Spark 引发 OutOfMemoryError

Question

当我运行我的 spark python 代码时，如下所示：

import pyspark
conf = (pyspark.SparkConf()
     .setMaster("local")
     .setAppName("My app")
     .set("spark.executor.memory", "512m"))
sc = pyspark.SparkContext(conf = conf)        #start the conf
data =sc.textFile('/Users/tsangbosco/Downloads/transactions')
data = data.flatMap(lambda x:x.split()).take(all)

文件大约 20G，我的电脑有 8G 内存，当我在独立模式下运行程序时，它会引发 OutOfMemoryError：

Exception in thread "Local computation of job 12" java.lang.OutOfMemoryError: Java heap space
    at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:131)
    at org.apache.spark.api.python.PythonRDD$$anon$1.next(PythonRDD.scala:119)
    at org.apache.spark.api.python.PythonRDD$$anon$1.next(PythonRDD.scala:112)
    at scala.collection.Iterator$class.foreach(Iterator.scala:727)
    at org.apache.spark.api.python.PythonRDD$$anon$1.foreach(PythonRDD.scala:112)
    at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
    at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
    at org.apache.spark.api.python.PythonRDD$$anon$1.to(PythonRDD.scala:112)
    at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
    at org.apache.spark.api.python.PythonRDD$$anon$1.toBuffer(PythonRDD.scala:112)
    at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
    at org.apache.spark.api.python.PythonRDD$$anon$1.toArray(PythonRDD.scala:112)
    at org.apache.spark.api.java.JavaRDDLike$$anonfun$1.apply(JavaRDDLike.scala:259)
    at org.apache.spark.api.java.JavaRDDLike$$anonfun$1.apply(JavaRDDLike.scala:259)
    at org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:884)
    at org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:884)
    at org.apache.spark.scheduler.DAGScheduler.runLocallyWithinThread(DAGScheduler.scala:681)
    at org.apache.spark.scheduler.DAGScheduler$$anon$1.run(DAGScheduler.scala:666)

spark 无法处理比我的 ram 大的文件吗？你能告诉我怎么修吗？

Answer 1

Spark 可以处理一些情况。但是您正在使用take强制 Spark 将所有数据提取到一个数组（在内存中）。在这种情况下，您应该将它们存储到文件中，例如使用saveAsTextFile.

如果您有兴趣查看某些数据，可以使用sample或takeSample。