[nytai]

SUMMARY

Fixes cache warmup via celery job.

• adds cache and data cache configs to the docker-compose superset_config to enable caching for development env.
• add authentication to the cache warmup celery beat job, using the THUMBNAIL_SELENIUM_USER config for auth.
• use the /superset/warm_up_cache endpoint for warming up the cache.
• run the warmup call as a single celery job instead of running all the warmups in single job. This approach should enable some parallelization of the warm up calls. A slow warmup call should also not slow down the entire process.

There is currently an open PR that addresses this issue, however it is using a web driver process to compute the warmup by visiting the dashboard which seems a bit process heavy. Since there is already a cache warmup endpoint that is able to handle charts and filters combos, it make more sense to use that endpoint.

BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

TESTING INSTRUCTIONS

• use the docker-compose workflow
• Add a celery cache warmup beat config using top_n_strategy, set it to run at a high interval (for eg, every minute). documented here
• visit dashboards to that top n strategy has data to work with
• observe the cache warmup logs in the worker
• visit dashboards and notice the charts are cached

ADDITIONAL INFORMATION

• Has associated issue: Fixes warm up cache does not work #18933, Fixes Cache warm-ups never succeed #9597
• Required feature flags:
• Changes UI
• Includes DB Migration (follow approval process in SIP-59)
  • Migration is atomic, supports rollback & is backwards-compatible
  • Confirm DB migration upgrade and downgrade tested
  • Runtime estimates and downtime expectations provided
• Introduces new feature or API
• Removes existing feature or API

[codecov]

Codecov Report

Merging #21076 (088ab7d) into master (5113b01) will decrease coverage by 0.05%.
The diff coverage is 34.28%.

❗ Current head 088ab7d differs from pull request most recent head e233d65. Consider uploading reports for the commit e233d65 to get more accurate results

@@            Coverage Diff             @@
##           master   #21076      +/-   ##
==========================================
- Coverage   66.28%   66.23%   -0.06%     
==========================================
  Files        1770     1770              
  Lines       67522    67528       +6     
  Branches     7177     7177              
==========================================
- Hits        44754    44724      -30     
- Misses      20934    20970      +36     
  Partials     1834     1834              

Flag	Coverage Δ
hive	53.16% <17.14%> (-0.01%)	⬇️
mysql	?
postgres	80.96% <34.28%> (-0.05%)	⬇️
presto	53.06% <17.14%> (-0.01%)	⬇️
python	81.38% <34.28%> (-0.11%)	⬇️
sqlite	79.56% <34.28%> (-0.05%)	⬇️
unit	?

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
superset/tasks/cache.py	61.15% <34.28%> (-12.76%)	⬇️
superset/common/utils/dataframe_utils.py	90.47% <0.00%> (-4.77%)	⬇️
superset/db_engine_specs/mysql.py	94.04% <0.00%> (-4.77%)	⬇️
superset/initialization/__init__.py	89.96% <0.00%> (-1.74%)	⬇️
superset/models/core.py	88.03% <0.00%> (-0.72%)	⬇️
superset/views/core.py	75.15% <0.00%> (-0.46%)	⬇️

📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more

[geido]

LGTM!

[nytai]

rerunning CI

[nytai]

UPDATE: I've recently discovered that the /superset/warm_up_cache endpoint does not work with the new charts based on the /api/v1/chart/data api and with dashboards that are using dashboard native filters. Generating a query context in the backend only will be quite difficult, so the approach in #20387 might be better