[
https://issues.apache.org/jira/browse/SPARK-8071?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Weizhong updated SPARK-8071:
----------------------------
Environment:
OS: SUSE 11 SP3; JDK: 1.8.0_40; Python: 2.6.8; Hadoop: 2.7.0; Spark: master
branch
was:
OS: SUSE 11 SP3
JDK: 1.8.0_40
Python: 2.6.8
Hadoop: 2.7.0
Spark: master branch
> Run PySpark dataframe.rollup/cube test failed
> ---------------------------------------------
>
> Key: SPARK-8071
> URL: https://issues.apache.org/jira/browse/SPARK-8071
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Environment: OS: SUSE 11 SP3; JDK: 1.8.0_40; Python: 2.6.8; Hadoop:
> 2.7.0; Spark: master branch
> Reporter: Weizhong
> Priority: Minor
>
> I run test for Spark, and failed on PySpark, details are:
> File "/xxx/Spark/python/pyspark/sql/dataframe.py", line 837, in
> pyspark.sql.dataframe.DataFrame.cube
> Failed example:
> df.cube('name', df.age).count().show()
> Exception raised:
> Traceback (most recent call last):
> File "/usr/lib64/python2.6/doctest.py", line 1253, in __run
> compileflags, 1) in test.globs
> File "<doctest pyspark.sql.dataframe.DataFrame.cube[0]>", line 1, in
> <module>
> df.cube('name', df.age).count().show()
> File "/xxx/Spark/python/pyspark/sql/dataframe.py", line 291, in show
> print(self._jdf.showString(n))
> File "/xxx/Spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
> line 538, in __call__
> self.target_id, self.name)
> File "/xxx/Spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py",
> line 300, in get_return_value
> format(target_id, '.', name), value)
> Py4JJavaError: An error occurred while calling o212.showString.
> : java.lang.AssertionError: assertion failed: No plan for Cube
> [name#1,age#0], [name#1,age#0,COUNT(1) AS count#27L], grouping__id#28
> LogicalRDD [age#0,name#1], MapPartitionsRDD[7] at applySchemaToPythonRDD
> at NativeMethodAccessorImpl.java:-2
> at scala.Predef$.assert(Predef.scala:179)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:312)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:913)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:911)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:917)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:917)
> at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1255)
> at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1189)
> at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1248)
> at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:176)
> 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)
> **********************************************************************
> File "/xxx/Spark/python/pyspark/sql/dataframe.py", line 816, in
> pyspark.sql.dataframe.DataFrame.rollup
> Failed example:
> df.rollup('name', df.age).count().show()
> Exception raised:
> Traceback (most recent call last):
> File "/usr/lib64/python2.6/doctest.py", line 1253, in __run
> compileflags, 1) in test.globs
> File "<doctest pyspark.sql.dataframe.DataFrame.rollup[0]>", line
> 1,SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
> SLF4J: Defaulting to no-operation (NOP) logger implementation
> SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further
> details.
> in <module>
> df.rollup('name', df.age).count().show()
> File "/xxx/Spark/python/pyspark/sql/dataframe.py", line 291, in show
> print(self._jdf.showString(n))
> File "/xxx/Spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
> line 538, in __call__
> self.target_id, self.name)
> File "/xxx/Spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py",
> line 300, in get_return_value
> format(target_id, '.', name), value)
> Py4JJavaError: An error occurred while calling o486.showString.
> : java.lang.AssertionError: assertion failed: No plan for Rollup
> [name#1,age#0], [name#1,age#0,COUNT(1) AS count#168L], grouping__id#169
> LogicalRDD [age#0,name#1], MapPartitionsRDD[7] at applySchemaToPythonRDD
> at NativeMethodAccessorImpl.java:-2
> at scala.Predef$.assert(Predef.scala:179)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:312)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:913)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:911)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:917)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:917)
> at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1255)
> at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1189)
> at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1248)
> at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:176)
> 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)
> **********************************************************************
> 1 of 1 in pyspark.sql.dataframe.DataFrame.cube
> 1 of 1 in pyspark.sql.dataframe.DataFrame.rollup
> ***Test Failed*** 2 failures.
> This problem
> http://stackoverflow.com/questions/29565923/cache-methods-not-working-in-spark-1-3-0
> is similar.
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