beliefer commented on a change in pull request #28096:
[SPARK-31295][DOC][FOLLOWUP] Supplement version for configuration appear in doc
URL: https://github.com/apache/spark/pull/28096#discussion_r402073406
##########
File path: docs/sql-performance-tuning.md
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@@ -230,26 +241,29 @@ AQE converts sort-merge join to broadcast hash join when
the runtime statistics
### Optimizing Skew Join
Data skew can severely downgrade the performance of join queries. This feature
dynamically handles skew in sort-merge join by splitting (and replicating if
needed) skewed tasks into roughly evenly sized tasks. It takes effect when both
`spark.sql.adaptive.enabled` and `spark.sql.adaptive.skewJoin.enabled`
configurations are enabled.
<table class="table">
- <tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr>
+ <tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since
Version</th></tr>
<tr>
<td><code>spark.sql.adaptive.skewJoin.enabled</code></td>
<td>true</td>
<td>
When true and <code>spark.sql.adaptive.enabled</code> is true, Spark
dynamically handles skew in sort-merge join by splitting (and replicating if
needed) skewed partitions.
</td>
+ <td>3.0.0</td>
</tr>
<tr>
<td><code>spark.sql.adaptive.skewJoin.skewedPartitionFactor</code></td>
<td>10</td>
<td>
A partition is considered as skewed if its size is larger than this
factor multiplying the median partition size and also larger than
<code>spark.sql.adaptive.skewedPartitionThresholdInBytes</code>.
</td>
+ <td>3.0.0</td>
Review comment:
SPARK-31037, commit ID:
46b7f1796bd0b96977ce9b473601033f397a3b18#diff-9a6b543db706f1a90f790783d6930a13
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