serial inserts for scaling prepare, factored out sample name #7288
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kcibul
commented
Jun 4, 2021
| `{fq_sample_mapping_table}` s ON (new_pet.sample_id = s.sample_id)) | ||
| """ | ||
| ( | ||
| location INT64, |
kcibul
commented
Jun 4, 2021
| @@ -297,7 +327,7 @@ def make_extract_table(fq_pet_vet_dataset, | |||
| #Default QueryJobConfig will be merged into job configs passed in | |||
| #but if a specific default config is being updated (eg labels), new config must be added | |||
| #to the client._default_query_job_config that already exists | |||
| default_config = QueryJobConfig(labels=query_labels_map, priority="INTERACTIVE", use_query_cache=False) | |||
| default_config = QueryJobConfig(labels=query_labels_map, priority="INTERACTIVE", use_query_cache=True) | |||
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I don't know why this was false before, probably for testing/benchmarking
ahaessly
approved these changes
Jun 7, 2021
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| cohort_extract_final_query_job.result() | ||
| JOB_IDS.add((f"insert final cohort table {fq_destination_table_data}", cohort_extract_final_query_job.job_id)) | ||
| sql = f""" |
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is it more or less error prone in python to reuse the same variable name? sql
should we instead use create_table_sql, etc?
This was referenced Mar 17, 2023
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Two primary sets of changes
Testing
Tested on the GVS tieout set. As expected the only difference in the cohort extract tables is that we are no longer seeing mis-joined VET information at
*sites (which is a nice side benefits). Otherwise tables tie out exactly in SQL.In addition, I ran a full GIAB tieout before and after and the results are identical