我正在尝试将Spark SQL表保存到Parquet文件中。由于other issues，我需要在写入之前减少分区数量。我的代码是
data.coalesce(1000,shuffle=true).saveAsParquetFile("s3n://...")
抛出
java.lang.NullPointerException
at org.apache.spark.SparkContext.getPreferredLocs(SparkContext.scala:927)
at org.apache.spark.rdd.PartitionCoalescer.currPrefLocs(CoalescedRDD.scala:174)
at org.apache.spark.rdd.PartitionCoalescer$LocationIterator$$anonfun$4$$anonfun$apply$2.apply(CoalescedRDD.scala:191)
at org.apache.spark.rdd.PartitionCoalescer$LocationIterator$$anonfun$4$$anonfun$apply$2.apply(CoalescedRDD.scala:190)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:350)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:350)
at org.apache.spark.rdd.PartitionCoalescer$LocationIterator.<init>(CoalescedRDD.scala:185)
at org.apache.spark.rdd.PartitionCoalescer.setupGroups(CoalescedRDD.scala:236)
at org.apache.spark.rdd.PartitionCoalescer.run(CoalescedRDD.scala:337)
at org.apache.spark.rdd.CoalescedRDD.getPartitions(CoalescedRDD.scala:83)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:202)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1128)
at org.apache.spark.sql.parquet.InsertIntoParquetTable.saveAsHadoopFile(ParquetTableOperations.scala:318)
at org.apache.spark.sql.parquet.InsertIntoParquetTable.execute(ParquetTableOperations.scala:246)
at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:409)
at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:409)
at org.apache.spark.sql.SchemaRDDLike$class.saveAsParquetFile(SchemaRDDLike.scala:77)
at org.apache.spark.sql.SchemaRDD.saveAsParquetFile(SchemaRDD.scala:103)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:22)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:27)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:29)
at $iwC$$iwC$$iwC.<init>(<console>:31)
at $iwC$$iwC.<init>(<console>:33)
at $iwC.<init>(<console>:35)
at <init>(<console>:37)
at .<init>(<console>:41)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:789)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1062)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:615)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:646)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:610)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:859)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:771)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:616)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:624)
at org.apache.spark.repl.SparkILoop.loop(SparkILoop.scala:629)
at org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply$mcZ$sp(SparkILoop.scala:954)
at org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:902)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:997)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:328)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
如果我取出合并步骤并更改代码以使用shuffle=true或使用repartition引发相同的错误，则代码可以正常工作。我使用的是spark-1.1.0。