add slurm script

Makefile

@@ -14,4 +14,5 @@ kg-microbe-biomedical:
 kg-microbe-biomedical-function-merge:
 	poetry run kg merge -m duckdb -n 1000000 -e 100000 -s "bacdive, mediadive, madin_etal, rhea_mappings, bactotraits, chebi, ec, envo, go, ncbitaxon, upa, hp, mondo, ctd, wallen_etal, uniprot_human, uniprot_functional_microbes" --merge-label $@
 
-include kg-microbe-merge.Makefile
+include kg-microbe-merge.Makefile
+

download.yaml

@@ -37,7 +37,7 @@
 # 
 - 
   url: git://Knowledge-Graph-Hub/kg-microbe/BactoTraits.tar.gz
-  local_name: BactoTraits.tar.gz
+  local_name: bactotraits.tar.gz
 
 #
 # KG-Microbe [CTD]

hpc/run_parallel_merge.sl

@@ -0,0 +1,32 @@
+#!/bin/bash
+#SBATCH --account=m4689
+#SBATCH --qos=regular
+#SBATCH --constraint=cpu
+#SBATCH --time=360
+#SBATCH --ntasks=1
+#SBATCH --mem=425GB
+#SBATCH --job-name=parallel_merge
+#SBATCH --output=parallel_merge_%A_%a.out
+#SBATCH --error=parallel_merge_%A_%a.err
+#SBATCH --array=0-3
+#SBATCH -N 1
+
+module load python/3.10
+cd kg-microbe-merge
+python -m venv venv-merge
+source venv-merge/bin/activate
+pip install poetry
+poetry install
+
+# Array of merged graph names
+merges=(
+    kg-microbe-core
+    kg-microbe-biomedical
+)
+
+# Get the merge for this job array task
+merge=${merges[$SLURM_ARRAY_TASK_ID]}
+
+echo "Starting $merge"
+time poetry run make $merge
+echo "Finished $merge"

hpc/run_parallel_merge_biomedical_function.sl

@@ -0,0 +1,33 @@
+#!/bin/bash
+#SBATCH --account=m4689
+#SBATCH --qos=regular
+#SBATCH --constraint=cpu
+#SBATCH --time=360
+#SBATCH --ntasks=1
+#SBATCH --mem=425GB
+#SBATCH --job-name=parallel_merge
+#SBATCH --output=parallel_merge_%A_%a.out
+#SBATCH --error=parallel_merge_%A_%a.err
+#SBATCH --array=0
+#SBATCH -N 1
+#SBATCH --mail-type=BEGIN,END
+#SBATCH [email protected]
+
+module load python/3.10
+cd kg-microbe-merge
+python -m venv venv-merge
+source venv-merge/bin/activate
+pip install poetry
+poetry install
+
+# Array of merged graph names
+merges=(
+    kg-microbe-biomedical-function
+)
+
+# Get the merge for this job array task
+merge=${merges[$SLURM_ARRAY_TASK_ID]}
+
+echo "Starting $merge"
+time poetry run make $merge
+echo "Finished $merge"

hpc/run_parallel_merge_function.sl

@@ -0,0 +1,33 @@
+#!/bin/bash
+#SBATCH --account=m4689
+#SBATCH --qos=regular
+#SBATCH --constraint=cpu
+#SBATCH --time=360
+#SBATCH --ntasks=1
+#SBATCH --mem=425GB
+#SBATCH --job-name=parallel_merge
+#SBATCH --output=parallel_merge_%A_%a.out
+#SBATCH --error=parallel_merge_%A_%a.err
+#SBATCH --array=0
+#SBATCH -N 1
+#SBATCH --mail-type=BEGIN,END
+#SBATCH [email protected]
+
+module load python/3.10
+cd kg-microbe-merge
+python -m venv venv-merge
+source venv-merge/bin/activate
+pip install poetry
+poetry install
+
+# Array of merged graph names
+merges=(
+    kg-microbe-function
+)
+
+# Get the merge for this job array task
+merge=${merges[$SLURM_ARRAY_TASK_ID]}
+
+echo "Starting $merge"
+time poetry run make $merge
+echo "Finished $merge"

kg_microbe_merge/utils/duckdb_utils.py

@@ -1,6 +1,7 @@
 """Utility functions for working with DuckDB in the KG Microbe Merge project."""
 
 import os
+from pathlib import Path
 from typing import List
 
 import duckdb
@@ -304,7 +305,9 @@ def duckdb_nodes_merge(nodes_file_list, output_file, priority_sources, batch_siz
     :param priority_sources: List of source names to prioritize.
     """
     # Create a DuckDB connection
-    conn = duckdb.connect("nodes.db")
+    merge_label = Path(output_file).parent.name
+    nodes_db_file = f"{merge_label}_nodes.db"
+    conn = duckdb.connect(nodes_db_file)
 
     # Load the files into DuckDB
     load_into_duckdb(conn, nodes_file_list, "combined_nodes")
@@ -379,7 +382,7 @@ def duckdb_nodes_merge(nodes_file_list, output_file, priority_sources, batch_siz
     finally:
         # Close the connection
         conn.close()
-        os.remove("nodes.db")
+        os.remove(nodes_db_file)
 
 
 def duckdb_edges_merge(edges_file_list, output_file, batch_size=1000000):
@@ -416,7 +419,8 @@ def duckdb_edges_merge(edges_file_list, output_file, batch_size=1000000):
     memory usage and allows for processing of very large datasets that exceed available RAM.
     """
     os.makedirs(TMP_DIR, exist_ok=True)
-    db_file = "edges_persistent.db"
+    merge_label = Path(output_file).parent.name
+    db_file = f"{merge_label}_edges_persistent.db"
     conn = duckdb.connect(db_file)
 
     try: