feat(mapping-optimizer): Support in operator for mapping optimizer #5685
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This was a TODO item. But on the spans dataset, one easy to encounter situation
is a condition like `sentry_tags[key] IN (value1, value2)`. This results in a
sql like
`in((arrayElement(sentry_tags.value, indexOf(sentry_tags.key, 'key')) AS `_snuba_sentry_tags[key]`), ['value1', 'value1'])`
which scans the entire `sentry_tags.key` and `sentry_tags.value` columns. The
optimization here is to use the tags hash map which gives us a condition like
`hasAny(_sentry_tags_hash_map, array(cityHash64('environment=prod'), cityHash64('environment=production')))`.
Codecov ReportAll modified and coverable lines are covered by tests ✅
✅ All tests successful. No failed tests found Additional details and impacted files@@ Coverage Diff @@
## master #5685 +/- ##
=======================================
Coverage 89.92% 89.93%
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Files 898 898
Lines 43453 43474 +21
Branches 299 299
=======================================
+ Hits 39077 39098 +21
Misses 4334 4334
Partials 42 42 ☔ View full report in Codecov by Sentry. |
evanh
approved these changes
Mar 25, 2024
Zylphrex
commented
Mar 25, 2024
| @@ -265,7 +351,7 @@ def _get_condition_without_redundant_checks( | |||
| if tag_exist_match: | |||
| matched_tag_exists_conditions[condition_id] = tag_exist_match | |||
| if not tag_exist_match: | |||
| eq_match = self.__optimizable_pattern.match(cond) | |||
| eq_match = self.__equals_condition_pattern.match(cond) | |||
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@volokluev would you happen to know if I need to implement this removing of redundant checks for IN conditions?
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you could but it's not strictly necessary. I'm not sure how often we get those cases with IN conditions. Definitely something that can be added later
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I think this is less common on the older datasets but more likely to happen with the spans dataset as we have sentry_tags which contains some more commonly used columns.
The example I ran into was with environment. For a 24h period, it read >48GiB of data, and after applying this optimization, I saw it was reduced to <24GiB of data. On 7 day periods, the query was already timing out. So this optimization should already be helpful
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oh yes absolutely. Merge the PR. I was saying that the redundant clause optimization is probably not going to be as applicable for IN clauses
Zylphrex
deleted the
txiao/feat/support-in-operator-for-mapping-optimizers
branch
|
PR reverted: 8c6329d |
getsentry-bot
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Mar 26, 2024
…mizer (#5685)" This reverts commit cf89313. Co-authored-by: Zylphrex <[email protected]>
Zylphrex
added a commit
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Mar 26, 2024
Re-apply #5685 This was a TODO item. But on the spans dataset, one easy to encounter situation is a condition like ``` sentry_tags[key] IN (value1, value2) ``` This results in a sql like ``` in((arrayElement(sentry_tags.value, indexOf(sentry_tags.key, 'key')) AS `_snuba_sentry_tags[key]`), ['value1', 'value1']) ``` which scans the entire `sentry_tags.key` and `sentry_tags.value` columns. The optimization here is to use the tags hash map which gives us a condition like ``` hasAny(_sentry_tags_hash_map, array(cityHash64('key=value1'), cityHash64('key=value1'))) ```
Zylphrex
added a commit
that referenced
this pull request
Mar 26, 2024
…5691) Re-apply #5685 This was a TODO item. But on the spans dataset, one easy to encounter situation is a condition like ``` sentry_tags[key] IN (value1, value2) ``` This results in a sql like ``` in((arrayElement(sentry_tags.value, indexOf(sentry_tags.key, 'key')) AS `_snuba_sentry_tags[key]`), ['value1', 'value1']) ``` which scans the entire `sentry_tags.key` and `sentry_tags.value` columns. The optimization here is to use the tags hash map which gives us a condition like ``` hasAny(_sentry_tags_hash_map, array(cityHash64('key=value1'), cityHash64('key=value1'))) ```
Zylphrex
added a commit
that referenced
this pull request
Mar 26, 2024
…5691) Re-apply #5685 This was a TODO item. But on the spans dataset, one easy to encounter situation is a condition like ``` sentry_tags[key] IN (value1, value2) ``` This results in a sql like ``` in((arrayElement(sentry_tags.value, indexOf(sentry_tags.key, 'key')) AS `_snuba_sentry_tags[key]`), ['value1', 'value1']) ``` which scans the entire `sentry_tags.key` and `sentry_tags.value` columns. The optimization here is to use the tags hash map which gives us a condition like ``` hasAny(_sentry_tags_hash_map, array(cityHash64('key=value1'), cityHash64('key=value1'))) ```
Zylphrex
added a commit
that referenced
this pull request
Mar 27, 2024
…5691) (#5692) Re-apply #5685 This was a TODO item. But on the spans dataset, one easy to encounter situation is a condition like ``` sentry_tags[key] IN (value1, value2) ``` This results in a sql like ``` in((arrayElement(sentry_tags.value, indexOf(sentry_tags.key, 'key')) AS `_snuba_sentry_tags[key]`), ['value1', 'value1']) ``` which scans the entire `sentry_tags.key` and `sentry_tags.value` columns. The optimization here is to use the tags hash map which gives us a condition like ``` hasAny(_sentry_tags_hash_map, array(cityHash64('key=value1'), cityHash64('key=value1'))) ```
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This was a TODO item. But on the spans dataset, one easy to encounter situation is a condition like
This results in a sql like
which scans the entire
sentry_tags.keyandsentry_tags.valuecolumns. The optimization here is to use the tags hash map which gives us a condition like