update big data error

[yixu2001]

dev
 
V_ORDER_ITEM_PROC_ATTR_CARBON3 （primary key ID） amount of data 7 Billion
 update_order_item3 （primary key ID）  amount of data 100Million

 spark1.6 carbon 1.1 run sql
  cc.sql("update e_carbon.V_ORDER_ITEM_PROC_ATTR_CARBON5
   A  set (a.ORDER_ITEM_ID, a.CLASS_ID )
    =(SELECT b.ORDER_ITEM_ID, b.CLASS_ID
     from e_carbon.update_order_item3 b
     where b.ID=A.ID)").show
       
Error message
17/05/22 16:14:33 AUDIT deleteExecution$: [HETL032][e_carbon][Thread-1]Delete data operation is failed for e_carbon.v_order_item_proc_attr_carbon5
17/05/22 16:14:33 ERROR deleteExecution$: main Delete data operation is failed due to failure in creating delete delta file for segment : null block : null
17/05/22 16:14:33 ERROR ProjectForUpdateCommand$: main Exception in update operationjava.lang.Exception: Multiple input rows matched for same row.
17/05/22 16:14:33 INFO MapPartitionsRDD: Removing RDD 21 from persistence list
17/05/22 16:14:33 INFO BlockManager: Removing RDD 21
17/05/22 16:14:33 INFO HdfsFileLock: main Deleted the lock file hdfs://ns1/user/e_carbon/private/carbon.store/e_carbon/v_order_item_proc_attr_carbon5/meta.lock
17/05/22 16:14:33 INFO CarbonLockUtil: main Metadata lock has been successfully released
java.lang.RuntimeException: Update operation failed. Multiple input rows matched for same row.
at scala.sys.package$.error(package.scala:27)
at org.apache.spark.sql.execution.command.ProjectForUpdateCommand.run(IUDCommands.scala:236)
at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
at org.apache.spark.sql.execution.ExecutedCommand.executeTake(commands.scala:67)
at org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:174)
at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1538)
at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1538)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
at org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:2125)
at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$execute$1(DataFrame.scala:1537)
at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$collect(DataFrame.scala:1544)
at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1414)
at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1413)
at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2138)
at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1413)
at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1495)
at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:171)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:394)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:355)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:363)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:31)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:36)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:38)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:40)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:42)
at $iwC$$iwC$$iwC.<init>(<console>:44)
at $iwC$$iwC.<init>(<console>:46)
at $iwC.<init>(<console>:48)
at <init>(<console>:50)
at .<init>(<console>:54)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.a
 



yixu2001

[ravikiran23]

HI,
      As i can see in the exception "Multiple input rows matched for same row.". In update there should be one to one mapping for the destination and source tables data on which we are doing join. in your case i feel the data of a.id and b.id contains duplicates. That's why update has failed  in your scenario.


Regards,
Ravikiran S N