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Posted to reviews@spark.apache.org by wangyum <gi...@git.apache.org> on 2018/11/12 12:24:48 UTC
[GitHub] spark pull request #23014: [MINOR][SQL] Add disable bucketedRead workaround ...
GitHub user wangyum opened a pull request:
https://github.com/apache/spark/pull/23014
[MINOR][SQL] Add disable bucketedRead workaround when throw RuntimeException
## What changes were proposed in this pull request?
It will throw `RuntimeException` when read from bucketed table(about 1.7G per bucket file):
Default(enable bucket read):
Disable bucket read:
## How was this patch tested?
manual tests
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/wangyum/spark anotherWorkaround
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/23014.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #23014
----
commit a41551efd667f3ed6c30b0a2b262818e37d00884
Author: Yuming Wang <yu...@...>
Date: 2018-11-12T12:06:35Z
Add new workaround
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[GitHub] spark issue #23014: [MINOR][SQL] Add disable bucketedRead workaround when th...
Posted by wangyum <gi...@git.apache.org>.
Github user wangyum commented on the issue:
https://github.com/apache/spark/pull/23014
retest this please
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Github user wangyum commented on the issue:
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retest this please
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* This patch **fails due to an unknown error code, -9**.
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[GitHub] spark pull request #23014: [MINOR][SQL] Add disable bucketedRead workaround ...
Posted by HyukjinKwon <gi...@git.apache.org>.
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/23014#discussion_r232893546
--- Diff: sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/WritableColumnVector.java ---
@@ -101,10 +101,11 @@ private void throwUnsupportedException(int requiredCapacity, Throwable cause) {
String message = "Cannot reserve additional contiguous bytes in the vectorized reader (" +
(requiredCapacity >= 0 ? "requested " + requiredCapacity + " bytes" : "integer overflow") +
"). As a workaround, you can reduce the vectorized reader batch size, or disable the " +
- "vectorized reader. For parquet file format, refer to " +
+ "vectorized reader, or disable " + SQLConf.BUCKETING_ENABLED().key() + " if you read " +
+ "from bucket table. For Parquet file format, refer to " +
SQLConf.PARQUET_VECTORIZED_READER_BATCH_SIZE().key() +
" (default " + SQLConf.PARQUET_VECTORIZED_READER_BATCH_SIZE().defaultValueString() +
- ") and " + SQLConf.PARQUET_VECTORIZED_READER_ENABLED().key() + "; for orc file format, " +
+ ") and " + SQLConf.PARQUET_VECTORIZED_READER_ENABLED().key() + "; for Orc file format, " +
--- End diff --
`Orc` is `ORC` BTW :-).
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[GitHub] spark pull request #23014: [MINOR][SQL] Add disable bucketedRead workaround ...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
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[GitHub] spark issue #23014: [MINOR][SQL] Add disable bucketedRead workaround when th...
Posted by HyukjinKwon <gi...@git.apache.org>.
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/23014
> The reason is that each bucket file is too big
Can you elaborate please? Is it because we don't chunk each file into multiple splits when we read bucketed table?
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[GitHub] spark pull request #23014: [MINOR][SQL] Add disable bucketedRead workaround ...
Posted by HyukjinKwon <gi...@git.apache.org>.
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/23014#discussion_r232885260
--- Diff: sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/WritableColumnVector.java ---
@@ -101,7 +101,8 @@ private void throwUnsupportedException(int requiredCapacity, Throwable cause) {
String message = "Cannot reserve additional contiguous bytes in the vectorized reader (" +
(requiredCapacity >= 0 ? "requested " + requiredCapacity + " bytes" : "integer overflow") +
"). As a workaround, you can reduce the vectorized reader batch size, or disable the " +
- "vectorized reader. For parquet file format, refer to " +
+ "vectorized reader, or disable " + SQLConf.BUCKETING_ENABLED().key() + " if you read " +
+ "from bucket table. For parquet file format, refer to " +
--- End diff --
parquet -> Parquet
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[GitHub] spark issue #23014: [MINOR][SQL] Add disable bucketedRead workaround when th...
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[GitHub] spark issue #23014: [MINOR][SQL] Add disable bucketedRead workaround when th...
Posted by wangyum <gi...@git.apache.org>.
Github user wangyum commented on the issue:
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Yes. The `filePartitions` are the same as the bucket number when `BucketedRead`:
https://github.com/apache/spark/blob/ab5752cb952e6536a68a988289e57100fdbba142/sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala#L382-L414
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