chenminghua8 opened a new pull request, #38381:
URL: https://github.com/apache/spark/pull/38381
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### What changes were proposed in this pull request?
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This RP modifies the "computeStats" method of the "LogicalRelation" class:
when the external table does not perform pre-analysis to generate statistics,
it calculates the space size of the HDFS file corresponding to the table as the
return value and uses this value to update the external table Statistics's
sizeInBytes value for lazy calculation of external table statistics. This
solves the problem that Row-level Runtime Filtering cannot be applied when the
external table does not have pre-performed analysis to generate statistics.
### Why are the changes needed?
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When using external tables, Row-level Runtime Filtering cannot be applied
without pre-performing analysis on the table to generate statistics. In actual
use, external tables usually do not have pre-executed analysis to generate
statistics, but it is also hoped that Row-level Runtime Filtering can be used
to improve execution efficiency. The reason why Row-level Runtime Filtering
cannot be enabled is that the "InjectRuntimeFilter" class calls the
"satisfyByteSizeRequirement" method to determine whether the Bloom filter
application side plan's aggregated scan size meets the requirements, and this
value is finally calculated by the "computeStats" method of the
"LogicalRelation" class. The current implementation of the 'computeStats'
method first determines whether there is statistics in the external table, and
if not, returns the value of 'spark.sql.defaultSizeInBytes', which results in
that the calculated value returned when no pre-analysis is performed on the
table to generate stat
istics cannot be satisfied Requirements for applying Row-level Runtime
Filtering.
### Does this PR introduce _any_ user-facing change?
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No
### How was this patch tested?
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New unit tests.
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