[ https://issues.apache.org/jira/browse/SPARK-13764?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-13764: --------------------------------- Description: Currently, JSON data source just fails to read if some JSON documents are malformed. {{PERMISSIVE}} : sets other fields to {{null}} when it meets a corrupted record and puts the malformed string into a new field configured by {{spark.sql.columnNameOfCorruptRecord}}. When a schema is set by user, it sets {{null}} for extra fields. {{DROPMALFORMED}} : ignores the whole corrupted records. {{FAILFAST}}: throws an exception when it meets corrupted records. was: Currently, JSON data source just fails to read if some JSON documents are malformed. Therefore, if there are two JSON documents below: {noformat} { "request": { "user": { "id": 123 } } } {noformat} {noformat} { "request": { "user": [] } } {noformat} This will fail emitting the exception below : {noformat} Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 in stage 0.0 failed 4 times, most recent failure: Lost task 7.3 in stage 0.0 (TID 10, 192.168.1.170): java.lang.ClassCastException: org.apache.spark.sql.types.GenericArrayData cannot be cast to org.apache.spark.sql.catalyst.InternalRow at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow$class.getStruct(rows.scala:50) at org.apache.spark.sql.catalyst.expressions.GenericMutableRow.getStruct(rows.scala:247) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificPredicate.eval(Unknown Source) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$$anonfun$create$2.apply(GeneratePredicate.scala:67) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$$anonfun$create$2.apply(GeneratePredicate.scala:67) at org.apache.spark.sql.execution.Filter$$anonfun$4$$anonfun$apply$4.apply(basicOperators.scala:117) at org.apache.spark.sql.execution.Filter$$anonfun$4$$anonfun$apply$4.apply(basicOperators.scala:115) at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:390) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1.org$apache$spark$sql$execution$aggregate$TungstenAggregate$$anonfun$$executePartition$1(TungstenAggregate.scala:97) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119) at org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:64) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300) at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300) at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.run(Task.scala:88) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) 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) {noformat} So, just like the parse modes in CSV data source, (See https://github.com/databricks/spark-csv), it would be great if there are some parse modes so that users do not have to filter or pre-process themselves. This happens only when custom schema is set. when this uses inferred schema, then it infers the type as {{StringType}} which reads the data successfully anyway. > Parse modes in JSON data source > ------------------------------- > > Key: SPARK-13764 > URL: https://issues.apache.org/jira/browse/SPARK-13764 > Project: Spark > Issue Type: New Feature > Components: SQL > Affects Versions: 2.0.0 > Reporter: Hyukjin Kwon > Priority: Minor > > Currently, JSON data source just fails to read if some JSON documents are > malformed. > {{PERMISSIVE}} : sets other fields to {{null}} when it meets a corrupted > record and puts the malformed string into a new field configured by > {{spark.sql.columnNameOfCorruptRecord}}. When a schema is set by user, it > sets {{null}} for extra fields. > {{DROPMALFORMED}} : ignores the whole corrupted records. > {{FAILFAST}}: throws an exception when it meets corrupted records. -- 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