[sqllab]More granular sqllab logging #5736
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| def upgrade(): | ||
| op.alter_column('query', 'start_running_time', nullable=False, new_column_name='time_at_db') |
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This table tends to have hanging locks and is hard to alter. I've had issue every time I've had to alter this model where it just completely lock up everything. We'd all need to schedule downtime to allow for this.
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Maybe we can use some sort of tracing instead.
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@mistercrunch Can you flesh this out a little more or provide an example? I'll be happy to investigate.
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I mean just using statsd.timing(DURATION)
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Codecov Report
@@ Coverage Diff @@
## master #5736 +/- ##
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- Coverage 63.75% 63.74% -0.01%
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Files 374 374
Lines 23320 23330 +10
Branches 2608 2608
==========================================
+ Hits 14867 14872 +5
- Misses 8440 8445 +5
Partials 13 13
Continue to review full report at Codecov.
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For the statsD key it seems like they should potentially by more descriptive, i.e., start with the sqllab prefix so rather than time_pending it could be something like sqllab.query.time_pending. You can look at Datadog for examples of how other applications define their keys.
superset/sql_lab.py
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| db_engine_spec.execute(cursor, query.executed_sql, async_=True) | ||
| logging.info('Handling cursor') | ||
| db_engine_spec.handle_cursor(cursor, query, session) | ||
| logging.info('Fetching data: {}'.format(query.to_dict())) | ||
| data = db_engine_spec.fetch_data(cursor, query.limit) | ||
| stats_logger.timing('time_in_database', utils.now_as_float() - query_start_time) |
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I wonder if there's a better (more descriptive) name than time_in_database? May time_executing_query?
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That makes sense. I updated the names. |
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* quote hive column names (apache#5368) * create db migration * use stats_logger timing * trigger build (cherry picked from commit 9a4bba4)
* quote hive column names (apache#5368) * create db migration * use stats_logger timing * trigger build
* quote hive column names (apache#5368) * create db migration * use stats_logger timing * trigger build
mistercrunch
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This PR improves how sqllab logs its performance by logging at a more granular level primarily for asynchronous queries.
It logs the
(for asynchroous queries) time spent pending
time spent in the database
time spent writing to results_backend
time spent time spent reading from results_backend
This PR depends on #5844
@mistercrunch @john-bodley