[MINOR][DOC] Update the condition description of serialized shuffle #23228
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Test build #99703 has finished for PR 23228 at commit
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Test build #4453 has finished for PR 23228 at commit
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srowen
reviewed
Dec 5, 2018
| @@ -33,10 +33,10 @@ import org.apache.spark.shuffle._ | |||
| * Sort-based shuffle has two different write paths for producing its map output files: | |||
| * | |||
| * - Serialized sorting: used when all three of the following conditions hold: | |||
| * 1. The shuffle dependency specifies no aggregation or output ordering. | |||
| * 1. The shuffle dependency specifies no map-side combine. | |||
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Does this sound right @JoshRosen ?
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looks right to me, according to
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LGTM, cc @jiangxb1987 |
jiangxb1987
approved these changes
Dec 10, 2018
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Please update the title |
10110346
changed the title
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I have updated, thanks all. |
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retest this please |
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Test build #99892 has finished for PR 23228 at commit
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retest this please |
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Test build #99902 has finished for PR 23228 at commit
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thanks, merging to master! |
srowen
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Dec 13, 2018
## What changes were proposed in this pull request? These three condition descriptions should be updated, follow #23228 : <li>no Ordering is specified,</li> <li>no Aggregator is specified, and</li> <li>the number of partitions is less than <code>spark.shuffle.sort.bypassMergeThreshold</code>. </li> 1、If the shuffle dependency specifies aggregation, but it only aggregates at the reduce-side, BypassMergeSortShuffle can still be used. 2、If the number of output partitions is spark.shuffle.sort.bypassMergeThreshold(eg.200), we can use BypassMergeSortShuffle. ## How was this patch tested? N/A Closes #23281 from lcqzte10192193/wid-lcq-1211. Authored-by: lichaoqun <li.chaoqun@zte.com.cn> Signed-off-by: Sean Owen <sean.owen@databricks.com>
holdenk
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Jan 5, 2019
## What changes were proposed in this pull request? These three condition descriptions should be updated, follow apache#23228 : <li>no Ordering is specified,</li> <li>no Aggregator is specified, and</li> <li>the number of partitions is less than <code>spark.shuffle.sort.bypassMergeThreshold</code>. </li> 1、If the shuffle dependency specifies aggregation, but it only aggregates at the reduce-side, BypassMergeSortShuffle can still be used. 2、If the number of output partitions is spark.shuffle.sort.bypassMergeThreshold(eg.200), we can use BypassMergeSortShuffle. ## How was this patch tested? N/A Closes apache#23281 from lcqzte10192193/wid-lcq-1211. Authored-by: lichaoqun <li.chaoqun@zte.com.cn> Signed-off-by: Sean Owen <sean.owen@databricks.com>
jackylee-ch
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Feb 18, 2019
## What changes were proposed in this pull request? `1. The shuffle dependency specifies no aggregation or output ordering.` If the shuffle dependency specifies aggregation, but it only aggregates at the reduce-side, serialized shuffle can still be used. `3. The shuffle produces fewer than 16777216 output partitions.` If the number of output partitions is 16777216 , we can use serialized shuffle. We can see this mothod: `canUseSerializedShuffle` ## How was this patch tested? N/A Closes apache#23228 from 10110346/SerializedShuffle_doc. Authored-by: liuxian <liu.xian3@zte.com.cn> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
jackylee-ch
pushed a commit
to jackylee-ch/spark
that referenced
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Feb 18, 2019
## What changes were proposed in this pull request? These three condition descriptions should be updated, follow apache#23228 : <li>no Ordering is specified,</li> <li>no Aggregator is specified, and</li> <li>the number of partitions is less than <code>spark.shuffle.sort.bypassMergeThreshold</code>. </li> 1、If the shuffle dependency specifies aggregation, but it only aggregates at the reduce-side, BypassMergeSortShuffle can still be used. 2、If the number of output partitions is spark.shuffle.sort.bypassMergeThreshold(eg.200), we can use BypassMergeSortShuffle. ## How was this patch tested? N/A Closes apache#23281 from lcqzte10192193/wid-lcq-1211. Authored-by: lichaoqun <li.chaoqun@zte.com.cn> Signed-off-by: Sean Owen <sean.owen@databricks.com>
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What changes were proposed in this pull request?
1. The shuffle dependency specifies no aggregation or output ordering.If the shuffle dependency specifies aggregation, but it only aggregates at the reduce-side, serialized shuffle can still be used.
3. The shuffle produces fewer than 16777216 output partitions.If the number of output partitions is 16777216 , we can use serialized shuffle.
We can see this mothod:
canUseSerializedShuffleHow was this patch tested?
N/A