Buckets:

glennmatlin's picture
download
raw
2.1 kB
#!/bin/bash
#SBATCH --job-name=check_ids
#SBATCH --output=logs/check_ids/%x_%j.out
#SBATCH --error=logs/check_ids/%x_%j.err
#SBATCH --account=gts-mriedl3
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
#SBATCH --mem=64G
#SBATCH --time=01:00:00
set -euo pipefail
mkdir -p logs/check_ids
cd "${SLURM_SUBMIT_DIR:-$(pwd)}"
COMBINED="/storage/scratch1/6/cchakraborty3/stratified_data/stratified/stratified_combined.jsonl"
ALL="/storage/scratch1/6/cchakraborty3/data_attribution/stratified_data/stratified_all.jsonl"
echo "Extracting doc_id from stratified_combined..."
jq -r '.doc_id' "$COMBINED" | sort > /tmp/combined_ids_${SLURM_JOB_ID}.txt
COMBINED_COUNT=$(wc -l < /tmp/combined_ids_${SLURM_JOB_ID}.txt)
echo "stratified_combined: ${COMBINED_COUNT} ids"
echo "Extracting id from stratified_all..."
jq -r '.id' "$ALL" | sort > /tmp/all_ids_${SLURM_JOB_ID}.txt
ALL_COUNT=$(wc -l < /tmp/all_ids_${SLURM_JOB_ID}.txt)
echo "stratified_all: ${ALL_COUNT} ids"
echo ""
echo "=== Comparison ==="
ONLY_COMBINED=$(comm -23 /tmp/combined_ids_${SLURM_JOB_ID}.txt /tmp/all_ids_${SLURM_JOB_ID}.txt | wc -l)
ONLY_ALL=$(comm -13 /tmp/combined_ids_${SLURM_JOB_ID}.txt /tmp/all_ids_${SLURM_JOB_ID}.txt | wc -l)
SHARED=$(comm -12 /tmp/combined_ids_${SLURM_JOB_ID}.txt /tmp/all_ids_${SLURM_JOB_ID}.txt | wc -l)
echo "IDs in both: ${SHARED}"
echo "IDs only in combined: ${ONLY_COMBINED}"
echo "IDs only in all: ${ONLY_ALL}"
if [ "$ONLY_COMBINED" -eq 0 ] && [ "$ONLY_ALL" -eq 0 ]; then
echo ""
echo "PASS: ID sets match exactly."
else
echo ""
echo "MISMATCH: ID sets differ."
if [ "$ONLY_COMBINED" -gt 0 ]; then
echo ""
echo "Sample IDs only in combined (first 10):"
comm -23 /tmp/combined_ids_${SLURM_JOB_ID}.txt /tmp/all_ids_${SLURM_JOB_ID}.txt | head -10
fi
if [ "$ONLY_ALL" -gt 0 ]; then
echo ""
echo "Sample IDs only in all (first 10):"
comm -13 /tmp/combined_ids_${SLURM_JOB_ID}.txt /tmp/all_ids_${SLURM_JOB_ID}.txt | head -10
fi
fi
rm -f /tmp/combined_ids_${SLURM_JOB_ID}.txt /tmp/all_ids_${SLURM_JOB_ID}.txt

Xet Storage Details

Size:
2.1 kB
·
Xet hash:
dd1789dfe0fd1a4afb2dc1aca870b4c67c6251e2221fe430992c382b7d1c9623

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.