"\n", + "x = \"target\"\n", + "y = \"Latency Distribution.95th Percentile Latency (microseconds)\"\n", + "evaluation.plot(df_aggregated, column=column, x=x, y=y, plot_by=\"configuration\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Show Infos about Connections" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "found 4 connections\n" + ] + } + ], + "source": [ + "connections = evaluation.get_connection_config()\n", + "\n", + "print(\"found\", len(connections), \"connections\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[\n", + " {\n", + " \"version\": \"CE 8.0.22\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-C\",\n", + " \"dialect\": \"MySQL\",\n", + " \"JDBC\": {\n", + " \"driver\": \"com.mysql.cj.jdbc.Driver\",\n", + " \"auth\": [\n", + " \"root\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:mysql://bexhoma-sut-mysql-24-1-8192-1674056386.perdelt.svc.cluster.local:9091/benchbase\",\n", + " \"jar\": [\n", + " \"./jars/mysql-connector-j-8.0.31.jar\",\n", + " \"./jars/slf4j-simple-1.7.21.jar\"\n", + " ]\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"MySQL-24-1-8192-1\",\n", + " \"docker\": \"MySQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 86.10324888676405,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 1081999486976,\n", + " \"CPU\": \"\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 256,\n", + " \"host\": \"5.4.0-126-generic\",\n", + " \"node\": \"cl-worker28\",\n", + " \"disk\": 508938276,\n", + " \"datadisk\": 8507004,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"4\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-mysql-24-1-8192-1674056386.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 1,\n", + " \"client\": \"1\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"mysql/mysql-server:8.0.31\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 1,\n", + " \"SF\": \"1\",\n", + " \"BENCHBASE_BENCH\": \"twitter\",\n", + " \"BENCHBASE_PROFILE\": \"mysql\",\n", + " \"BEXHOMA_DATABASE\": \"benchbase\",\n", + " \"BENCHBASE_TARGET\": 8192,\n", + " \"BENCHBASE_TERMINALS\": 24,\n", + " \"BEXHOMA_PASSWORD\": \"root\"\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"CE 8.0.22\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-C\",\n", + " \"dialect\": \"MySQL\",\n", + " \"JDBC\": {\n", + " \"driver\": \"com.mysql.cj.jdbc.Driver\",\n", + " \"auth\": [\n", + " \"root\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:mysql://bexhoma-sut-mysql-24-1-8192-1674056386.perdelt.svc.cluster.local:9091/benchbase\",\n", + " \"jar\": [\n", + " \"./jars/mysql-connector-j-8.0.31.jar\",\n", + " \"./jars/slf4j-simple-1.7.21.jar\"\n", + " ]\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"MySQL-24-1-8192-2\",\n", + " \"docker\": \"MySQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 86.10324888676405,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 1081999486976,\n", + " \"CPU\": \"\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 256,\n", + " \"host\": \"5.4.0-126-generic\",\n", + " \"node\": \"cl-worker28\",\n", + " \"disk\": 508975744,\n", + " \"datadisk\": 8517980,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"4\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-mysql-24-1-8192-1674056386.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 2,\n", + " \"client\": \"2\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"mysql/mysql-server:8.0.31\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 1,\n", + " \"SF\": \"1\",\n", + " \"BENCHBASE_BENCH\": \"twitter\",\n", + " \"BENCHBASE_PROFILE\": \"mysql\",\n", + " \"BEXHOMA_DATABASE\": \"benchbase\",\n", + " \"BENCHBASE_TARGET\": 8192,\n", + " \"BENCHBASE_TERMINALS\": 24,\n", + " \"BEXHOMA_PASSWORD\": \"root\"\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"v11.4\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-B\",\n", + " \"JDBC\": {\n", + " \"driver\": \"org.postgresql.Driver\",\n", + " \"auth\": [\n", + " \"postgres\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:postgresql://bexhoma-sut-postgresql-24-1-8192-1674056386.perdelt.svc.cluster.local:9091/postgres\",\n", + " \"jar\": \"./jars/postgresql-42.5.0.jar\"\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"PostgreSQL-24-1-8192-1\",\n", + " \"docker\": \"PostgreSQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 65.46283559501171,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 1081999486976,\n", + " \"CPU\": \"AMD EPYC 7742 64-Core Processor\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 256,\n", + " \"host\": \"5.4.0-126-generic\",\n", + " \"node\": \"cl-worker28\",\n", + " \"disk\": 508937540,\n", + " \"datadisk\": 50468,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"4\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-postgresql-24-1-8192-1674056386.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 1,\n", + " \"client\": \"1\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"postgres:15beta4\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 1,\n", + " \"SF\": \"1\",\n", + " \"BENCHBASE_BENCH\": \"twitter\",\n", + " \"BENCHBASE_PROFILE\": \"postgres\",\n", + " \"BEXHOMA_DATABASE\": \"postgres\",\n", + " \"BENCHBASE_TARGET\": 8192,\n", + " \"BENCHBASE_TERMINALS\": 24\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"v11.4\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-B\",\n", + " \"JDBC\": {\n", + " \"driver\": \"org.postgresql.Driver\",\n", + " \"auth\": [\n", + " \"postgres\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:postgresql://bexhoma-sut-postgresql-24-1-8192-1674056386.perdelt.svc.cluster.local:9091/postgres\",\n", + " \"jar\": \"./jars/postgresql-42.5.0.jar\"\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"PostgreSQL-24-1-8192-2\",\n", + " \"docker\": \"PostgreSQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 65.46283559501171,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 1081999486976,\n", + " \"CPU\": \"AMD EPYC 7742 64-Core Processor\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 256,\n", + " \"host\": \"5.4.0-126-generic\",\n", + " \"node\": \"cl-worker28\",\n", + " \"disk\": 508973848,\n", + " \"datadisk\": 68048,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"4\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-postgresql-24-1-8192-1674056386.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-24-1-8192-1674056386(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 2,\n", + " \"client\": \"2\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"postgres:15beta4\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 1,\n", + " \"SF\": \"1\",\n", + " \"BENCHBASE_BENCH\": \"twitter\",\n", + " \"BENCHBASE_PROFILE\": \"postgres\",\n", + " \"BEXHOMA_DATABASE\": \"postgres\",\n", + " \"BENCHBASE_TARGET\": 8192,\n", + " \"BENCHBASE_TERMINALS\": 24\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " }\n", + "]\n" + ] + } + ], + "source": [ + "import json\n", + "pretty_connections = json.dumps(connections, indent=2)\n", + "\n", + "print(pretty_connections)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading time per number of loading threads" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MySQL-24-1-8192-1 86.10324888676405 [s] for 1 threads on cl-worker28\n", + "MySQL-24-1-8192-2 86.10324888676405 [s] for 1 threads on cl-worker28\n", + "PostgreSQL-24-1-8192-1 65.46283559501171 [s] for 1 threads on cl-worker28\n", + "PostgreSQL-24-1-8192-2 65.46283559501171 [s] for 1 threads on cl-worker28\n" + ] + } + ], + "source": [ + "for c in connections:\n", + " print(c['name'], \n", + " c['timeLoad'], \n", + " '[s] for', \n", + " c['parameter']['connection_parameter']['loading_parameters']['PARALLEL'], \n", + " 'threads on',\n", + " c['hostsystem']['node'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Get monitoring metrics\n", + "\n", + "### Loading" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation.transform_monitoring_results()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['total_cpu_memory',\n", + " 'total_cpu_memory_cached',\n", + " 'total_cpu_util',\n", + " 'total_cpu_throttled',\n", + " 'total_cpu_util_others',\n", + " 'total_cpu_util_s',\n", + " 'total_cpu_util_user_s',\n", + " 'total_cpu_util_sys_s',\n", + " 'total_cpu_throttled_s',\n", + " 'total_cpu_util_others_s',\n", + " 'total_network_rx',\n", + " 'total_network_tx',\n", + " 'total_fs_read',\n", + " 'total_fs_write',\n", + " 'total_gpu_util',\n", + " 'total_gpu_power',\n", + " 'total_gpu_memory']" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation.get_monitoring_metrics()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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MySQL-24-1-8192-1398.523438398.523438398.5234384666.8828124666.8828124666.8828124666.8828124666.8828124666.8828124666.882812...19487.85546919487.85546919487.85546919487.85546919487.85546919487.85546919522.52734419522.52734419522.52734419522.527344
MySQL-24-1-8192-2398.523438398.523438398.5234384666.8828124666.8828124666.8828124666.8828124666.8828124666.8828124666.882812...19487.85546919487.85546919487.85546919487.85546919487.85546919487.85546919522.52734419522.52734419522.52734419522.527344
PostgreSQL-24-1-8192-11119.6367191119.6367191119.6367191120.6992191120.6992191120.6992191120.6992191120.6992191120.6992191120.699219...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
PostgreSQL-24-1-8192-21119.6367191119.6367191119.6367191120.6992191120.6992191120.6992191120.6992191120.6992191120.6992191120.699219...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
\n", + "

4 rows × 82 columns

\n", + "
" + ], + "text/plain": [ + " 0 1 2 3 \\\n", + "MySQL-24-1-8192-1 398.523438 398.523438 398.523438 4666.882812 \n", + "MySQL-24-1-8192-2 398.523438 398.523438 398.523438 4666.882812 \n", + "PostgreSQL-24-1-8192-1 1119.636719 1119.636719 1119.636719 1120.699219 \n", + "PostgreSQL-24-1-8192-2 1119.636719 1119.636719 1119.636719 1120.699219 \n", + "\n", + " 4 5 6 7 \\\n", + "MySQL-24-1-8192-1 4666.882812 4666.882812 4666.882812 4666.882812 \n", + "MySQL-24-1-8192-2 4666.882812 4666.882812 4666.882812 4666.882812 \n", + "PostgreSQL-24-1-8192-1 1120.699219 1120.699219 1120.699219 1120.699219 \n", + "PostgreSQL-24-1-8192-2 1120.699219 1120.699219 1120.699219 1120.699219 \n", + "\n", + " 8 9 ... 72 \\\n", + "MySQL-24-1-8192-1 4666.882812 4666.882812 ... 19487.855469 \n", + "MySQL-24-1-8192-2 4666.882812 4666.882812 ... 19487.855469 \n", + "PostgreSQL-24-1-8192-1 1120.699219 1120.699219 ... NaN \n", + "PostgreSQL-24-1-8192-2 1120.699219 1120.699219 ... NaN \n", + "\n", + " 73 74 75 \\\n", + "MySQL-24-1-8192-1 19487.855469 19487.855469 19487.855469 \n", + "MySQL-24-1-8192-2 19487.855469 19487.855469 19487.855469 \n", + "PostgreSQL-24-1-8192-1 NaN NaN NaN \n", + "PostgreSQL-24-1-8192-2 NaN NaN NaN \n", + "\n", + " 76 77 78 \\\n", + "MySQL-24-1-8192-1 19487.855469 19487.855469 19522.527344 \n", + "MySQL-24-1-8192-2 19487.855469 19487.855469 19522.527344 \n", + "PostgreSQL-24-1-8192-1 NaN NaN NaN \n", + "PostgreSQL-24-1-8192-2 NaN NaN NaN \n", + "\n", + " 79 80 81 \n", + "MySQL-24-1-8192-1 19522.527344 19522.527344 19522.527344 \n", + "MySQL-24-1-8192-2 19522.527344 19522.527344 19522.527344 \n", + "PostgreSQL-24-1-8192-1 NaN NaN NaN \n", + "PostgreSQL-24-1-8192-2 NaN NaN NaN \n", + "\n", + "[4 rows x 82 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = evaluation.get_monitoring_metric('total_cpu_memory')\n", + "\n", + "df.T" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "#fig, ax = plt.subplots()\n", + "ax = df.plot(kind='line')\n", + "#ax.set_ylim(0,df[y].max())\n", + "plt.legend(loc='best')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "list_metrics = evaluation.get_monitoring_metrics()\n", + "row=0\n", + "col=0\n", + "rows = (len(list_metrics)+1)//2\n", + "\n", + "fig, axes = plt.subplots(nrows=rows, ncols=2, sharex=True, squeeze=False, figsize=(12,8*rows))\n", + "for metric in list_metrics:\n", + " df = evaluation.get_monitoring_metric(metric)\n", + " ax = df.plot(ax=axes[row,col], kind='line', title=metric, layout=(rows,2))\n", + " col = col + 1\n", + " if col > 1:\n", + " row = row + 1\n", + " col = 0\n", + "plt.legend(loc='best')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Benchmarking" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation.transform_monitoring_results(component='stream')" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "list_metrics = evaluation.get_monitoring_metrics()\n", + "row=0\n", + "col=0\n", + "rows = (len(list_metrics)+1)//2\n", + "\n", + "fig, axes = plt.subplots(nrows=rows, ncols=2, sharex=True, squeeze=False, figsize=(12,8*rows))\n", + "for metric in list_metrics:\n", + " df = evaluation.get_monitoring_metric(metric, component='stream')\n", + " #if df.sum().sum() > 0:\n", + " ax = df.plot(ax=axes[row,col], kind='line', title=metric, layout=(rows,2))\n", + " col = col + 1\n", + " if col > 1:\n", + " row = row + 1\n", + " col = 0\n", + "plt.legend(loc='best')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.html b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.html new file mode 100644 index 00000000..3b5de316 --- /dev/null +++ b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.html @@ -0,0 +1,10447 @@ + + + + + +Evaluate-HammerDB-result + + + + + + + + + + + + +
+ + + + + + + + + + + + + + + + + + + + +
+ + diff --git a/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.ipynb b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.ipynb new file mode 100644 index 00000000..1be18214 --- /dev/null +++ b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-HammerDB.ipynb @@ -0,0 +1,3002 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Evaluate HammerDB Result\n", + "\n", + "About the benchmark [1]:\n", + "> The TPC-C specification on which TPROC-C is based implements a computer system to fulfil orders from customers to supply products from a company. The company sells 100,000 items and keeps its stock in warehouses. Each warehouse has 10 sales districts and each district serves 3000 customers. The customers call the company whose operators take the order, each order containing a number of items. Orders are usually satisfied from the local warehouse however a small number of items are not in stock at a particular point in time and are supplied by an alternative warehouse. It is important to note that the size of the company is not fixed and can add Warehouses and sales districts as the company grows. For this reason your test schema can be as small or large as you wish with a larger schema requiring a more powerful computer system to process the increased level of transactions. The TPROC-C schema is shown below, in particular note how the number of rows in all of the tables apart from the ITEM table which is fixed is dependent upon the number of warehouses you choose to create your schema.\n", + "\n", + "\"drawing\"\n", + "\n", + "About the metrics [2]:\n", + "> HammerDB workloads produce 2 statistics to compare systems called **TPM** and NOPM respectively. NOPM value is based on a metric captured from within the test schema itself. As such **NOPM (New Orders per minute)** as a performance metric independent of any particular database implementation is the recommended primary metric to use.\n", + "\n", + "References\n", + "1. https://www.hammerdb.com/docs/ch03s05.html\n", + "1. https://www.hammerdb.com/docs/ch03s04.html\n", + "1. https://www.hammerdb.com/docs/ch03.html\n", + "\n", + "## Import Packages" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import os\n", + "import re\n", + "import matplotlib.pyplot as plt\n", + "import pickle\n", + "# Some nice output\n", + "pd.set_option(\"display.max_rows\", None)\n", + "pd.set_option('display.max_colwidth', None)\n", + "from IPython.display import display, Markdown\n", + "%matplotlib inline\n", + "\n", + "import evaluator" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prepare Result\n", + "\n", + "### Pick Result" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "code = \"1674056379\"\n", + "path = \"./\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Start Evaluation" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation = evaluator.tpcc(code=code, path=path)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Transform all Benchmarking Log Files to DataFrames\n", + "\n", + "We also pick the first log file to be an example for later" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-7wbg7.log\n", + ".//1674056379/bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log log is incomplete\n", + "Error in bexhoma-benchmarker-mariadb-4-1674056379-1-2-p5qnl.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2hh9t.log\n", + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log log is incomplete\n", + "Error in bexhoma-benchmarker-postgresql-4-1674056379-1-2-2zbh6.log\n" + ] + } + ], + "source": [ + "filename_example = \"\"\n", + "\n", + "directory = os.fsencode(path+\"/\"+code)\n", + "for file in os.listdir(directory):\n", + " filename = os.fsdecode(file)\n", + " if filename.startswith(\"bexhoma-benchmarker\") and filename.endswith(\".log\"):\n", + " #print(\"filename:\", filename)\n", + " pod_name = filename[filename.rindex(\"-\")+1:-len(\".log\")]\n", + " #print(\"pod_name:\", pod_name)\n", + " jobname = filename[len(\"bexhoma-benchmarker-\"):-len(\"-\"+pod_name+\".log\")]\n", + " #print(\"jobname:\", jobname)\n", + " evaluation.end_benchmarking(jobname)\n", + " filename_example = filename" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Show a DataFrame for single Pod as Example" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ".//1674056379/bexhoma-benchmarker-postgresql-4-1674056379-1-2-vcbdh.log.df.pickle\n" + ] + }, + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countiterationsdurationrampupsfrunerrorsvusers_loadingvusersNOPMTPMdbms
PostgreSQL-4-2
0PostgreSQL-4-2PostgreSQL-412vcbdh2100000005240041676715522PostgreSQL
\n", + "
" + ], + "text/plain": [ + " connection configuration experiment_run client pod \\\n", + "PostgreSQL-4-2 \n", + "0 PostgreSQL-4-2 PostgreSQL-4 1 2 vcbdh \n", + "\n", + " pod_count iterations duration rampup sf run errors \\\n", + "PostgreSQL-4-2 \n", + "0 2 10000000 5 2 4 0 0 \n", + "\n", + " vusers_loading vusers NOPM TPM dbms \n", + "PostgreSQL-4-2 \n", + "0 4 1 6767 15522 PostgreSQL " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "filename = path+\"/\"+code+\"/\"+filename_example+\".df.pickle\"\n", + "print(filename)\n", + "df = pd.read_pickle(filename)\n", + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Transform all DataFrames into single Result DataFrame" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation.evaluate_results()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Get Benchmarking Result" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countiterationsdurationrampupsfrunerrorsvusers_loadingvusersNOPMTPMdbms
connection_pod
MariaDB-4-1-1MariaDB-4-1MariaDB-411fcldv1100000005240041977622695MariaDB
MariaDB-4-2-1MariaDB-4-2MariaDB-412hzc7621000000052400411198127661MariaDB
MariaDB-4-2-2MariaDB-4-2MariaDB-412pdq8h21000000052400411121825868MariaDB
MySQL-4-1-1MySQL-4-1MySQL-411lqk6b1100000005240041214483MySQL
MySQL-4-2-1MySQL-4-2MySQL-412f49vg210000000524004156118MySQL
MySQL-4-2-2MySQL-4-2MySQL-412z52zw210000000524004156118MySQL
PostgreSQL-4-1-1PostgreSQL-4-1PostgreSQL-4117t78z11000000052400411037323710PostgreSQL
PostgreSQL-4-2-1PostgreSQL-4-2PostgreSQL-412j7hhq2100000005240041683515697PostgreSQL
PostgreSQL-4-2-2PostgreSQL-4-2PostgreSQL-412vcbdh2100000005240041676715522PostgreSQL
\n", + "
" + ], + "text/plain": [ + " connection configuration experiment_run client pod \\\n", + "connection_pod \n", + "MariaDB-4-1-1 MariaDB-4-1 MariaDB-4 1 1 fcldv \n", + "MariaDB-4-2-1 MariaDB-4-2 MariaDB-4 1 2 hzc76 \n", + "MariaDB-4-2-2 MariaDB-4-2 MariaDB-4 1 2 pdq8h \n", + "MySQL-4-1-1 MySQL-4-1 MySQL-4 1 1 lqk6b \n", + "MySQL-4-2-1 MySQL-4-2 MySQL-4 1 2 f49vg \n", + "MySQL-4-2-2 MySQL-4-2 MySQL-4 1 2 z52zw \n", + "PostgreSQL-4-1-1 PostgreSQL-4-1 PostgreSQL-4 1 1 7t78z \n", + "PostgreSQL-4-2-1 PostgreSQL-4-2 PostgreSQL-4 1 2 j7hhq \n", + "PostgreSQL-4-2-2 PostgreSQL-4-2 PostgreSQL-4 1 2 vcbdh \n", + "\n", + " pod_count iterations duration rampup sf run errors \\\n", + "connection_pod \n", + "MariaDB-4-1-1 1 10000000 5 2 4 0 0 \n", + "MariaDB-4-2-1 2 10000000 5 2 4 0 0 \n", + "MariaDB-4-2-2 2 10000000 5 2 4 0 0 \n", + "MySQL-4-1-1 1 10000000 5 2 4 0 0 \n", + "MySQL-4-2-1 2 10000000 5 2 4 0 0 \n", + "MySQL-4-2-2 2 10000000 5 2 4 0 0 \n", + "PostgreSQL-4-1-1 1 10000000 5 2 4 0 0 \n", + "PostgreSQL-4-2-1 2 10000000 5 2 4 0 0 \n", + "PostgreSQL-4-2-2 2 10000000 5 2 4 0 0 \n", + "\n", + " vusers_loading vusers NOPM TPM dbms \n", + "connection_pod \n", + "MariaDB-4-1-1 4 1 9776 22695 MariaDB \n", + "MariaDB-4-2-1 4 1 11981 27661 MariaDB \n", + "MariaDB-4-2-2 4 1 11218 25868 MariaDB \n", + "MySQL-4-1-1 4 1 214 483 MySQL \n", + "MySQL-4-2-1 4 1 56 118 MySQL \n", + "MySQL-4-2-2 4 1 56 118 MySQL \n", + "PostgreSQL-4-1-1 4 1 10373 23710 PostgreSQL \n", + "PostgreSQL-4-2-1 4 1 6835 15697 PostgreSQL \n", + "PostgreSQL-4-2-2 4 1 6767 15522 PostgreSQL " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = evaluation.get_df_benchmarking()\n", + "\n", + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Reconstruct workflow out of result" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'MariaDB-4': [[1, 2]], 'MySQL-4': [[1, 2]], 'PostgreSQL-4': [[1, 2]]}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation.reconstruct_workflow(df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot Results\n", + "\n", + "#### Set data types for plotting" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countiterationsdurationrampupsfrunerrorsvusers_loadingvusersNOPMTPMdbms
connection_pod
MariaDB-4-1-1MariaDB-4-1MariaDB-411fcldv1100000005240041977622695MariaDB
MariaDB-4-2-1MariaDB-4-2MariaDB-412hzc7621000000052400411198127661MariaDB
MariaDB-4-2-2MariaDB-4-2MariaDB-412pdq8h21000000052400411121825868MariaDB
MySQL-4-1-1MySQL-4-1MySQL-411lqk6b1100000005240041214483MySQL
MySQL-4-2-1MySQL-4-2MySQL-412f49vg210000000524004156118MySQL
MySQL-4-2-2MySQL-4-2MySQL-412z52zw210000000524004156118MySQL
PostgreSQL-4-1-1PostgreSQL-4-1PostgreSQL-4117t78z11000000052400411037323710PostgreSQL
PostgreSQL-4-2-1PostgreSQL-4-2PostgreSQL-412j7hhq2100000005240041683515697PostgreSQL
PostgreSQL-4-2-2PostgreSQL-4-2PostgreSQL-412vcbdh2100000005240041676715522PostgreSQL
\n", + "
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connectionconfigurationexperiment_runclientpodpod_countiterationsdurationrampupsfrunerrorsvusers_loadingvusersNOPMTPMdbms
connection_pod
MariaDB-4-1-1MariaDB-4-1MariaDB-411fcldv1100000005240041977622695MariaDB
MariaDB-4-2-1MariaDB-4-2MariaDB-412hzc7621000000052400411198127661MariaDB
MariaDB-4-2-2MariaDB-4-2MariaDB-412pdq8h21000000052400411121825868MariaDB
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" + ], + "text/plain": [ + " connection configuration experiment_run client pod \\\n", + "connection_pod \n", + "MariaDB-4-1-1 MariaDB-4-1 MariaDB-4 1 1 fcldv \n", + "MariaDB-4-2-1 MariaDB-4-2 MariaDB-4 1 2 hzc76 \n", + "MariaDB-4-2-2 MariaDB-4-2 MariaDB-4 1 2 pdq8h \n", + "\n", + " pod_count iterations duration rampup sf run errors \\\n", + "connection_pod \n", + "MariaDB-4-1-1 1 10000000 5 2 4 0 0 \n", + "MariaDB-4-2-1 2 10000000 5 2 4 0 0 \n", + "MariaDB-4-2-2 2 10000000 5 2 4 0 0 \n", + "\n", + " vusers_loading vusers NOPM TPM dbms \n", + "connection_pod \n", + "MariaDB-4-1-1 4 1 9776 22695 MariaDB \n", + "MariaDB-4-2-1 4 1 11981 27661 MariaDB \n", + "MariaDB-4-2-2 4 1 11218 25868 MariaDB " + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[df['configuration']=='MariaDB-4']" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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connectionconfigurationexperiment_runclientpodpod_countiterationsdurationrampupsfrunerrorsvusers_loadingvusersNOPMTPMdbms
connection_pod
MariaDB-4-1-1MariaDB-4-1MariaDB-411fcldv1100000005240041977622695MariaDB
MariaDB-4-2-1MariaDB-4-2MariaDB-412hzc7621000000052400411198127661MariaDB
MariaDB-4-2-2MariaDB-4-2MariaDB-412pdq8h21000000052400411121825868MariaDB
MySQL-4-1-1MySQL-4-1MySQL-411lqk6b1100000005240041214483MySQL
MySQL-4-2-1MySQL-4-2MySQL-412f49vg210000000524004156118MySQL
MySQL-4-2-2MySQL-4-2MySQL-412z52zw210000000524004156118MySQL
PostgreSQL-4-1-1PostgreSQL-4-1PostgreSQL-4117t78z11000000052400411037323710PostgreSQL
PostgreSQL-4-2-1PostgreSQL-4-2PostgreSQL-412j7hhq2100000005240041683515697PostgreSQL
PostgreSQL-4-2-2PostgreSQL-4-2PostgreSQL-412vcbdh2100000005240041676715522PostgreSQL
\n", + "
" + ], + "text/plain": [ + " connection configuration experiment_run client pod \\\n", + "connection_pod \n", + "MariaDB-4-1-1 MariaDB-4-1 MariaDB-4 1 1 fcldv \n", + "MariaDB-4-2-1 MariaDB-4-2 MariaDB-4 1 2 hzc76 \n", + "MariaDB-4-2-2 MariaDB-4-2 MariaDB-4 1 2 pdq8h \n", + "MySQL-4-1-1 MySQL-4-1 MySQL-4 1 1 lqk6b \n", + "MySQL-4-2-1 MySQL-4-2 MySQL-4 1 2 f49vg \n", + "MySQL-4-2-2 MySQL-4-2 MySQL-4 1 2 z52zw \n", + "PostgreSQL-4-1-1 PostgreSQL-4-1 PostgreSQL-4 1 1 7t78z \n", + "PostgreSQL-4-2-1 PostgreSQL-4-2 PostgreSQL-4 1 2 j7hhq \n", + "PostgreSQL-4-2-2 PostgreSQL-4-2 PostgreSQL-4 1 2 vcbdh \n", + "\n", + " pod_count iterations duration rampup sf run errors \\\n", + "connection_pod \n", + "MariaDB-4-1-1 1 10000000 5 2 4 0 0 \n", + "MariaDB-4-2-1 2 10000000 5 2 4 0 0 \n", + "MariaDB-4-2-2 2 10000000 5 2 4 0 0 \n", + "MySQL-4-1-1 1 10000000 5 2 4 0 0 \n", + "MySQL-4-2-1 2 10000000 5 2 4 0 0 \n", + "MySQL-4-2-2 2 10000000 5 2 4 0 0 \n", + "PostgreSQL-4-1-1 1 10000000 5 2 4 0 0 \n", + "PostgreSQL-4-2-1 2 10000000 5 2 4 0 0 \n", + "PostgreSQL-4-2-2 2 10000000 5 2 4 0 0 \n", + "\n", + " vusers_loading vusers NOPM TPM dbms \n", + "connection_pod \n", + "MariaDB-4-1-1 4 1 9776 22695 MariaDB \n", + "MariaDB-4-2-1 4 1 11981 27661 MariaDB \n", + "MariaDB-4-2-2 4 1 11218 25868 MariaDB \n", + "MySQL-4-1-1 4 1 214 483 MySQL \n", + "MySQL-4-2-1 4 1 56 118 MySQL \n", + "MySQL-4-2-2 4 1 56 118 MySQL \n", + "PostgreSQL-4-1-1 4 1 10373 23710 PostgreSQL \n", + "PostgreSQL-4-2-1 4 1 6835 15697 PostgreSQL \n", + "PostgreSQL-4-2-2 4 1 6767 15522 PostgreSQL " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#df_plot = df_plot[df_plot[\"experiment_run\"]==\"1\"]\n", + "#df_plot = df_plot[df_plot[\"client\"] == \"1\"]\n", + "df_plot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + 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connectionconfigurationexperiment_runclientpodpod_countiterationsdurationsfrunerrorsvusers_loadingvusersNOPMTPMdbms
MariaDB-4-1MariaDB-4-1MariaDB-411fcldv110000000540041977622695MariaDB
MariaDB-4-2MariaDB-4-2MariaDB-412hzc76pdq8h2100000005400421198127661MariaDB
MySQL-4-1MySQL-4-1MySQL-411lqk6b110000000540041214483MySQL
MySQL-4-2MySQL-4-2MySQL-412f49vgz52zw21000000054004256118MySQL
PostgreSQL-4-1PostgreSQL-4-1PostgreSQL-4117t78z1100000005400411037323710PostgreSQL
PostgreSQL-4-2PostgreSQL-4-2PostgreSQL-412j7hhqvcbdh210000000540042683515697PostgreSQL
\n", + "
" + ], + "text/plain": [ + " connection configuration experiment_run client \\\n", + "MariaDB-4-1 MariaDB-4-1 MariaDB-4 1 1 \n", + "MariaDB-4-2 MariaDB-4-2 MariaDB-4 1 2 \n", + "MySQL-4-1 MySQL-4-1 MySQL-4 1 1 \n", + "MySQL-4-2 MySQL-4-2 MySQL-4 1 2 \n", + "PostgreSQL-4-1 PostgreSQL-4-1 PostgreSQL-4 1 1 \n", + "PostgreSQL-4-2 PostgreSQL-4-2 PostgreSQL-4 1 2 \n", + "\n", + " pod pod_count iterations duration sf run errors \\\n", + "MariaDB-4-1 fcldv 1 10000000 5 4 0 0 \n", + "MariaDB-4-2 hzc76pdq8h 2 10000000 5 4 0 0 \n", + "MySQL-4-1 lqk6b 1 10000000 5 4 0 0 \n", + "MySQL-4-2 f49vgz52zw 2 10000000 5 4 0 0 \n", + "PostgreSQL-4-1 7t78z 1 10000000 5 4 0 0 \n", + "PostgreSQL-4-2 j7hhqvcbdh 2 10000000 5 4 0 0 \n", + "\n", + " vusers_loading vusers NOPM TPM dbms \n", + "MariaDB-4-1 4 1 9776 22695 MariaDB \n", + "MariaDB-4-2 4 2 11981 27661 MariaDB \n", + "MySQL-4-1 4 1 214 483 MySQL \n", + "MySQL-4-2 4 2 56 118 MySQL \n", + "PostgreSQL-4-1 4 1 10373 23710 PostgreSQL \n", + "PostgreSQL-4-2 4 2 6835 15697 PostgreSQL " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = evaluation.get_df_benchmarking()\n", + "df_plot = evaluation.benchmarking_set_datatypes(df)\n", + "df_aggregated = evaluation.benchmarking_aggregate_by_parallel_pods(df_plot)\n", + "df_aggregated" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "column = \"experiment_run\"\n", + "x = \"vusers\"\n", + "y = \"NOPM\"\n", + "evaluation.plot(df_aggregated, column=column, x=x, y=y, plot_by=\"configuration\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Show Infos about Connections" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "found 6 connections\n" + ] + } + ], + "source": [ + "import ast\n", + "\n", + "with open(path+code+\"/connections.config\",'r') as inf:\n", + " connections = ast.literal_eval(inf.read())\n", + "\n", + "print(\"found\", len(connections), \"connections\")" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[\n", + " {\n", + " \"version\": \"v11.4\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-B\",\n", + " \"JDBC\": {\n", + " \"driver\": \"org.postgresql.Driver\",\n", + " \"auth\": [\n", + " \"postgres\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:postgresql://bexhoma-sut-postgresql-4-1674056379.perdelt.svc.cluster.local:9091/postgres\",\n", + " \"jar\": \"./jars/postgresql-42.5.0.jar\"\n", + " },\n", + " \"dialect\": \"MonetDB\",\n", + " \"active\": true,\n", + " \"name\": \"PostgreSQL-4-1\",\n", + " \"docker\": \"PostgreSQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 67.62372010201216,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 541037633536,\n", + " \"CPU\": \"AMD Opteron(tm) Processor 6378\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 64,\n", + " \"host\": \"5.4.0-81-generic\",\n", + " \"node\": \"cl-worker11\",\n", + " \"disk\": 1175827044,\n", + " \"datadisk\": 903336,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"8\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-postgresql-4-1674056379.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 1,\n", + " \"client\": \"1\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"postgres:15beta4\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 4,\n", + " \"SF\": \"4\",\n", + " \"HAMMERDB_DURATION\": 5,\n", + " \"HAMMERDB_TYPE\": \"postgresql\",\n", + " \"HAMMERDB_VUSERS\": 4\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"v10.4.6\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-A\",\n", + " \"dialect\": \"MonetDB\",\n", + " \"JDBC\": {\n", + " \"driver\": \"org.mariadb.jdbc.Driver\",\n", + " \"auth\": [\n", + " \"root\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:mariadb://bexhoma-sut-mariadb-4-1674056379.perdelt.svc.cluster.local:9091/tpcc\",\n", + " \"jar\": \"./jars/mariadb-java-client-3.1.0.jar\"\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"MariaDB-4-1\",\n", + " \"docker\": \"MariaDB\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 114.58742006868124,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 541037633536,\n", + " \"CPU\": \"AMD Opteron(tm) Processor 6378\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 64,\n", + " \"host\": \"5.4.0-81-generic\",\n", + " \"node\": \"cl-worker11\",\n", + " \"disk\": 1176198036,\n", + " \"datadisk\": 4744180,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"8\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-mariadb-4-1674056379.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 1,\n", + " \"client\": \"1\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"mariadb:10.9.4\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 4,\n", + " \"SF\": \"4\",\n", + " \"HAMMERDB_DURATION\": 5,\n", + " \"HAMMERDB_TYPE\": \"mariadb\",\n", + " \"HAMMERDB_VUSERS\": 4\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"CE 8.0.22\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-C\",\n", + " \"dialect\": \"MonetDB\",\n", + " \"JDBC\": {\n", + " \"driver\": \"com.mysql.cj.jdbc.Driver\",\n", + " \"auth\": [\n", + " \"root\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:mysql://bexhoma-sut-mysql-4-1674056379.perdelt.svc.cluster.local:9091/tpcc\",\n", + " \"jar\": [\n", + " \"./jars/mysql-connector-j-8.0.31.jar\",\n", + " \"./jars/slf4j-simple-1.7.21.jar\"\n", + " ]\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"MySQL-4-1\",\n", + " \"docker\": \"MySQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 180.62911394238472,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 541037633536,\n", + " \"CPU\": \"\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 64,\n", + " \"host\": \"5.4.0-81-generic\",\n", + " \"node\": \"cl-worker11\",\n", + " \"disk\": 1176278372,\n", + " \"datadisk\": 9208512,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"8\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-mysql-4-1674056379.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 1,\n", + " \"client\": \"1\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"mysql/mysql-server:8.0.31\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 4,\n", + " \"SF\": \"4\",\n", + " \"HAMMERDB_DURATION\": 5,\n", + " \"HAMMERDB_TYPE\": \"mysql\",\n", + " \"USER\": \"root\",\n", + " \"PASSWORD\": \"root\",\n", + " \"HAMMERDB_VUSERS\": 4\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"v11.4\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-B\",\n", + " \"JDBC\": {\n", + " \"driver\": \"org.postgresql.Driver\",\n", + " \"auth\": [\n", + " \"postgres\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:postgresql://bexhoma-sut-postgresql-4-1674056379.perdelt.svc.cluster.local:9091/postgres\",\n", + " \"jar\": \"./jars/postgresql-42.5.0.jar\"\n", + " },\n", + " \"dialect\": \"MonetDB\",\n", + " \"active\": true,\n", + " \"name\": \"PostgreSQL-4-2\",\n", + " \"docker\": \"PostgreSQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 67.62372010201216,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 541037633536,\n", + " \"CPU\": \"AMD Opteron(tm) Processor 6378\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 64,\n", + " \"host\": \"5.4.0-81-generic\",\n", + " \"node\": \"cl-worker11\",\n", + " \"disk\": 1177024544,\n", + " \"datadisk\": 1508712,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"8\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-postgresql-4-1674056379.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)postgresql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 2,\n", + " \"client\": \"2\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"postgres:15beta4\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 4,\n", + " \"SF\": \"4\",\n", + " \"HAMMERDB_DURATION\": 5,\n", + " \"HAMMERDB_TYPE\": \"postgresql\",\n", + " \"HAMMERDB_VUSERS\": 4\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"v10.4.6\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-A\",\n", + " \"dialect\": \"MonetDB\",\n", + " \"JDBC\": {\n", + " \"driver\": \"org.mariadb.jdbc.Driver\",\n", + " \"auth\": [\n", + " \"root\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:mariadb://bexhoma-sut-mariadb-4-1674056379.perdelt.svc.cluster.local:9091/tpcc\",\n", + " \"jar\": \"./jars/mariadb-java-client-3.1.0.jar\"\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"MariaDB-4-2\",\n", + " \"docker\": \"MariaDB\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 114.58742006868124,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 541037633536,\n", + " \"CPU\": \"AMD Opteron(tm) Processor 6378\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 64,\n", + " \"host\": \"5.4.0-81-generic\",\n", + " \"node\": \"cl-worker11\",\n", + " \"disk\": 1177074904,\n", + " \"datadisk\": 4838388,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"8\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-mariadb-4-1674056379.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mariadb-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 2,\n", + " \"client\": \"2\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"mariadb:10.9.4\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 4,\n", + " \"SF\": \"4\",\n", + " \"HAMMERDB_DURATION\": 5,\n", + " \"HAMMERDB_TYPE\": \"mariadb\",\n", + " \"HAMMERDB_VUSERS\": 4\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " },\n", + " {\n", + " \"version\": \"CE 8.0.22\",\n", + " \"alias\": \"DBMS D\",\n", + " \"docker_alias\": \"GP-C\",\n", + " \"dialect\": \"MonetDB\",\n", + " \"JDBC\": {\n", + " \"driver\": \"com.mysql.cj.jdbc.Driver\",\n", + " \"auth\": [\n", + " \"root\",\n", + " \"\"\n", + " ],\n", + " \"url\": \"jdbc:mysql://bexhoma-sut-mysql-4-1674056379.perdelt.svc.cluster.local:9091/tpcc\",\n", + " \"jar\": [\n", + " \"./jars/mysql-connector-j-8.0.31.jar\",\n", + " \"./jars/slf4j-simple-1.7.21.jar\"\n", + " ]\n", + " },\n", + " \"active\": true,\n", + " \"name\": \"MySQL-4-2\",\n", + " \"docker\": \"MySQL\",\n", + " \"script\": \"Schema\",\n", + " \"info\": [],\n", + " \"timeLoad\": 180.62911394238472,\n", + " \"priceperhourdollar\": 0.0,\n", + " \"hostsystem\": {\n", + " \"RAM\": 541037633536,\n", + " \"CPU\": \"\",\n", + " \"GPU\": \"\",\n", + " \"GPUIDs\": [],\n", + " \"Cores\": 64,\n", + " \"host\": \"5.4.0-81-generic\",\n", + " \"node\": \"cl-worker11\",\n", + " \"disk\": 1177077900,\n", + " \"datadisk\": 9243300,\n", + " \"cuda\": \"\",\n", + " \"requests_cpu\": \"8\",\n", + " \"requests_memory\": \"16Gi\",\n", + " \"limits_cpu\": 0,\n", + " \"limits_memory\": 0\n", + " },\n", + " \"worker\": [],\n", + " \"connectionmanagement\": {\n", + " \"numProcesses\": 1,\n", + " \"runsPerConnection\": 0,\n", + " \"timeout\": 180,\n", + " \"singleConnection\": true\n", + " },\n", + " \"monitoring\": {\n", + " \"prometheus_url\": \"http://bexhoma-monitoring-mysql-4-1674056379.perdelt.svc.cluster.local:9090/api/v1/\",\n", + " \"metrics\": {\n", + " \"total_cpu_memory\": {\n", + " \"query\": \"(sum(max(container_memory_working_set_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory [MiB]\"\n", + " },\n", + " \"total_cpu_memory_cached\": {\n", + " \"query\": \"(sum(max(container_memory_usage_bytes{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}) by (instance)))/1024/1024\",\n", + " \"title\": \"CPU Memory Cached [MiB]\"\n", + " },\n", + " \"total_cpu_util\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Util [%]\"\n", + " },\n", + " \"total_cpu_throttled\": {\n", + " \"query\": \"sum(irate(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"}[1m]))\",\n", + " \"title\": \"CPU Throttle [%]\"\n", + " },\n", + " \"total_cpu_util_others\": {\n", + " \"query\": \"sum(irate(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"}[1m]))\",\n", + " \"title\": \"CPU Util Others [%]\"\n", + " },\n", + " \"total_cpu_util_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util [s]\"\n", + " },\n", + " \"total_cpu_util_user_s\": {\n", + " \"query\": \"sum(container_cpu_user_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util User [s]\"\n", + " },\n", + " \"total_cpu_util_sys_s\": {\n", + " \"query\": \"sum(container_cpu_system_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Util Sys [s]\"\n", + " },\n", + " \"total_cpu_throttled_s\": {\n", + " \"query\": \"sum(container_cpu_cfs_throttled_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})\",\n", + " \"title\": \"CPU Throttle [s]\"\n", + " },\n", + " \"total_cpu_util_others_s\": {\n", + " \"query\": \"sum(container_cpu_usage_seconds_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name!=\\\"dbms\\\",id!=\\\"/\\\"})\",\n", + " \"title\": \"CPU Util Others [s]\"\n", + " },\n", + " \"total_network_rx\": {\n", + " \"query\": \"sum(container_network_receive_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Rx [MiB]\"\n", + " },\n", + " \"total_network_tx\": {\n", + " \"query\": \"sum(container_network_transmit_bytes_total{container_label_app=\\\"bexhoma\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\"})/1024/1024\",\n", + " \"title\": \"Net Tx [MiB]\"\n", + " },\n", + " \"total_fs_read\": {\n", + " \"query\": \"sum(container_fs_reads_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Read [MiB]\"\n", + " },\n", + " \"total_fs_write\": {\n", + " \"query\": \"sum(container_fs_writes_bytes_total{container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_pod_name=~\\\"(.*)mysql-4-1674056379(.*)\\\", container_label_io_kubernetes_container_name=\\\"dbms\\\"})/1024/1024\",\n", + " \"title\": \"FS Write [MiB]\"\n", + " },\n", + " \"total_gpu_util\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_GPU_UTIL{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Util [%]\"\n", + " },\n", + " \"total_gpu_power\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_POWER_USAGE{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Power Usage [W]\"\n", + " },\n", + " \"total_gpu_memory\": {\n", + " \"query\": \"sum(DCGM_FI_DEV_FB_USED{UUID=~\\\"\\\"})\",\n", + " \"title\": \"GPU Memory [MiB]\"\n", + " }\n", + " }\n", + " },\n", + " \"parameter\": {\n", + " \"parallelism\": 2,\n", + " \"client\": \"2\",\n", + " \"numExperiment\": \"1\",\n", + " \"dockerimage\": \"mysql/mysql-server:8.0.31\",\n", + " \"connection_parameter\": {\n", + " \"loading_parameters\": {\n", + " \"PARALLEL\": 4,\n", + " \"SF\": \"4\",\n", + " \"HAMMERDB_DURATION\": 5,\n", + " \"HAMMERDB_TYPE\": \"mysql\",\n", + " \"USER\": \"root\",\n", + " \"PASSWORD\": \"root\",\n", + " \"HAMMERDB_VUSERS\": 4\n", + " }\n", + " }\n", + " },\n", + " \"numProcesses\": 0\n", + " }\n", + "]\n" + ] + } + ], + "source": [ + "import json\n", + "pretty_connections = json.dumps(connections, indent=2)\n", + "\n", + "print(pretty_connections)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading time per number of loading threads" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MariaDB-4-1 114.58742006868124 [s] for 4 threads on cl-worker11\n", + "MariaDB-4-2 114.58742006868124 [s] for 4 threads on cl-worker11\n", + "MySQL-4-1 180.62911394238472 [s] for 4 threads on cl-worker11\n", + "MySQL-4-2 180.62911394238472 [s] for 4 threads on cl-worker11\n", + "PostgreSQL-4-1 67.62372010201216 [s] for 4 threads on cl-worker11\n", + "PostgreSQL-4-2 67.62372010201216 [s] for 4 threads on cl-worker11\n" + ] + } + ], + "source": [ + "connections_sorted = sorted(connections, key=lambda c: c['name']) \n", + "\n", + "for c in connections_sorted:\n", + " print(c['name'], \n", + " c['timeLoad'], \n", + " '[s] for', \n", + " c['parameter']['connection_parameter']['loading_parameters']['PARALLEL'], \n", + " 'threads on',\n", + " c['hostsystem']['node'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Get monitoring metrics\n", + "\n", + "### Loading" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation.transform_monitoring_results()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Example metric" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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MariaDB-4-14197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.910156...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
MariaDB-4-24197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.9101564197.910156...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
MySQL-4-1407.738281407.738281407.738281407.738281407.738281407.738281407.738281407.738281407.738281407.738281...19851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.742188
MySQL-4-2407.738281407.738281407.738281407.738281407.738281407.738281407.738281407.738281407.738281407.738281...19851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.60937519851.742188
PostgreSQL-4-11138.5234381138.5234381138.5234381138.5234381144.9921881144.9921881144.9921881144.9921881144.9921881144.992188...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
PostgreSQL-4-21138.5234381138.5234381138.5234381138.5234381144.9921881144.9921881144.9921881144.9921881144.9921881144.992188...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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NaN NaN \n", + "MariaDB-4-2 4197.910156 4197.910156 ... NaN NaN \n", + "MySQL-4-1 407.738281 407.738281 ... 19851.609375 19851.609375 \n", + "MySQL-4-2 407.738281 407.738281 ... 19851.609375 19851.609375 \n", + "PostgreSQL-4-1 1144.992188 1144.992188 ... NaN NaN \n", + "PostgreSQL-4-2 1144.992188 1144.992188 ... NaN NaN \n", + "\n", + " 159 160 161 162 \\\n", + "MariaDB-4-1 NaN NaN NaN NaN \n", + "MariaDB-4-2 NaN NaN NaN NaN \n", + "MySQL-4-1 19851.609375 19851.609375 19851.609375 19851.609375 \n", + "MySQL-4-2 19851.609375 19851.609375 19851.609375 19851.609375 \n", + "PostgreSQL-4-1 NaN NaN NaN NaN \n", + "PostgreSQL-4-2 NaN NaN NaN NaN \n", + "\n", + " 163 164 165 166 \n", + "MariaDB-4-1 NaN NaN NaN NaN \n", + "MariaDB-4-2 NaN NaN NaN NaN \n", + "MySQL-4-1 19851.609375 19851.609375 19851.609375 19851.742188 \n", + "MySQL-4-2 19851.609375 19851.609375 19851.609375 19851.742188 \n", + "PostgreSQL-4-1 NaN NaN NaN NaN \n", + "PostgreSQL-4-2 NaN NaN NaN NaN \n", + "\n", + "[6 rows x 167 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation.get_monitoring_metrics()\n", + "\n", + "df = evaluation.get_monitoring_metric('total_cpu_memory')\n", + "\n", + "df.T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot all metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dict_colors = evaluation.get_dict_color_by_connection_property('docker')\n", + "\n", + "evaluation.plot_all_metrics(component='loading', dict_colors=dict_colors)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Benchmarking" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "evaluation.transform_monitoring_results(component='stream')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot all metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dict_colors = evaluation.get_dict_color_by_connection_property('docker')\n", + "\n", + "evaluation.plot_all_metrics(component='stream', dict_colors=dict_colors)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": true + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/test.sh b/test.sh index 81bd8c6d..5dc64169 100644 --- a/test.sh +++ b/test.sh @@ -285,7 +285,7 @@ sleep 5 #### HammerDB Simple -# python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 run +# python hammerdb.py -tr -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 run # 16 warehouses # 16 threads used for loading # 8 terminals in 1 pod @@ -307,7 +307,7 @@ sleep 5 #### HammerDB Monitoring -# python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -m -mc run +# python hammerdb.py -tr -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -m -mc run # 16 warehouses # 16 threads used for loading # 8 terminals in 1 pod @@ -331,7 +331,7 @@ sleep 5 #### HammerDB Complex -# python hammerdb.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run +# python hammerdb.py -tr -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1,2 -rst shared -rss 30Gi -m -mc run # 16 warehouses # 16 threads used for loading # 8 terminals in 1 pod and in 2 pods (4 each) From 16f0922e65657e20b749e65c374034522d159738 Mon Sep 17 00:00:00 2001 From: perdelt Date: Mon, 5 Aug 2024 17:42:23 +0200 Subject: [PATCH 4/6] Docs: More about Benchbase --- benchbase.py | 2 + docs/Example-Benchbase.md | 302 ++++++++++++++++++ .../notebooks/Evaluate-Benchbase.html | 6 +- .../notebooks/Evaluate-Benchbase.ipynb | 72 ++++- test.sh | 6 +- 5 files changed, 365 insertions(+), 23 deletions(-) create mode 100644 docs/Example-Benchbase.md diff --git a/benchbase.py b/benchbase.py index 631af496..64c419e4 100644 --- a/benchbase.py +++ b/benchbase.py @@ -459,6 +459,8 @@ end = default_timer() end_datetime = str(datetime.datetime.now()) duration_experiment = end - start + elif args.mode == 'summary': + experiment.show_summary() else: # configure number of clients per config #list_clients = args.num_query_executors.split(",") diff --git a/docs/Example-Benchbase.md b/docs/Example-Benchbase.md new file mode 100644 index 00000000..8068c4d7 --- /dev/null +++ b/docs/Example-Benchbase.md @@ -0,0 +1,302 @@ +# Example: Benchbase + + + +> TPC-C involves a mix of five concurrent transactions of different types and complexity either executed on-line or queued for deferred execution. The database is comprised of nine types of tables with a wide range of record and population sizes. TPC-C is measured in transactions per minute (tpmC). While the benchmark portrays the activity of a wholesale supplier, TPC-C is not limited to the activity of any particular business segment, but, rather represents any industry that must manage, sell, or distribute a product or service. + +drawing + +References: +1. https://github.com/cmu-db/benchbase/wiki/TPC-C +1. http://www.vldb.org/pvldb/vol7/p277-difallah.pdf + + +## Perform Benchmark + +For performing the experiment we can run the [benchbase file](https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/blob/master/benchbase.py). + +Example: `python benchbase.py -ms 1 -tr -ltf 16 -dbms PostgreSQL -nvu 16 -sf 16 -nbp 1 -sd 5 run` + +This +* starts a clean instance of PostgreSQL (`-dbms`) + * data directory inside a Docker container +* starts 1 loader pod (per DBMS) that + * creates TPC-C schema in the database + * imports data for 16 (`-sf`) warehouses into the DBMS + * using all threads of driver machine (benchbase setting) +* runs 1 (`-nbp`) streams of TPC-C queries (per DBMS) + * running for 5 (`-sd`) minutes + * each stream (pod) having 16 threads (`-nvu`) to simulate 16 users + * target is 16x(`-ltf`) 1024 ops +* with a maximum of 1 DBMS per time (`-ms`) +* tests if results match workflow (`-tr`) +* shows a summary + +### Status + +You can watch the status while benchmark is running via `bexperiments status` + +``` +Dashboard: Running +Message Queue: Running +Data directory: Running +Result directory: Running ++------------------------+--------------+--------------+-------------+--------------+ +| 1706264335 | sut | loaded [s] | loading | monitoring | ++========================+==============+==============+=============+==============+ +| PostgreSQL-64-1-131072 | (1. Running) | 0.64 | (1 Running) | (Running) | ++------------------------+--------------+--------------+-------------+--------------+ +``` + +The code `1706264335` is the unique identifier of the experiment. +You can find the number also in the output of `benchbase.py`. + +### Cleanup + +The script is supposed to clean up and remove everything from the cluster that is related to the experiment after finishing. +If something goes wrong, you can also clean up manually with `bexperiment stop` (removes everything) or `bexperiment stop -e 1706264335` (removes everything that is related to experiment `1706264335`). + +## Evaluate Results + +At the end of a benchmark you will see a summary like + +```bash +### Loading + threads target pod_count [OVERALL].Throughput(ops/sec) [OVERALL].RunTime(ms) [INSERT].Return=OK [INSERT].99thPercentileLatency(us) +PostgreSQL-64-1-16384 64 16384 1 16285.849226 61403.0 1000000 1283.00 +PostgreSQL-64-8-16384 64 16384 8 16189.808395 62334.0 1000000 1029.25 +PostgreSQL-64-1-32768 64 32768 1 32334.206357 30927.0 1000000 2993.00 +PostgreSQL-64-8-32768 64 32768 8 32487.310483 30788.0 1000000 2362.50 +PostgreSQL-64-1-49152 64 49152 1 47429.330298 21084.0 1000000 4343.00 +PostgreSQL-64-8-49152 64 49152 8 48401.920774 20850.0 1000000 3848.50 +PostgreSQL-64-1-65536 64 65536 1 63881.436055 15654.0 1000000 6127.00 +PostgreSQL-64-8-65536 64 65536 8 64436.143011 15540.0 1000000 4843.00 +PostgreSQL-64-1-81920 64 81920 1 71078.257161 14069.0 1000000 6219.00 +PostgreSQL-64-8-81920 64 81920 8 72415.868804 14361.0 1000000 5296.00 +PostgreSQL-64-1-98304 64 98304 1 81586.032471 12257.0 1000000 5027.00 +PostgreSQL-64-8-98304 64 98304 8 86657.160474 11681.0 1000000 5571.00 +PostgreSQL-64-1-114688 64 114688 1 74693.755602 13388.0 1000000 5923.00 +PostgreSQL-64-8-114688 64 114688 8 80616.643342 13037.0 1000000 5275.50 +PostgreSQL-64-1-131072 64 131072 1 81766.148814 12230.0 1000000 6087.00 +PostgreSQL-64-8-131072 64 131072 8 80708.979092 12469.0 1000000 5656.00 + +### Execution + threads target pod_count [OVERALL].Throughput(ops/sec) [OVERALL].RunTime(ms) [READ].Return=OK [READ].99thPercentileLatency(us) [UPDATE].Return=OK [UPDATE].99thPercentileLatency(us) +PostgreSQL-64-1-16384-1 64 16384 1 16281.61 61419.0 499663 540.00 500337 743.00 +PostgreSQL-64-8-16384-1 64 16384 8 16313.68 61310.0 500621 544.75 499379 759.38 +PostgreSQL-64-1-32768-1 64 32768 1 32171.93 31083.0 500316 570.00 499684 925.00 +PostgreSQL-64-8-32768-1 64 32768 8 32481.38 30794.0 500704 594.88 499296 839.75 +PostgreSQL-64-1-49152-1 64 49152 1 48351.22 20682.0 499465 808.00 500535 1395.00 +PostgreSQL-64-8-49152-1 64 49152 8 48521.04 20624.0 500275 946.75 499725 1554.88 +PostgreSQL-64-1-65536-1 64 65536 1 62468.77 16008.0 499253 1069.00 500747 1656.00 +PostgreSQL-64-8-65536-1 64 65536 8 64434.09 15541.0 500305 1056.00 499695 1617.00 +PostgreSQL-64-1-81920-1 64 81920 1 78659.64 12713.0 500203 1313.00 499797 2055.00 +PostgreSQL-64-8-81920-1 64 81920 8 79285.81 12740.0 500409 1337.38 499591 2126.25 +PostgreSQL-64-1-98304-1 64 98304 1 89421.44 11183.0 499133 1425.00 500867 2767.00 +PostgreSQL-64-8-98304-1 64 98304 8 87541.47 11748.0 500122 1363.75 499878 2414.00 +PostgreSQL-64-1-114688-1 64 114688 1 101770.81 9826.0 500000 1351.00 500000 2213.00 +PostgreSQL-64-8-114688-1 64 114688 8 104663.23 9835.0 500450 1515.62 499550 2866.25 +PostgreSQL-64-1-131072-1 64 131072 1 88354.83 11318.0 499788 1566.00 500212 3451.00 +PostgreSQL-64-8-131072-1 64 131072 8 115356.26 9250.0 500084 1526.75 499916 3356.75 +``` + +We can see that the overall throughput is close to the target and that scaled-out drivers (8 pods with 8 threads each) have similar results as a monolithic driver (1 pod with 64 thread). +The runtime is between 8 seconds and 1 minute. + +To see the summary of experiment `1706264335` you can simply call `python benchbase.py -e 1706264335 summary`. + +### Detailed Evaluation + +Results are transformed into pandas DataFrames and can be inspected in detail. +See for example +* [Jupyter Notebooks](https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/images/evaluator_dbmsbenchmarker/notebooks/) + +You can connect to an evaluation server in the cluster by `bexperiments dashboard`. +This forwards ports, so you have +* a Jupyter notebook server at http://localhost:8888 + +You can connect to an evaluation server locally by `bexperiments jupyter`. +This forwards ports, so you have +* a Jupyter notebook server at http://localhost:8888 + +## Adjust Parameters + +The script supports +* exact repetitions for statistical confidence +* variations to scan a large parameters space +* combine results for easy evaluation + +There are various ways to change parameters. + +### Manifests + +The YAML manifests for the components can be found in https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/k8s + +### SQL Scrips + +The SQL scripts for pre and post ingestion can be found in https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/experiments/benchbase + +### Dockerfiles + +The Dockerfiles for the components can be found in https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/images/benchbase + +### Command line + +You maybe want to adjust some of the parameters that are set in the file: `python hammerdb.py -h` + +```bash +usage: ycsb.py [-h] [-aws] [-dbms {PostgreSQL,MySQL}] [-db] [-cx CONTEXT] [-e EXPERIMENT] [-m] [-mc] [-ms MAX_SUT] [-nc NUM_CONFIG] [-ne NUM_QUERY_EXECUTORS] [-nl NUM_LOADING] [-nlp NUM_LOADING_PODS] [-wl {a,b,c,e,f}] [-sf SCALING_FACTOR] [-sfo SCALING_FACTOR_OPERATIONS] [-su SCALING_USERS] + [-sbs SCALING_BATCHSIZE] [-ltf LIST_TARGET_FACTORS] [-tb TARGET_BASE] [-t TIMEOUT] [-rr REQUEST_RAM] [-rc REQUEST_CPU] [-rct REQUEST_CPU_TYPE] [-rg REQUEST_GPU] [-rgt REQUEST_GPU_TYPE] [-rst {None,,local-hdd,shared}] [-rss REQUEST_STORAGE_SIZE] [-rnn REQUEST_NODE_NAME] [-rnl REQUEST_NODE_LOADING] + [-rnb REQUEST_NODE_BENCHMARKING] [-tr] + {run,start,load,summary} + +Perform YCSB benchmarks in a Kubernetes cluster. Number of rows and operations is SF*1,000,000. This installs a clean copy for each target and split of the driver. Optionally monitoring is activated. + +positional arguments: + {run,start,load,summary} + import YCSB data or run YCSB queries + +options: + -h, --help show this help message and exit + -aws, --aws fix components to node groups at AWS + -dbms {PostgreSQL,MySQL}, --dbms {PostgreSQL,MySQL} + DBMS to load the data + -db, --debug dump debug informations + -cx CONTEXT, --context CONTEXT + context of Kubernetes (for a multi cluster environment), default is current context + -e EXPERIMENT, --experiment EXPERIMENT + sets experiment code for continuing started experiment + -m, --monitoring activates monitoring for sut + -mc, --monitoring-cluster + activates monitoring for all nodes of cluster + -ms MAX_SUT, --max-sut MAX_SUT + maximum number of parallel DBMS configurations, default is no limit + -nc NUM_CONFIG, --num-config NUM_CONFIG + number of runs per configuration + -ne NUM_QUERY_EXECUTORS, --num-query-executors NUM_QUERY_EXECUTORS + comma separated list of number of parallel clients + -nl NUM_LOADING, --num-loading NUM_LOADING + number of parallel loaders per configuration + -nlp NUM_LOADING_PODS, --num-loading-pods NUM_LOADING_PODS + total number of loaders per configuration + -wl {a,b,c,e,f}, --workload {a,b,c,e,f} + YCSB default workload + -sf SCALING_FACTOR, --scaling-factor SCALING_FACTOR + scaling factor (SF) = number of rows in millions + -sfo SCALING_FACTOR_OPERATIONS, --scaling-factor-operations SCALING_FACTOR_OPERATIONS + scaling factor = number of operations in millions (=SF if not set) + -su SCALING_USERS, --scaling-users SCALING_USERS + scaling factor = number of total threads + -sbs SCALING_BATCHSIZE, --scaling-batchsize SCALING_BATCHSIZE + batch size + -ltf LIST_TARGET_FACTORS, --list-target-factors LIST_TARGET_FACTORS + comma separated list of factors of 16384 ops as target - default range(1,9) + -tb TARGET_BASE, --target-base TARGET_BASE + ops as target, base for factors - default 16384 = 2**14 + -t TIMEOUT, --timeout TIMEOUT + timeout for a run of a query + -rr REQUEST_RAM, --request-ram REQUEST_RAM + request ram for sut, default 16Gi + -rc REQUEST_CPU, --request-cpu REQUEST_CPU + request cpus for sut, default 4 + -rct REQUEST_CPU_TYPE, --request-cpu-type REQUEST_CPU_TYPE + request node for sut to have node label cpu= + -rg REQUEST_GPU, --request-gpu REQUEST_GPU + request number of gpus for sut + -rgt REQUEST_GPU_TYPE, --request-gpu-type REQUEST_GPU_TYPE + request node for sut to have node label gpu= + -rst {None,,local-hdd,shared}, --request-storage-type {None,,local-hdd,shared} + request persistent storage of certain type + -rss REQUEST_STORAGE_SIZE, --request-storage-size REQUEST_STORAGE_SIZE + request persistent storage of certain size + -rnn REQUEST_NODE_NAME, --request-node-name REQUEST_NODE_NAME + request a specific node for sut + -rnl REQUEST_NODE_LOADING, --request-node-loading REQUEST_NODE_LOADING + request a specific node for loading pods + -rnb REQUEST_NODE_BENCHMARKING, --request-node-benchmarking REQUEST_NODE_BENCHMARKING + request a specific node for benchmarking pods + -tr, --test-result test if result fulfills some basic requirements +``` + +## Monitoring + +[Monitoring](Monitoring.html) can be activated for DBMS only (`-m`) or for all components (`-mc`). + +If monitoring is activated, the summary also contains a section like + +```bash +### Ingestion + SUT - CPU of Ingestion (via counter) [CPUs] SUT - Max RAM of Ingestion [Gb] +PostgreSQL-64-1-16384-1 211.08 3.56 +PostgreSQL-64-1-32768-1 208.34 3.51 +PostgreSQL-64-1-49152-1 43.55 2.78 +PostgreSQL-64-1-65536-1 95.57 3.16 +PostgreSQL-64-1-81920-1 224.71 3.50 +PostgreSQL-64-1-98304-1 208.72 3.50 +PostgreSQL-64-1-114688-1 39.80 2.74 +PostgreSQL-64-1-131072-1 142.15 3.47 +PostgreSQL-64-8-16384-1 192.93 3.51 +PostgreSQL-64-8-32768-1 185.90 3.50 +PostgreSQL-64-8-49152-1 191.40 3.81 +PostgreSQL-64-8-65536-1 189.31 3.77 +PostgreSQL-64-8-81920-1 141.00 3.46 +PostgreSQL-64-8-98304-1 117.22 3.28 +PostgreSQL-64-8-114688-1 209.95 3.50 +PostgreSQL-64-8-131072-1 208.55 3.50 + +### Execution + SUT - CPU of Execution (via counter) [CPUs] SUT - Max RAM of Execution [Gb] +PostgreSQL-64-1-16384-1 158.03 4.02 +PostgreSQL-64-1-32768-1 171.52 4.02 +PostgreSQL-64-1-49152-1 131.15 3.98 +PostgreSQL-64-1-65536-1 185.56 3.68 +PostgreSQL-64-1-81920-1 0.00 3.50 +PostgreSQL-64-1-98304-1 0.00 3.50 +PostgreSQL-64-1-114688-1 0.00 3.50 +PostgreSQL-64-1-131072-1 0.00 3.50 +PostgreSQL-64-8-16384-1 122.51 3.98 +PostgreSQL-64-8-32768-1 110.22 3.97 +PostgreSQL-64-8-49152-1 163.70 4.00 +PostgreSQL-64-8-65536-1 0.00 3.50 +PostgreSQL-64-8-81920-1 169.54 4.00 +PostgreSQL-64-8-98304-1 66.88 3.92 +PostgreSQL-64-8-114688-1 190.45 3.69 +PostgreSQL-64-8-131072-1 146.15 4.02 +``` + +This gives a survey about CPU (in CPU seconds) and RAM usage (in Gb) during loading and execution of the benchmark. + +In this example, metrics are very instable. Metrics are fetched every 30 seconds. +This is too coarse for such a quick example. + + +## Use Persistent Storage + +The default behaviour of bexhoma is that the database is stored inside the ephemeral storage of the Docker container. +If your cluster allows dynamic provisioning of volumes, you might request a persistent storage of a certain type (storageClass) and size. + +Example: `python benchbase.py -dbms PostgreSQL -nvu '8' -su 16 -sf 16 -nbp 1 -sd 5 -nc 2 -rst local-hdd -rss 50Gi run` + +The following status shows we have two volumes of type `local-hdd`. Every experiment running HammerDB's TPC-C of SF=16 (warehouses) will take the databases from these volumes and skip loading. +In this example `-nc` is set to two, that is the complete experiment is repeated twice for statistical confidence. +The first instance of PostgreSQL mounts the volume and generates the data. +All other instances just use the database without generating and loading data. + +``` ++------------------------------------+-----------------+--------------+--------------+-------------------+------------+----------------------+-----------+----------+--------+--------+ +| Volumes | configuration | experiment | loaded [s] | timeLoading [s] | dbms | storage_class_name | storage | status | size | used | ++====================================+=================+==============+==============+===================+============+======================+===========+==========+========+========+ +| bexhoma-storage-postgresql-ycsb-1 | postgresql | ycsb-1 | True | 64 | PostgreSQL | shared | 50Gi | Bound | 50G | 2.1G | ++------------------------------------+-----------------+--------------+--------------+-------------------+------------+----------------------+-----------+----------+--------+--------+ ++------------------+--------------+--------------+--------------------------+ + ++------------------+--------------+--------------+--------------+---------------+ +| 1706957093 | sut | loaded [s] | monitoring | benchmarker | ++==================+==============+==============+==============+===============+ +| MySQL-64-1-16384 | (2. Running) | 2398.11 | (Running) | (1. Running) | ++------------------+--------------+--------------+--------------+---------------+ +``` + + + + diff --git a/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html index 055943bc..82827a85 100644 --- a/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html +++ b/images/evaluator_dbmsbenchmarker/notebooks/Evaluate-Benchbase.html @@ -7484,12 +7484,12 @@