def run_query(client,
baseline_table,
date,
dry_run,
output_dir=None,
views_only=False):
"""Process a single table, potentially also writing out the generated queries."""
tables = table_names_from_baseline(baseline_table)
last_seen_table = tables["last_seen_table"]
last_seen_view = tables["last_seen_view"]
render_kwargs = dict(header="-- Generated via bigquery_etl.glean_usage\n",
usage_types=USAGE_TYPES)
render_kwargs.update(tables)
job_kwargs = dict(use_legacy_sql=False, dry_run=dry_run)
query_sql = render(QUERY_FILENAME, **render_kwargs)
init_sql = render(QUERY_FILENAME, init=True, **render_kwargs)
view_sql = render(VIEW_FILENAME, **render_kwargs)
sql = query_sql
try:
client.get_table(last_seen_table)
except NotFound:
if views_only:
logging.info("Skipping view for table which doesn't exist:"
f" {last_seen_table}")
return
elif dry_run:
logging.info(f"Table does not yet exist: {last_seen_table}")
else:
logging.info(f"Creating table: {last_seen_table}")
sql = init_sql
else:
if views_only:
write_sql(output_dir, last_seen_view, "view.sql", view_sql)
return
# Table exists, so we will run the incremental query.
job_kwargs.update(
destination=f"{last_seen_table}${date.strftime('%Y%m%d')}",
write_disposition=WriteDisposition.WRITE_TRUNCATE,
query_parameters=[
ScalarQueryParameter("submission_date", "DATE", date)
],
)
if not dry_run:
logging.info(f"Running query for: {last_seen_table}")
if output_dir:
write_sql(output_dir, last_seen_view, "view.sql", view_sql)
write_sql(output_dir, last_seen_table, "query.sql", query_sql)
write_sql(output_dir, last_seen_table, "init.sql", init_sql)
job_config = bigquery.QueryJobConfig(**job_kwargs)
job = client.query(sql, job_config)
if not dry_run:
job.result()
logging.info(f"Recreating view {last_seen_view}")
client.query(view_sql,
bigquery.QueryJobConfig(use_legacy_sql=False)).result()
def run_query(project_id,
baseline_table,
date,
dry_run,
output_dir=None,
output_only=False):
"""Process a single table, potentially also writing out the generated queries."""
tables = table_names_from_baseline(baseline_table)
last_seen_table = tables["last_seen_table"]
last_seen_view = tables["last_seen_view"]
render_kwargs = dict(header="-- Generated via bigquery_etl.glean_usage\n",
usage_types=USAGE_TYPES)
render_kwargs.update(tables)
job_kwargs = dict(use_legacy_sql=False, dry_run=dry_run)
query_sql = render(QUERY_FILENAME, **render_kwargs)
init_sql = render(QUERY_FILENAME, init=True, **render_kwargs)
view_sql = render(VIEW_FILENAME, **render_kwargs)
view_metadata = render(VIEW_METADATA_FILENAME,
format=False,
**render_kwargs)
sql = query_sql
if not (referenced_table_exists(view_sql)):
if output_only:
logging.info("Skipping view for table which doesn't exist:"
f" {last_seen_table}")
return
elif dry_run:
logging.info(f"Table does not yet exist: {last_seen_table}")
else:
logging.info(f"Creating table: {last_seen_table}")
sql = init_sql
elif output_only:
pass
else:
# Table exists, so we will run the incremental query.
job_kwargs.update(
destination=f"{last_seen_table}${date.strftime('%Y%m%d')}",
write_disposition=WriteDisposition.WRITE_TRUNCATE,
query_parameters=[
ScalarQueryParameter("submission_date", "DATE", date)
],
)
if not dry_run:
logging.info(f"Running query for: {last_seen_table}")
if output_dir:
write_sql(output_dir, last_seen_view, "metadata.yaml", view_metadata)
write_sql(output_dir, last_seen_view, "view.sql", view_sql)
write_sql(output_dir, last_seen_table, "query.sql", query_sql)
write_sql(output_dir, last_seen_table, "init.sql", init_sql)
if output_only:
# Return before we initialize the BQ client so that we can generate SQL
# without having BQ credentials.
return
client = bigquery.Client(project_id)
job_config = bigquery.QueryJobConfig(**job_kwargs)
job = client.query(sql, job_config)
if not dry_run:
job.result()
logging.info(f"Recreating view {last_seen_view}")
client.query(view_sql,
bigquery.QueryJobConfig(use_legacy_sql=False)).result()
def run_query(
project_id, baseline_table, date, dry_run, output_dir=None, output_only=False
):
"""Process a single table, potentially also writing out the generated queries."""
tables = table_names_from_baseline(baseline_table, include_project_id=False)
table_id = tables["first_seen_table"]
view_id = tables["first_seen_view"]
render_kwargs = dict(
header="-- Generated via bigquery_etl.glean_usage\n",
project_id=project_id,
# do not match on org_mozilla_firefoxreality
fennec_id=any(
(f"{app_id}_stable" in baseline_table)
for app_id in [
"org_mozilla_firefox",
"org_mozilla_fenix_nightly",
"org_mozilla_fennec_aurora",
"org_mozilla_firefox_beta",
"org_mozilla_fenix",
]
),
)
render_kwargs.update(tables)
job_kwargs = dict(use_legacy_sql=False, dry_run=dry_run)
query_sql = render(QUERY_FILENAME, **render_kwargs)
init_sql = render(INIT_FILENAME, **render_kwargs)
view_sql = render(VIEW_FILENAME, **render_kwargs)
view_metadata = render(VIEW_METADATA_FILENAME, format=False, **render_kwargs)
sql = query_sql
if not (referenced_table_exists(view_sql)):
if output_only:
logging.info("Skipping view for table which doesn't exist:" f" {table_id}")
return
elif dry_run:
logging.info(f"Table does not yet exist: {table_id}")
else:
logging.info(f"Creating table: {table_id}")
sql = init_sql
elif output_only:
pass
else:
# Table exists, so just overwrite the entire table with the day's results
job_kwargs.update(
destination=f"{project_id}.{table_id}",
write_disposition=WriteDisposition.WRITE_TRUNCATE,
query_parameters=[ScalarQueryParameter("submission_date", "DATE", date)],
)
if not dry_run:
logging.info(f"Running query for: {table_id}")
if output_dir:
write_sql(output_dir, view_id, "metadata.yaml", view_metadata)
write_sql(output_dir, view_id, "view.sql", view_sql)
write_sql(output_dir, table_id, "query.sql", query_sql)
write_sql(output_dir, table_id, "init.sql", init_sql)
if output_only:
# Return before we initialize the BQ client so that we can generate SQL
# without having BQ credentials.
return
client = bigquery.Client(project_id)
job_config = bigquery.QueryJobConfig(**job_kwargs)
job = client.query(sql, job_config)
if not dry_run:
job.result()
logging.info(f"Recreating view {view_id}")
client.query(view_sql, bigquery.QueryJobConfig(use_legacy_sql=False)).result()
