Currently, the planning process shows a performance degradation when comparing to version 1.25. Worse palling time seems to affect most queries, but it is especially clear for queries with many Rel nodes (especially with multiple joins).
In a downstream project, we have a stress test that checks the planning time. In some cases, the planning time is increased by x4 (for a query with 28 joins).
The main contributing factor (but not the only one) for the slow-down could be traced to https://github.com/apache/calcite/pull/2222/files.
As it was mentioned by the reviewers, we may improve the current situation with some tiny changes:
- Introduce a method to check that a Rel node belongs to the RelSubset instead of getting all Rel nodes (the current code may take up to 60% of the planning time).
* Improve the null check in RelMdPredicates by building an error message in RelMdPredicates.ExprsItr only when it is required (may additionally take 10% of the planning time due to SortedMap.toString() being expensive when frequently called).
With these 2 changes, I was able to regain most of the lost planning performance.
The following flame graph clearly shows that the call to RelSubset.getRelList() from VolcanoRuleCall.onMatch() is expensive (28 join query):
After the proposed improvements, the flame graph shows the following (28 join query):
It is clear that the HintStrategyTable.isRuleExcluded() call is expensive, but the overall picture is much better.
Also, in my environment, the TPC-H Q7 test takes ~20% less time (39.6 sec vs 32.9 sec) after the proposed improvements. Here, the flame graph also shows that ordinary queries are also affected by the redundant RelSubset.getRelList() calls: