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[SPARK-33019][CORE] Use spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version=1 by default #29895

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[SPARK-33019][CORE] Use spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version=1 by default #29895

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3 changes: 3 additions & 0 deletions core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
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Expand Up @@ -462,6 +462,9 @@ private[spark] object SparkHadoopUtil {
for ((key, value) <- conf.getAll if key.startsWith("spark.hadoop.")) {
hadoopConf.set(key.substring("spark.hadoop.".length), value)
}
if (conf.getOption("spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version").isEmpty) {
hadoopConf.set("mapreduce.fileoutputcommitter.algorithm.version", "1")
}
}

private def appendSparkHiveConfigs(conf: SparkConf, hadoopConf: Configuration): Unit = {
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10 changes: 2 additions & 8 deletions docs/configuration.md
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Expand Up @@ -1761,16 +1761,10 @@ Apart from these, the following properties are also available, and may be useful
</tr>
<tr>
<td><code>spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version</code></td>
<td>Dependent on environment</td>
<td>1</td>
<td>
The file output committer algorithm version, valid algorithm version number: 1 or 2.
Version 2 may have better performance, but version 1 may handle failures better in certain situations,
as per <a href="https://issues.apache.org/jira/browse/MAPREDUCE-4815">MAPREDUCE-4815</a>.
The default value depends on the Hadoop version used in an environment:
1 for Hadoop versions lower than 3.0
2 for Hadoop versions 3.0 and higher
It's important to note that this can change back to 1 again in the future once <a href="https://issues.apache.org/jira/browse/MAPREDUCE-7282">MAPREDUCE-7282</a>
is fixed and merged.
Comment on lines -1767 to -1773
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@yamyamyuo yamyamyuo Sep 29, 2020

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Just curious why this is deleted? It is a very comprehensive comments about the hadoop version background. @dongjoon-hyun

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@dongjoon-hyun dongjoon-hyun Sep 29, 2020

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This PR aims to provide a consistent view for Apache Spark users. For example, The default value depends on the Hadoop version used in an environment is not valid any more. After this PR, Apache Spark users will use v1 consistently by default.

Note that 2 may cause a correctness issue like MAPREDUCE-7282.
</td>
<td>2.2.0</td>
</tr>
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