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https://issues.apache.org/jira/browse/SPARK-36069?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17377968#comment-17377968
]
geekyouth commented on SPARK-36069:
-----------------------------------
here is my unit test output:
org.apache.spark.SparkException: Malformed records are detected in record
parsing. Parse Mode: FAILFAST. To process malformed records as null result, try
setting the option 'mode' as 'PERMISSIVE'.org.apache.spark.SparkException:
Malformed records are detected in record parsing. Parse Mode: FAILFAST. To
process malformed records as null result, try setting the option 'mode' as
'PERMISSIVE'. at
org.apache.spark.sql.catalyst.util.FailureSafeParser.parse(FailureSafeParser.scala:70)
at
org.apache.spark.sql.catalyst.expressions.JsonToStructs.nullSafeEval(jsonExpressions.scala:597)
at
org.apache.spark.sql.catalyst.expressions.UnaryExpression.eval(Expression.scala:461)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.subExpr_0$(Unknown
Source) at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source) at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at
org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:341)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872) at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:313) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at
org.apache.spark.scheduler.Task.run(Task.scala:127) at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.sql.catalyst.util.BadRecordException:
java.lang.RuntimeException: Cannot parse 0.31 as double. at
org.apache.spark.sql.catalyst.json.JacksonParser.parse(JacksonParser.scala:478)
at
org.apache.spark.sql.catalyst.expressions.JsonToStructs.$anonfun$parser$3(jsonExpressions.scala:585)
at
org.apache.spark.sql.catalyst.util.FailureSafeParser.parse(FailureSafeParser.scala:60)
... 20 more
> spark function from_json should output field name, field type and field value
> when FAILFAST mode throw exception
> ----------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-36069
> URL: https://issues.apache.org/jira/browse/SPARK-36069
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: geekyouth
> Priority: Major
>
> spark function from_json outputs error message when FAILFAST mode throw
> exception.
>
> But the message does not contain important info exemaple: field name, field
> vlue , field type...
>
> This infoormation is very important for devlops to find where error input
> data is located.
>
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