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authorChen Chao <crazyjvm@gmail.com>2014-04-16 17:58:42 -0700
committerReynold Xin <rxin@apache.org>2014-04-16 17:58:42 -0700
commit9c40b9ead0d17ad836b3507c701198645c33d878 (patch)
treee1ead9ad23fe2bdfb15a45780ee70bd5ecc34860 /docs/scala-programming-guide.md
parent38877ccf394a50bfd37c8433d4aafaa91683d3b8 (diff)
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misleading task number of groupByKey
"By default, this uses only 8 parallel tasks to do the grouping." is a big misleading. Please refer to https://github.com/apache/spark/pull/389 detail is as following code : def defaultPartitioner(rdd: RDD[_], others: RDD[_]*): Partitioner = { val bySize = (Seq(rdd) ++ others).sortBy(_.partitions.size).reverse for (r <- bySize if r.partitioner.isDefined) { return r.partitioner.get } if (rdd.context.conf.contains("spark.default.parallelism")) { new HashPartitioner(rdd.context.defaultParallelism) } else { new HashPartitioner(bySize.head.partitions.size) } } Author: Chen Chao <crazyjvm@gmail.com> Closes #403 from CrazyJvm/patch-4 and squashes the following commits: 42f6c9e [Chen Chao] fix format 829a995 [Chen Chao] fix format 1568336 [Chen Chao] misleading task number of groupByKey
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@@ -189,8 +189,8 @@ The following tables list the transformations and actions currently supported (s
<tr>
<td> <b>groupByKey</b>([<i>numTasks</i>]) </td>
<td> When called on a dataset of (K, V) pairs, returns a dataset of (K, Seq[V]) pairs. <br />
-<b>Note:</b> By default, this uses only 8 parallel tasks to do the grouping. You can pass an optional <code>numTasks</code> argument to set a different number of tasks.
-</td>
+<b>Note:</b> By default, if the RDD already has a partitioner, the task number is decided by the partition number of the partitioner, or else relies on the value of <code>spark.default.parallelism</code> if the property is set , otherwise depends on the partition number of the RDD. You can pass an optional <code>numTasks</code> argument to set a different number of tasks.
+ </td>
</tr>
<tr>
<td> <b>reduceByKey</b>(<i>func</i>, [<i>numTasks</i>]) </td>