spark通过合理设置spark.default.parallelism参数提高执行效率_spark.default.parallelism对于direct模式的kafka有效果吗-优快云博客

本文探讨了Spark中的partition概念及其与task的关系，指出默认情况下，如果未设置`spark.default.parallelism`参数，可能会导致大量小任务，从而降低执行效率。在两台8核12GB内存的机器上，作者通过设置该参数将任务数从2.9万个减少到10个，执行时间从分钟级降至20秒。建议将任务与CPU核心数保持在2-3:1的比例，以充分利用集群资源。

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spark中有partition的概念（和slice是同一个概念，在spark1.2中官网已经做出了说明），一般每个partition对应一个task。在我的测试过程中，如果没有设置spark.default.parallelism参数，spark计算出来的partition非常巨大，与我的cores非常不搭。我在两台机器上（8cores *2 +6g * 2）上，spark计算出来的partition达到2.8万个，也就是2.9万个tasks，每个task完成时间都是几毫秒或者零点几毫秒，执行起来非常缓慢。在我尝试设置了 spark.default.parallelism 后，任务数减少到10，执行一次计算过程从minute降到20second。

参数可以通过spark_home/conf/spark-default.conf配置文件设置。

eg.

 spark.master                       spark://master:7077
 spark.default.parallelism          10
 spark.driver.memory                2g
 spark.serializer                   org.apache.spark.serializer.KryoSerializer
 spark.sql.shuffle.partitions       50

Property Name	Default	Meaning
`spark.default.parallelism`	For distributed shuffle operations like `reduceByKey` and `join`, the largest number of partitions in a parent RDD. For operations like`parallelize` with no parent RDDs, it depends on the cluster manager: Local mode: number of cores on the local machine Mesos fine grained mode: 8 Others: total number of cores on all executor nodes or 2, whichever is larger	Default number of partitions in RDDs returned by transformations like `join`, `reduceByKey`, and `parallelize` when not set by user.

from:http://spark.apache.org/docs/latest/tuning.html

Level of Parallelism

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), 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 documentation), or set the config propertyspark.default.parallelism to change the default. In general, we recommend 2-3 tasks per CPU core in your cluster.