ARROW-11088: [Rust][DataFusion] Calculate column indices upfront in hash join #9059
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Codecov Report
@@ Coverage Diff @@
## master #9059 +/- ##
==========================================
- Coverage 82.55% 82.55% -0.01%
==========================================
Files 203 203
Lines 50043 50054 +11
==========================================
+ Hits 41313 41322 +9
- Misses 8730 8732 +2
Continue to review full report at Codecov.
|
Contributor
Author
|
Fixed the linting error in #9061 |
kou
changed the title
Dandandan
force-pushed
the
join_columns
branch
from
2690d88 to
45fa819
Compare
Contributor
Author
|
Can be combined in #9070 to reduce nr. of open PRs |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
As mentioned in #9048 it is wasteful to calculate the column indexes for every batch. In this PR we instead do it only once.
This doesn't seem to have a large impact on performance, as expected, but seems to give a small improvement when using smaller batch sizes.