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@@ -196,6 +196,10 @@ The following tables list the transformations and actions currently supported (s
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<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> If you are grouping in order to perform an aggregation (such as a sum or
+ average) over each key, using `reduceByKey` or `combineByKey` will yield much better
+ performance.
+<br />
<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.
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