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Apache Spark簡單連接導致神秘錯誤

[英]Apache Spark simple join results in cryptic error

 原文  2018-10-08 23:27:11  6   2    java/ apache-spark/ cassandra

問題描述

我有兩個數據集，可以分別查詢和顯示（）。 一個擁有17條記錄，另一個擁有3條記錄。 

Dataset<Row> attReader = spark
    .read()
    .format("org.apache.spark.sql.cassandra")
    .option("table", "table_1")
    .load();

Dataset<Row> surReader = spark
    .read()
    .format("org.apache.spark.sql.cassandra")
    .option("table", "table_2")
    .load();

當我嘗試加入並顯示給他們時： 

    Dataset<Row> joined = attReader.join(surReader,
        attReader.col("key_field").equalTo(surReader.col("key_field")), "inner");
    joined.show();

我確定這些字段是正確的，因為我可以顯示各個數據集的數據並查看它們。 連接字段是字符串。

我收到以下異常，但沒有太多幫助： 

org.apache.spark.SparkException: Exception thrown in awaitResult: 
    at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
    at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecuteBroadcast(BroadcastExchangeExec.scala:136)
    at org.apache.spark.sql.execution.InputAdapter.doExecuteBroadcast(WholeStageCodegenExec.scala:367)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeBroadcast$1.apply(SparkPlan.scala:144)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeBroadcast$1.apply(SparkPlan.scala:140)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.executeBroadcast(SparkPlan.scala:140)
    at org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.prepareBroadcast(BroadcastHashJoinExec.scala:135)
    at org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.codegenInner(BroadcastHashJoinExec.scala:232)
    at org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.doConsume(BroadcastHashJoinExec.scala:102)
    at org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:181)
    at org.apache.spark.sql.execution.FilterExec.consume(basicPhysicalOperators.scala:85)
    at org.apache.spark.sql.execution.FilterExec.doConsume(basicPhysicalOperators.scala:206)
    at org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:181)
    at org.apache.spark.sql.execution.RowDataSourceScanExec.consume(DataSourceScanExec.scala:77)
    at org.apache.spark.sql.execution.RowDataSourceScanExec.doProduce(DataSourceScanExec.scala:125)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.RowDataSourceScanExec.produce(DataSourceScanExec.scala:77)
    at org.apache.spark.sql.execution.FilterExec.doProduce(basicPhysicalOperators.scala:125)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.FilterExec.produce(basicPhysicalOperators.scala:85)
    at org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.doProduce(BroadcastHashJoinExec.scala:97)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.produce(BroadcastHashJoinExec.scala:39)
    at org.apache.spark.sql.execution.ProjectExec.doProduce(basicPhysicalOperators.scala:45)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
    at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
    at org.apache.spark.sql.execution.ProjectExec.produce(basicPhysicalOperators.scala:35)
    at org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:524)
    at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:576)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:337)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3278)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2489)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2489)
    at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3259)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3258)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2489)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2703)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
    at org.apache.spark.sql.Dataset.show(Dataset.scala:723)
    at org.apache.spark.sql.Dataset.show(Dataset.scala:682)
    at org.apache.spark.sql.Dataset.show(Dataset.scala:691)
    at com.kilonova.CassandraStream.sparkSql(CassandraStream.java:111)
    at com.kilonova.CassandraStream.init(CassandraStream.java:174)
    at com.kilonova.Main.runStream(Main.java:20)
    at com.kilonova.Main.main(Main.java:14)
Caused by: java.lang.IllegalArgumentException
    at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
    at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
    at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
    at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
    at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
    at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
    at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
    at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
    at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
    at scala.collection.mutable.HashMap$$anon$1.foreach(HashMap.scala:103)
    at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
    at org.apache.spark.util.FieldAccessFinder$$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
    at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
    at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:262)
    at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:261)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:261)
    at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
    at org.apache.spark.SparkContext.clean(SparkContext.scala:2299)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2073)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
    at org.apache.spark.sql.execution.SparkPlan.executeCollectIterator(SparkPlan.scala:304)
    at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:76)
    at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1$$anonfun$apply$1.apply(BroadcastExchangeExec.scala:73)
    at org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:97)
    at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72)
    at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec$$anonfun$relationFuture$1.apply(BroadcastExchangeExec.scala:72)
    at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
    at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
    at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1135)
    at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
    at java.base/java.lang.Thread.run(Thread.java:844)

2 個解決方案

解決方案1
 1  2018-10-09 02:33:11

如果Spark的大小小於spark.sql.autoBroadcastJoinThreshold指定的值，則Spark嘗試廣播該聯接中的較小表之一。 默認情況下，此屬性設置為10 MB。

出現此錯誤的原因之一是由於廣播超時。 此屬性由spark.sql.broadcastTimeout控制，默認情況下設置為300秒。

要解決您的問題，您可以執行以下任一操作

  1. 通過將spark.sql.autoBroadcastJoinThreshold設置為-1來禁用廣播。 但這可能會影響查詢性能。
  2. 如果要廣播表，請增加超時值。

我已經看到了Spark沒有表統計信息的情況，它可能會嘗試廣播聯接中兩個表中較大的一個。 這會降低性能。 您可以通過獲取查詢計划並找出要廣播的表來確定此問題。 

dataframe.queryExecution.sparkPlan

如果發現spark正在廣播更大的表，則應該計算該表的統計信息，以實現更好的查詢優化。 您可以采用以下方式之一：

  1. 通過Spark運行analytics table命令。 如果您使用與Spark相同的metastore運行Hive / Impala服務，則可以通過Hive運行Analyze表或通過Impala運行Compute Statistics。

  2. 您可以在對該表進行聯接之前對其進行緩存。 這樣，Spark可以即時計算表格的統計信息。

有關分析表統計信息的更多參考：

讓我知道它是否對您有幫助。

解決方案2
 1 已采納  2018-10-09 22:46:41

這可能是由於JDK版本引起的。 您可能未使用JDK 8。

請檢查該線程以獲取更多信息。

該線程可能會有所幫助。 org.apache.xbean.asm5.ClassReader上的Spark Java IllegalArgumentException

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