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Erik LaBianca edited comment on SPARK-18859 at 1/20/17 10:33 PM: ----------------------------------------------------------------- Not quite a repro, but here's explain output. {noformat} val df = spark.read .format("jdbc") .options(DataSources.PostgresOptions + ( "dbtable" -> s"""(select profiles_contact_points.id, remote_id |from profiles_contact_points | left join profiles_contacts_connectors | on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id | where profiles_contact_points.user_id = 1 ) t""".stripMargin )) .load df.printSchema() df.explain(true) df.map(_ != null).count() {noformat} Results in the following. {noformat} df: org.apache.spark.sql.DataFrame = [id: bigint, remote_id: string] root |-- id: long (nullable = false) |-- remote_id: string (nullable = false) == Parsed Logical Plan == Relation[id#2018L,remote_id#2019] JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) == Analyzed Logical Plan == id: bigint, remote_id: string Relation[id#2018L,remote_id#2019] JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) == Optimized Logical Plan == Relation[id#2018L,remote_id#2019] JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) == Physical Plan == *Scan JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) [id#2018L,remote_id#2019] ReadSchema: struct<id:bigint,remote_id:string> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 238.0 failed 4 times, most recent failure: Lost task 0.3 in stage 238.0 (TID 55547, ip-x.ec2.internal): java.lang.NullPointerException at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) 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:370) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1873) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1886) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1899) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1913) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:912) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:358) at org.apache.spark.rdd.RDD.collect(RDD.scala:911) at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:290) at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199) at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2227) at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2226) at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2559) at org.apache.spark.sql.Dataset.count(Dataset.scala:2226) ... 170 elided Caused by: java.lang.NullPointerException at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) 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:370) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) ... 3 more {noformat} was (Author: easel): Not quite a repro, but here's explain output. {noformat} val df = spark.read .format("jdbc") .options(DataSources.PostgresOptions + ( "dbtable" -> s"""(select profiles_contact_points.id, remote_id |from profiles_contact_points | left join profiles_contacts_connectors | on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id | where profiles_contact_points.user_id = 1 ) t""".stripMargin )) .load //.as[ContactRemoteValue] df.printSchema() df.explain(true) df.map(_ != null).count() {noformat} Results in the following. {noformat} df: org.apache.spark.sql.DataFrame = [id: bigint, remote_id: string] root |-- id: long (nullable = false) |-- remote_id: string (nullable = false) == Parsed Logical Plan == Relation[id#2018L,remote_id#2019] JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) == Analyzed Logical Plan == id: bigint, remote_id: string Relation[id#2018L,remote_id#2019] JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) == Optimized Logical Plan == Relation[id#2018L,remote_id#2019] JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) == Physical Plan == *Scan JDBCRelation((select profiles_contact_points.id, remote_id from profiles_contact_points left join profiles_contacts_connectors on profiles_contact_points.contact_id = profiles_contacts_connectors.contact_id where profiles_contact_points.user_id = 1 ) t) [id#2018L,remote_id#2019] ReadSchema: struct<id:bigint,remote_id:string> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 238.0 failed 4 times, most recent failure: Lost task 0.3 in stage 238.0 (TID 55547, ip-x.ec2.internal): java.lang.NullPointerException at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1873) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1886) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1899) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1913) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:912) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:358) at org.apache.spark.rdd.RDD.collect(RDD.scala:911) at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:290) at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2193) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2546) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2192) at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2199) at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2227) at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2226) at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2559) at org.apache.spark.sql.Dataset.count(Dataset.scala:2226) ... 170 elided Caused by: java.lang.NullPointerException at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) ... 3 more {noformat} > Catalyst codegen does not mark column as nullable when it should. Causes NPE > ---------------------------------------------------------------------------- > > Key: SPARK-18859 > URL: https://issues.apache.org/jira/browse/SPARK-18859 > Project: Spark > Issue Type: Bug > Components: Optimizer, SQL > Affects Versions: 2.0.2 > Reporter: Mykhailo Osypov > Priority: Critical > > When joining two tables via LEFT JOIN, columns in right table may be NULLs, > however catalyst codegen cannot recognize it. > Example: > {code:title=schema.sql|borderStyle=solid} > create table masterdata.testtable( > id int not null, > age int > ); > create table masterdata.jointable( > id int not null, > name text not null > ); > {code} > {code:title=query_to_select.sql|borderStyle=solid} > (select t.id, t.age, j.name from masterdata.testtable t left join > masterdata.jointable j on t.id = j.id) as testtable; > {code} > {code:title=master code|borderStyle=solid} > val df = sqlContext > .read > .format("jdbc") > .option("dbTable", "query to select") > .... > .load > //df generated schema > /* > root > |-- id: integer (nullable = false) > |-- age: integer (nullable = true) > |-- name: string (nullable = false) > */ > {code} > {code:title=Codegen|borderStyle=solid} > /* 038 */ scan_rowWriter.write(0, scan_value); > /* 039 */ > /* 040 */ if (scan_isNull1) { > /* 041 */ scan_rowWriter.setNullAt(1); > /* 042 */ } else { > /* 043 */ scan_rowWriter.write(1, scan_value1); > /* 044 */ } > /* 045 */ > /* 046 */ scan_rowWriter.write(2, scan_value2); > {code} > Since *j.name* is from right table of *left join* query, it may be null. > However generated schema doesn't think so (probably because it defined as > *name text not null*) > {code:title=StackTrace|borderStyle=solid} > java.lang.NullPointerException > at > org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter.write(UnsafeRowWriter.java:210) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) > at > org.apache.spark.sql.execution.debug.package$DebugExec$$anonfun$3$$anon$1.hasNext(package.scala:146) > at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1763) > at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1134) > at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1134) > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899) > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:86) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > 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) > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org