[
https://issues.apache.org/jira/browse/CARBONDATA-1445?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ravindra Pesala reassigned CARBONDATA-1445:
-------------------------------------------
Assignee: Ravindra Pesala (was: Ashwini K)
> if 'carbon.update.persist.enable'='false', it will fail to update data
> -----------------------------------------------------------------------
>
> Key: CARBONDATA-1445
> URL: https://issues.apache.org/jira/browse/CARBONDATA-1445
> Project: CarbonData
> Issue Type: Bug
> Components: data-load, spark-integration, sql
> Affects Versions: 1.2.0
> Environment: CarbonData master branch, Spark 2.1.1
> Reporter: Zhichao Zhang
> Assignee: Ravindra Pesala
> Priority: Minor
>
> When updating data, if set 'carbon.update.persist.enable'='false', it will
> fail.
> I debug code and find that in the method LoadTable.processData the
> 'dataFrameWithTupleId' will call udf 'getTupleId()' which is defined in
> CarbonEnv.init(): 'sparkSession.udf.register("getTupleId", () => "")', it
> will return blank string to 'CarbonUpdateUtil.getRequiredFieldFromTID', so
> ArrayIndexOutOfBoundsException occur.
> *the plans (logical and physical) for dataFrameWithTupleId :*
> == Parsed Logical Plan ==
> 'Project [unresolvedalias('stringField3, None), unresolvedalias('intField,
> None), unresolvedalias('longField, None), unresolvedalias('int2Field, None),
> unresolvedalias('stringfield1-updatedColumn, None),
> unresolvedalias('stringfield2-updatedColumn, None), UDF('tupleId) AS
> segId#286]
> +- Project [stringField3#113, intField#114, longField#115L, int2Field#116,
> UDF:getTupleId() AS tupleId#262, concat(stringField1#111, _test) AS
> stringfield1-updatedColumn#263, concat(stringField2#112, _test) AS
> stringfield2-updatedColumn#264]
> +- Filter (isnotnull(stringField3#113) && (stringField3#113 = 1))
> +-
> Relation[stringField1#111,stringField2#112,stringField3#113,intField#114,longField#115L,int2Field#116]
> CarbonDatasourceHadoopRelation [ Database name :default, Table name
> :study_carbondata, Schema
> :Some(StructType(StructField(stringField1,StringType,true),
> StructField(stringField2,StringType,true),
> StructField(stringField3,StringType,true),
> StructField(intField,IntegerType,true), StructField(longField,LongType,true),
> StructField(int2Field,IntegerType,true))) ]
> == Analyzed Logical Plan ==
> stringField3: string, intField: int, longField: bigint, int2Field: int,
> stringfield1-updatedColumn: string, stringfield2-updatedColumn: string,
> segId: string
> Project [stringField3#113, intField#114, longField#115L, int2Field#116,
> stringfield1-updatedColumn#263, stringfield2-updatedColumn#264,
> UDF(tupleId#262) AS segId#286]
> +- Project [stringField3#113, intField#114, longField#115L, int2Field#116,
> UDF:getTupleId() AS tupleId#262, concat(stringField1#111, _test) AS
> stringfield1-updatedColumn#263, concat(stringField2#112, _test) AS
> stringfield2-updatedColumn#264]
> +- Filter (isnotnull(stringField3#113) && (stringField3#113 = 1))
> +-
> Relation[stringField1#111,stringField2#112,stringField3#113,intField#114,longField#115L,int2Field#116]
> CarbonDatasourceHadoopRelation [ Database name :default, Table name
> :study_carbondata, Schema
> :Some(StructType(StructField(stringField1,StringType,true),
> StructField(stringField2,StringType,true),
> StructField(stringField3,StringType,true),
> StructField(intField,IntegerType,true), StructField(longField,LongType,true),
> StructField(int2Field,IntegerType,true))) ]
> == Optimized Logical Plan ==
> CarbonDictionaryCatalystDecoder [CarbonDecoderRelation(Map(int2Field#116 ->
> int2Field#116, longField#115L -> longField#115L, stringField2#112 ->
> stringField2#112, stringField1#111 -> stringField1#111, stringField3#113 ->
> stringField3#113, intField#114 ->
> intField#114),CarbonDatasourceHadoopRelation [ Database name :default, Table
> name :study_carbondata, Schema
> :Some(StructType(StructField(stringField1,StringType,true),
> StructField(stringField2,StringType,true),
> StructField(stringField3,StringType,true),
> StructField(intField,IntegerType,true), StructField(longField,LongType,true),
> StructField(int2Field,IntegerType,true))) ])],
> ExcludeProfile(ArrayBuffer(stringField2#112, stringField1#111)),
> CarbonAliasDecoderRelation(), true
> +- Project [stringField3#113, intField#114, longField#115, int2Field#116,
> concat(stringField1#111, _test) AS stringfield1-updatedColumn#263,
> concat(stringField2#112, _test) AS stringfield2-updatedColumn#264,
> UDF(UDF:getTupleId()) AS segId#286]
> +- Filter (isnotnull(stringField3#113) && (stringField3#113 = 1))
> +-
> Relation[stringField1#111,stringField2#112,stringField3#113,intField#114,longField#115L,int2Field#116]
> CarbonDatasourceHadoopRelation [ Database name :default, Table name
> :study_carbondata, Schema
> :Some(StructType(StructField(stringField1,StringType,true),
> StructField(stringField2,StringType,true),
> StructField(stringField3,StringType,true),
> StructField(intField,IntegerType,true), StructField(longField,LongType,true),
> StructField(int2Field,IntegerType,true))) ]
> == Physical Plan ==
> *CarbonDictionaryDecoder [CarbonDecoderRelation(Map(int2Field#116 ->
> int2Field#116, longField#115L -> longField#115L, stringField2#112 ->
> stringField2#112, stringField1#111 -> stringField1#111, stringField3#113 ->
> stringField3#113, intField#114 ->
> intField#114),CarbonDatasourceHadoopRelation [ Database name :default, Table
> name :study_carbondata, Schema
> :Some(StructType(StructField(stringField1,StringType,true),
> StructField(stringField2,StringType,true),
> StructField(stringField3,StringType,true),
> StructField(intField,IntegerType,true), StructField(longField,LongType,true),
> StructField(int2Field,IntegerType,true))) ])],
> ExcludeProfile(ArrayBuffer(stringField2#112, stringField1#111)),
> CarbonAliasDecoderRelation(), org.apache.spark.sql.CarbonSession@9e4388d
> +- *Project [stringField3#113, intField#114, longField#115, int2Field#116,
> concat(stringField1#111, _test) AS stringfield1-updatedColumn#263,
> concat(stringField2#112, _test) AS stringfield2-updatedColumn#264,
> UDF(UDF:getTupleId()) AS segId#286]
> +- *Scan CarbonDatasourceHadoopRelation [ Database name :default, Table
> name :study_carbondata, Schema
> :Some(StructType(StructField(stringField1,StringType,true),
> StructField(stringField2,StringType,true),
> StructField(stringField3,StringType,true),
> StructField(intField,IntegerType,true), StructField(longField,LongType,true),
> StructField(int2Field,IntegerType,true))) ]
> default.study_carbondata[stringField3#113,intField#114,longField#115,stringField2#112,int2Field#116,stringField1#111]
> PushedFilters: [IsNotNull(stringField3), EqualTo(stringField3,1)]
> *My code:*
> {code:java}
> import spark.implicits._
> val df1 = spark.sparkContext.parallelize(0 to 50)
> .map(x => ("a", x.toString(), (x % 2).toString(), x, x.toLong, x * 2))
> .toDF("stringField1", "stringField2", "stringField3", "intField",
> "longField", "int2Field")
>
> val df2 = spark.sparkContext.parallelize(51 to 100)
> .map(x => ("b", x.toString(), (x % 2).toString(), x, x.toLong, x * 2))
> .toDF("stringField1", "stringField2", "stringField3", "intField",
> "longField", "int2Field")
>
> val df3 = df1.union(df2)
> spark.sql("DROP TABLE IF EXISTS study_carbondata ").show()
> spark.sql("""
> | CREATE TABLE IF NOT EXISTS study_carbondata (
> | stringField1 string,
> | stringField2 string,
> | stringField3 string,
> | intField int,
> | longField bigint,
> | int2Field int
> | )
> | STORED BY 'carbondata'
> | TBLPROPERTIES('DICTIONARY_INCLUDE'='stringField1, stringField2,
> stringField3, longField',
> | 'SORT_COLUMNS'='stringField1, stringField2, stringField3, intField',
> | 'NO_INVERTED_INDEX'='longField',
> | 'TABLE_BLOCKSIZE'='8'
> | )
> """.stripMargin)
> val sortScope = "LOCAL_SORT" //GLOBAL_SORT LOCAL_SORT
> df3.write
> .format("carbondata")
> .option("tableName", "study_carbondata")
> .option("compress", "true") // just valid when tempCSV is true
> .option("tempCSV", "false")
> .option("single_pass", "true")
> .option("sort_scope", sortScope) //GLOBAL_SORT LOCAL_SORT
> .mode(SaveMode.Append)
> .save()
> spark.sql("""
> UPDATE study_carbondata a
> SET (a.stringField1, a.stringField2) = (concat(a.stringField1 ,
> "_test" ), concat(a.stringField2 , "_test" ))
> WHERE a.stringField3 = '1'
> """).show(false)
> {code}
> *Error logs:*
> 2017-09-04 00:39:23,354 - ERROR -
> org.apache.carbondata.common.logging.impl.StandardLogService.logErrorMessage(StandardLogService.java:143)
> - main -main
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 21.0 failed 1 times, most recent failure: Lost task 0.0 in stage 21.0
> (TID 27, localhost, executor driver): org.apache.spark.SparkException: Failed
> to execute user defined function($anonfun$7: (string) => string)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(generated.java:146)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:369)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:369)
> at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:350)
> at scala.collection.Iterator$class.foreach(Iterator.scala:742)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at
> scala.collection.TraversableOnce$class.to(TraversableOnce.scala:308)
> at scala.collection.AbstractIterator.to(Iterator.scala:1194)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:300)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1194)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:287)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1194)
> at
> org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1354)
> at
> org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1354)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1951)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.carbondata.core.mutate.CarbonUpdateUtil.getRequiredFieldFromTID(CarbonUpdateUtil.java:67)
> at
> org.apache.spark.sql.execution.command.LoadTable$$anonfun$7.apply(carbonTableSchema.scala:866)
> at
> org.apache.spark.sql.execution.command.LoadTable$$anonfun$7.apply(carbonTableSchema.scala:865)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(generated.java:144)
> ... 26 more
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> at scala.Option.foreach(Option.scala:257)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951)
> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1354)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
> at org.apache.spark.rdd.RDD.take(RDD.scala:1327)
> at
> org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply$mcZ$sp(RDD.scala:1462)
> at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1462)
> at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1462)
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