From e76189fa1e1e7b9d32de18aefa3a614bef7b7ddd Mon Sep 17 00:00:00 2001 From: Matt Green Date: Mon, 5 Aug 2024 14:25:59 -0700 Subject: [PATCH 1/2] Update Readme --- .gitignore | 1 + README.md | 14 +++++++++----- docs/images/denormalized_dark.png | Bin 0 -> 14013 bytes docs/images/denormalized_logo.png | Bin 0 -> 15675 bytes 4 files changed, 10 insertions(+), 5 deletions(-) create mode 100644 docs/images/denormalized_dark.png create mode 100644 docs/images/denormalized_logo.png diff --git a/.gitignore b/.gitignore index 9026c77..a1ab9bc 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ /target .vscode +.DS_Store diff --git a/README.md b/README.md index 2ec0b23..94c88ee 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,13 @@ -# Denormalized +

+ + Denormalized Logo + +

Denormalized is a fast embeddable stream processing engine built on Apache DataFusion. +It currently supports sourcing and sinking to kafka, windowed aggregations, and stream joins. -While this repo is very much a *work-in-progress*, we currently support windowed aggregations and joins on streams of data with a -connector available for Kafka. +This repo is still a *work-in-progress* and we are actively seeking design partners. If you have have a specific use-case you'd like to discuss please drop us a line via a github issue or email hello@denormalized.io. ## Building Denormalized @@ -19,5 +23,5 @@ With the data generation in place, run - ## Credits -Denormalized is built and maintained by [Denormalized Inc](www.denormalized.io) from San Francisco. Please drop in a line to -hello@denormalized.io or simply open up a GitHub Issue. +Denormalized is built and maintained by [Denormalized](https://www.denormalized.io) in San Francisco. 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zdaW~zS<_P}QQaYpQ|5LbANLbPYg1*?=`B&vyDv;KPX%Z!`{_&Uf8S+L%I7(0um9=Y mRZoWhwO0ZEkGV5TX`{PUv}EqvWXXOy>$+M-nw5_n-u^$qVj$oE literal 0 HcmV?d00001 From 82aa86421d7a4d23cab0c8cc48e9fc46abb39c44 Mon Sep 17 00:00:00 2001 From: Matt Green Date: Tue, 6 Aug 2024 14:37:02 -0700 Subject: [PATCH 2/2] add new example --- Cargo.lock | 2 + Cargo.toml | 2 +- README.md | 37 ++++++++++----- docs/kafka_rideshare_example.md | 35 +++++++++++++++ examples/Cargo.toml | 2 + examples/examples/emit_measurements.rs | 51 +++++++++++++++++++++ examples/examples/simple_aggregation.rs | 46 +++++++++++++++++++ examples/examples/test.rs | 60 ------------------------- 8 files changed, 163 insertions(+), 72 deletions(-) create mode 100644 docs/kafka_rideshare_example.md create mode 100644 examples/examples/emit_measurements.rs create mode 100644 examples/examples/simple_aggregation.rs delete mode 100644 examples/examples/test.rs diff --git a/Cargo.lock b/Cargo.lock index 99d8f0c..ef8c7e8 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1110,7 +1110,9 @@ dependencies = [ "datafusion-physical-expr", "df-streams-core", "futures", + "rand", "rdkafka", + "serde", "serde_json", "tempfile", "tokio", diff --git a/Cargo.toml b/Cargo.toml index 1e83231..34cd93d 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -50,7 +50,7 @@ futures = "0.3" tracing = "0.1.40" tracing-log = "0.2.0" tracing-subscriber = "0.3.18" -tokio = { version = "1.36", features = ["macros", "rt", "sync"] } +tokio = { version = "1.36", features = ["macros", "rt", "sync", "rt-multi-thread"] } async-trait = "0.1.81" rdkafka = "0.36.2" log = "^0.4" diff --git a/README.md b/README.md index 94c88ee..2dcf250 100644 --- a/README.md +++ b/README.md @@ -9,17 +9,32 @@ It currently supports sourcing and sinking to kafka, windowed aggregations, and This repo is still a *work-in-progress* and we are actively seeking design partners. If you have have a specific use-case you'd like to discuss please drop us a line via a github issue or email hello@denormalized.io. -## Building Denormalized - -Simply run `cargo build` - -## Running Examples - -See our [benchmarking repo](https://github.com/probably-nothing-labs/benchmarking) for local Kafka setup and data generation. - -With the data generation in place, run - - -`cargo run --example kafka_rideshare` +## Quickstart + +### Prerequisites +- Docker +- Rust/Cargo installed + +### Running an example +1. Start kafka in docker `docker run -p 9092:9092 --name kafka apache/kafka` +2. Start emitting some sample data: `cargo run --example emit_measurements` +3. Run a [simple streaming aggregation](./examples/examples/simple_aggregation.rs) on the data using denormalized: `cargo run --example emit_measurements` + +## More examples + +A more powerful example can be seen in our [kafka ridesharing example](./docs/kafka_rideshare_example.md) + +## Roadmap +- [x] Stream aggregation +- [x] Stream joins +- [ ] Checkpointing / restoration +- [ ] Session windows +- [ ] Stateful UDF API +- [ ] DuckDB support +- [ ] Reading/writing from Postgres +- [ ] Python bindings +- [ ] Typescript bindings +- [ ] UI ## Credits diff --git a/docs/kafka_rideshare_example.md b/docs/kafka_rideshare_example.md new file mode 100644 index 0000000..607c45c --- /dev/null +++ b/docs/kafka_rideshare_example.md @@ -0,0 +1,35 @@ +# Kafka Rideshare Example + +This example application aggregates data across a more involved example setup. + +### Configure Kafka Cluster + +Clone our [docker compose files for running kafka](https://github.com/probably-nothing-labs/kafka-monitoring-stack-docker-compose). If you already have a different kafka cluster running, you can skip this step. +```sh +git clone git@github.com:probably-nothing-labs/kafka-monitoring-stack-docker-compose.git +cd kafka-monitoring-stack-docker-compose +docker compose -f denormalized-benchmark-cluster.yml up +``` + +This will spin up a 3 node kafka cluster in docker along with an instance of kafka-ui that can be viewed at http://localhost:8080/ + +### Generate some sample data to the kafka cluster + +We wrote a [small rust tool](https://github.com/probably-nothing-labs/benchmarking) that will send fake traffic to the locally run rust program. +```sh +git clone git@github.com:probably-nothing-labs/benchmarking.git +cd benchmarking +cargo run -- -d 60 -a 1000 +``` + +This will start a simulation for 60s and will create two topics: `driver-imu-data` and `trips` which should have around ~58k and ~500 messages accordingly. +There are several other knobs that can be tuned to change the amount of traffic which can be viewed with `cargo run -- --help`. +There are also several other knobs that are not exposes but can be changed in the [src/main.rs](https://github.com/probably-nothing-labs/benchmarking/blob/main/src/main.rs#L104-L108) file + +### Run a Streaming Datafusion job + +```sh +cargo run --example kafka_rideshare +``` + +Once everything is setup and one of the two streaming jobs is running, it is recommend to re-run the kafka data generation tool so that live data is produced. This is because watermark tracking of streaming data makes it difficult to properly aggregate older data that lives in the kafka topic. diff --git a/examples/Cargo.toml b/examples/Cargo.toml index 66611e9..a94c834 100644 --- a/examples/Cargo.toml +++ b/examples/Cargo.toml @@ -20,7 +20,9 @@ tracing = { workspace = true } futures = { workspace = true } tracing-log = { workspace = true } tracing-subscriber = { workspace = true } +serde = { workspace = true } serde_json = { workspace = true } tokio = { workspace = true, features = ["rt-multi-thread", "parking_lot"] } tempfile = { version = "3" } rdkafka = { workspace = true } +rand = "0.8.5" diff --git a/examples/examples/emit_measurements.rs b/examples/examples/emit_measurements.rs new file mode 100644 index 0000000..311bbcd --- /dev/null +++ b/examples/examples/emit_measurements.rs @@ -0,0 +1,51 @@ +use datafusion::error::Result; +use rdkafka::producer::FutureProducer; +use serde::{Deserialize, Serialize}; +use std::time::{SystemTime, UNIX_EPOCH}; + +use rdkafka::config::ClientConfig; +use rdkafka::producer::FutureRecord; +use rdkafka::util::Timeout; + +#[derive(Serialize, Deserialize)] +pub struct Measurment { + occurred_at_ms: u64, + temperature: f64, +} + +/// docker run -p 9092:9092 --name kafka apache/kafka +#[tokio::main] +async fn main() -> Result<()> { + let producer: FutureProducer = ClientConfig::new() + .set("bootstrap.servers", String::from("localhost:9092")) + .set("message.timeout.ms", "60000") + .create() + .expect("Producer creation error"); + + let topic = "temperature".to_string(); + + loop { + let msg = serde_json::to_vec(&Measurment { + occurred_at_ms: get_timestamp_ms(), + temperature: rand::random::() * 115.0, + }) + .unwrap(); + + producer + .send( + FutureRecord::<(), Vec>::to(topic.as_str()).payload(&msg), + Timeout::Never, + ) + .await + .unwrap(); + + tokio::time::sleep(tokio::time::Duration::from_millis(1)).await; + } +} + +fn get_timestamp_ms() -> u64 { + let now = SystemTime::now(); + let since_the_epoch = now.duration_since(UNIX_EPOCH).expect("Time went backwards"); + + since_the_epoch.as_millis() as u64 +} diff --git a/examples/examples/simple_aggregation.rs b/examples/examples/simple_aggregation.rs new file mode 100644 index 0000000..3ce7878 --- /dev/null +++ b/examples/examples/simple_aggregation.rs @@ -0,0 +1,46 @@ +use std::time::Duration; + +use datafusion::error::Result; +use datafusion::functions_aggregate::average::avg; +use datafusion_expr::{col, max, min}; + +use df_streams_core::context::Context; +use df_streams_core::datasource::kafka::{ConnectionOpts, KafkaTopicBuilder}; +use df_streams_core::physical_plan::utils::time::TimestampUnit; + +#[tokio::main] +async fn main() -> Result<()> { + let sample_event = r#"{"occurred_at_ms": 1715201766763, "temperature": 87.2}"#; + + let bootstrap_servers = String::from("localhost:9092"); + + let ctx = Context::new()?; + + let mut topic_builder = KafkaTopicBuilder::new(bootstrap_servers.clone()); + + let source_topic = topic_builder + .with_timestamp(String::from("occurred_at_ms"), TimestampUnit::Int64Millis) + .with_encoding("json")? + .with_topic(String::from("temperature")) + .infer_schema_from_json(sample_event)? + .build_reader(ConnectionOpts::from([ + ("auto.offset.reset".to_string(), "earliest".to_string()), + ("group.id".to_string(), "sample_pipeline".to_string()), + ])) + .await?; + + let ds = ctx.from_topic(source_topic).await?.streaming_window( + vec![], + vec![ + min(col("temperature")).alias("min"), + max(col("temperature")).alias("max"), + avg(col("temperature")).alias("average"), + ], + Duration::from_millis(1_000), // 5 second window + None, + )?; + + ds.clone().print_stream().await?; + + Ok(()) +} diff --git a/examples/examples/test.rs b/examples/examples/test.rs deleted file mode 100644 index d4d20b0..0000000 --- a/examples/examples/test.rs +++ /dev/null @@ -1,60 +0,0 @@ -#![allow(dead_code)] -#![allow(unused_variables)] -#![allow(unused_imports)] - -use datafusion::error::Result; -use df_streams_core::datasource::kafka::{ConnectionOpts, KafkaReadConfig, KafkaTopicBuilder}; -use std::{sync::Arc, time::Duration}; - -use rdkafka::admin::AdminClient; -use rdkafka::admin::AdminOptions; -use rdkafka::admin::ConfigResource; -use rdkafka::admin::ConfigResourceResult; -use rdkafka::admin::ResourceSpecifier; -use rdkafka::config::ClientConfig; -use rdkafka::config::FromClientConfig; -use rdkafka::consumer::Consumer; -use rdkafka::consumer::StreamConsumer; -use rdkafka::metadata::MetadataTopic; -use tracing::field::debug; - -#[tokio::main] -async fn main() -> Result<()> { - let bootstrap_servers = String::from("localhost:19092,localhost:29092,localhost:39092"); - let mut client_config = ClientConfig::new(); - client_config.set("bootstrap.servers", bootstrap_servers.to_string()); - - let admin = AdminClient::from_config(&client_config).unwrap(); - - // let res: Vec = admin - // .describe_configs( - // &vec![ResourceSpecifier::Topic("out_topic")], - // &AdminOptions::default(), - // ) - // .await - // .unwrap() - // .into_iter() - // .map(|v| v.unwrap()) - // .collect(); - // - // for (k, v) in res[0].entry_map().into_iter() { - // println!("{}: {:?}", k, v.value); - // } - - let mut client_config = ClientConfig::new(); - - client_config.set("bootstrap.servers", bootstrap_servers.to_string()); - - let consumer: StreamConsumer = client_config.create().expect("Consumer creation failed"); - - let data = consumer - .fetch_metadata(Some("out_topic"), Duration::from_millis(5_000)) - .unwrap(); - let topic_metadata = data.topics(); - let md = &topic_metadata[0]; - let partitions = md.partitions(); - - println!("{:?}", partitions.len()); - - Ok(()) -}