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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2019/04/12 11:21:10 UTC
[GitHub] [spark] deshanxiao commented on a change in pull request #24102:
[SPARK-27171][SQL] Support Full-Partitons scan in limit for the first time
deshanxiao commented on a change in pull request #24102: [SPARK-27171][SQL] Support Full-Partitons scan in limit for the first time
URL: https://github.com/apache/spark/pull/24102#discussion_r274864400
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File path: sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala
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@@ -344,7 +344,7 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ
while (buf.size < n && partsScanned < totalParts) {
// The number of partitions to try in this iteration. It is ok for this number to be
// greater than totalParts because we actually cap it at totalParts in runJob.
- var numPartsToTry = 1L
+ var numPartsToTry = Math.max(Math.ceil(sqlContext.conf.limitStartUpFactor * totalParts).toLong, 1L)
Review comment:
@cloud-fan Sorry for so late reply. I try to execute a very simple query:
```
select * from tst where data='20180410' and name like 'xx' limit 1; (400 partitions)
```
It creates many jobs because "limit" will scan more partitions as the retry increasing (1 -> 4 -> 20 -> 100 -> 200). When I try to add this parameter (0.1). The scan partition from 40 to 200. I think the parameter will increase parallelism to speed up the query. So, different queries may improve performance differently.
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