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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2017/01/12 01:58:17 UTC
[jira] [Resolved] (SPARK-11428) Schema Merging Broken for Some
Queries
[ https://issues.apache.org/jira/browse/SPARK-11428?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-11428.
----------------------------------
Resolution: Duplicate
I am pretty sure that it is a duplicate of SPARK-11103. Please reopen this if anyone meets the same issue.
> Schema Merging Broken for Some Queries
> --------------------------------------
>
> Key: SPARK-11428
> URL: https://issues.apache.org/jira/browse/SPARK-11428
> Project: Spark
> Issue Type: Bug
> Components: PySpark, Spark Core
> Affects Versions: 1.5.1
> Environment: AWS,
> Reporter: Brad Willard
> Labels: dataframe, parquet, pyspark, schema, sparksql
>
> I have data being written into parquet format via spark streaming. The data can change slightly so schema merging is required. I load a dataframe like this
> {code}
> urls = [
> "/streaming/parquet/events/key=2015-10-30*",
> "/streaming/parquet/events/key=2015-10-29*"
> ]
> sdf = sql_context.read.option("mergeSchema", "true").parquet(*urls)
> sdf.registerTempTable('events')
> {code}
> If I print the schema you can see the contested column
> {code}
> sdf.printSchema()
> root
> |-- _id: string (nullable = true)
> ...
> |-- d__device_s: string (nullable = true)
> |-- d__isActualPageLoad_s: string (nullable = true)
> |-- d__landing_s: string (nullable = true)
> |-- d__lang_s: string (nullable = true)
> |-- d__os_s: string (nullable = true)
> |-- d__performance_i: long (nullable = true)
> |-- d__product_s: string (nullable = true)
> |-- d__refer_s: string (nullable = true)
> |-- d__rk_i: long (nullable = true)
> |-- d__screen_s: string (nullable = true)
> |-- d__submenuName_s: string (nullable = true)
> {code}
> The column that's in one but not the other file is d__product_s
> So I'm able to run this query and it works fine.
> {code}
> sql_context.sql('''
> select
> distinct(d__product_s)
> from
> events
> where
> n = 'view'
> ''').collect()
> [Row(d__product_s=u'website'),
> Row(d__product_s=u'store'),
> Row(d__product_s=None),
> Row(d__product_s=u'page')]
> {code}
> However if I instead use that column in the where clause things break.
> {code}
> sql_context.sql('''
> select
> *
> from
> events
> where
> n = 'view' and d__product_s = 'page'
> ''').take(1)
> ---------------------------------------------------------------------------
> Py4JJavaError Traceback (most recent call last)
> <ipython-input-15-04698b649759> in <module>()
> 6 where
> 7 n = 'frontsite_view' and d__product_s = 'page'
> ----> 8 ''').take(1)
> /root/spark/python/pyspark/sql/dataframe.pyc in take(self, num)
> 303 with SCCallSiteSync(self._sc) as css:
> 304 port = self._sc._jvm.org.apache.spark.sql.execution.EvaluatePython.takeAndServe(
> --> 305 self._jdf, num)
> 306 return list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
> 307
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in __call__(self, *args)
> 536 answer = self.gateway_client.send_command(command)
> 537 return_value = get_return_value(answer, self.gateway_client,
> --> 538 self.target_id, self.name)
> 539
> 540 for temp_arg in temp_args:
> /root/spark/python/pyspark/sql/utils.pyc in deco(*a, **kw)
> 34 def deco(*a, **kw):
> 35 try:
> ---> 36 return f(*a, **kw)
> 37 except py4j.protocol.Py4JJavaError as e:
> 38 s = e.java_exception.toString()
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
> 298 raise Py4JJavaError(
> 299 'An error occurred while calling {0}{1}{2}.\n'.
> --> 300 format(target_id, '.', name), value)
> 301 else:
> 302 raise Py4JError(
> Py4JJavaError: An error occurred while calling z:org.apache.spark.sql.execution.EvaluatePython.takeAndServe.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed 30 times, most recent failure: Lost task 0.29 in stage 15.0 (TID 6536, 10.X.X.X): java.lang.IllegalArgumentException: Column [d__product_s] was not found in schema!
> at org.apache.parquet.Preconditions.checkArgument(Preconditions.java:55)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.getColumnDescriptor(SchemaCompatibilityValidator.java:190)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumn(SchemaCompatibilityValidator.java:178)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumnFilterPredicate(SchemaCompatibilityValidator.java:160)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:94)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:59)
> at org.apache.parquet.filter2.predicate.Operators$Eq.accept(Operators.java:180)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:131)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:59)
> at org.apache.parquet.filter2.predicate.Operators$And.accept(Operators.java:308)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validate(SchemaCompatibilityValidator.java:64)
> at org.apache.parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:59)
> at org.apache.parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:40)
> at org.apache.parquet.filter2.compat.FilterCompat$FilterPredicateCompat.accept(FilterCompat.java:126)
> at org.apache.parquet.filter2.compat.RowGroupFilter.filterRowGroups(RowGroupFilter.java:46)
> at org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:160)
> at org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:140)
> at org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.<init>(SqlNewHadoopRDD.scala:155)
> at org.apache.spark.rdd.SqlNewHadoopRDD.compute(SqlNewHadoopRDD.scala:120)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:87)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
> at scala.Option.foreach(Option.scala:236)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1822)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1835)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1848)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:215)
> at org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:207)
> at org.apache.spark.sql.DataFrame$$anonfun$collect$1.apply(DataFrame.scala:1385)
> at org.apache.spark.sql.DataFrame$$anonfun$collect$1.apply(DataFrame.scala:1385)
> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
> at org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:1903)
> at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1384)
> at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1314)
> at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1377)
> at org.apache.spark.sql.execution.EvaluatePython$.takeAndServe(python.scala:127)
> at org.apache.spark.sql.execution.EvaluatePython.takeAndServe(python.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
> at py4j.Gateway.invoke(Gateway.java:259)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:207)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.IllegalArgumentException: Column [d__product_s] was not found in schema!
> at org.apache.parquet.Preconditions.checkArgument(Preconditions.java:55)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.getColumnDescriptor(SchemaCompatibilityValidator.java:190)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumn(SchemaCompatibilityValidator.java:178)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumnFilterPredicate(SchemaCompatibilityValidator.java:160)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:94)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:59)
> at org.apache.parquet.filter2.predicate.Operators$Eq.accept(Operators.java:180)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:131)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:59)
> at org.apache.parquet.filter2.predicate.Operators$And.accept(Operators.java:308)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validate(SchemaCompatibilityValidator.java:64)
> at org.apache.parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:59)
> at org.apache.parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:40)
> at org.apache.parquet.filter2.compat.FilterCompat$FilterPredicateCompat.accept(FilterCompat.java:126)
> at org.apache.parquet.filter2.compat.RowGroupFilter.filterRowGroups(RowGroupFilter.java:46)
> at org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:160)
> at org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:140)
> at org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.<init>(SqlNewHadoopRDD.scala:155)
> at org.apache.spark.rdd.SqlNewHadoopRDD.compute(SqlNewHadoopRDD.scala:120)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:87)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> ... 1 more
> {code}
> I get the same error also when attempting to write the same query with the dataframe api as well.
> {code}
> sdf.where(sdf.d__product_s == 'page').take(1)
> {code}
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