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Diffstat (limited to 'docs/tuning.md')
| -rw-r--r-- | docs/tuning.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/tuning.md b/docs/tuning.md index 9aaa53cd65..e9b4d6717c 100644 --- a/docs/tuning.md +++ b/docs/tuning.md @@ -213,10 +213,10 @@ but at a high level, managing how frequently full GC takes place can help in red Clusters will not be fully utilized unless you set the level of parallelism for each operation high enough. Spark automatically sets the number of "map" tasks to run on each file according to its size -(though you can control it through optional parameters to `SparkContext.textFile`, etc), but for -distributed "reduce" operations, such as `groupByKey` and `reduceByKey`, it uses a default value of 8. -You can pass the level of parallelism as a second argument (see the -[`spark.PairRDDFunctions`](api/core/index.html#spark.PairRDDFunctions) documentation), +(though you can control it through optional parameters to `SparkContext.textFile`, etc), and for +distributed "reduce" operations, such as `groupByKey` and `reduceByKey`, it uses the largest +parent RDD's number of partitions. You can pass the level of parallelism as a second argument +(see the [`spark.PairRDDFunctions`](api/core/index.html#spark.PairRDDFunctions) documentation), or set the system property `spark.default.parallelism` to change the default. In general, we recommend 2-3 tasks per CPU core in your cluster. |