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Update backfill scripts for classifications #42

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merged 9 commits into from
Oct 18, 2023
Merged

Update backfill scripts for classifications #42

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a83d0f0
update classifications backfill script to chunk and save in file
yuenmichelle1 Oct 16, 2023
16df964
update to <= remove unused limit in query
yuenmichelle1 Oct 16, 2023
73cfae1
update copy into source
yuenmichelle1 Oct 17, 2023
f8fa8e3
split backfill to file creation then copy from files
yuenmichelle1 Oct 17, 2023
782d043
cast to int
yuenmichelle1 Oct 18, 2023
cf756ca
Merge branch 'main' into update-backfill-scripts-for-classifications
yuenmichelle1 Oct 18, 2023
7ac7786
revert accidental adding commas on limit
yuenmichelle1 Oct 18, 2023
25af5bc
Merge branch 'main' into update-backfill-scripts-for-classifications
yuenmichelle1 Oct 18, 2023
522a0c7
add keepalives to hopefully ensure connection does not get lost
yuenmichelle1 Oct 18, 2023
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2 changes: 1 addition & 1 deletion scripts/copy_classifications_from_files.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@

output_file_no = 0
while output_file_no <= num_files:
with psycopg.connect(f"host={TIMESCALE_CONNECTION} port={TIMESCALE_PORT} dbname={ERAS_DB} user={ERAS_USER} password={ERAS_PW} sslmode=require") as timescale_db_conn:
with psycopg.connect(f"host={TIMESCALE_CONNECTION} port={TIMESCALE_PORT} dbname={ERAS_DB} user={ERAS_USER} password={ERAS_PW} sslmode=require keepalives=1 keepalives_idle=30 keepalives_interval=10 keepalives_count=20") as timescale_db_conn:
with timescale_db_conn.cursor(name="timescale_cursor").copy("COPY classification_events FROM STDIN DELIMITER ',' CSV HEADER") as timescale_copy:
timescale_copy.write(open(f"prod_classifications_{output_file_no}.csv").read())
output_file_no += 1
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2 changes: 1 addition & 1 deletion scripts/save_classifications_chunk_in_files.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@
else:
query = f"{classifications_query} limit {limit} offset {limit * offset}"

with psycopg.connect(f"host={PANOPTES_CONN} port={PANOPTES_PORT} dbname={PANOPTES_DB} user={PANOPTES_USER} password={PANOPTES_PW} sslmode=require") as panoptes_db_conn:
with psycopg.connect(f"host={PANOPTES_CONN} port={PANOPTES_PORT} dbname={PANOPTES_DB} user={PANOPTES_USER} password={PANOPTES_PW} sslmode=require keepalives=1 keepalives_idle=30 keepalives_interval=10 keepalives_count=20") as panoptes_db_conn:
with open(f"prod_classifications_{offset}.csv", "wb") as f:
with panoptes_db_conn.cursor(name="panoptes_cursor").copy(f"COPY ({classifications_query}) TO STDOUT WITH CSV HEADER", (FIRST_INGESTED_CLASSIFICATION_ID,)) as panoptes_copy:
for data in panoptes_copy:
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