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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/12/11 09:14:59 UTC
[jira] [Commented] (SPARK-18786) pySpark SQLContext.getOrCreate(sc)
take stopped sparkContext
[ https://issues.apache.org/jira/browse/SPARK-18786?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15739415#comment-15739415 ]
Sean Owen commented on SPARK-18786:
-----------------------------------
I agree it's surprising and maybe fixable, but this may be in the category of things you just shouldn't do. You generally do not stop() a SparkContext except at the end of a program.
> pySpark SQLContext.getOrCreate(sc) take stopped sparkContext
> ------------------------------------------------------------
>
> Key: SPARK-18786
> URL: https://issues.apache.org/jira/browse/SPARK-18786
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.6.0, 2.0.0
> Reporter: Alex Liu
>
> The following steps to reproduce the issue
> {code}
> import sys
> sys.path.insert(1, 'spark/python/')
> sys.path.insert(1, 'spark/python/lib/py4j-0.9-src.zip')
> from pyspark import SparkContext, SQLContext
> sc = SparkContext.getOrCreate()
> sqlContext = SQLContext.getOrCreate(sc)
> sqlContext.read.json(sc.parallelize(['{{ "name": "Adam" }}'])).show()
> sc.stop()
> sc = SparkContext.getOrCreate()
> sqlContext = SQLContext.getOrCreate(sc)
> sqlContext.read.json(sc.parallelize(['{{ "name": "Adam" }}'])).show()
> {code}
> It has the following errors after the last command
> {code}
> >>> sqlContext.read.json(sc.parallelize(['{{ "name": "Adam" }}'])).show()
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "spark/python/pyspark/sql/dataframe.py", line 257, in show
> print(self._jdf.showString(n, truncate))
> File "spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__
> File "spark/python/pyspark/sql/utils.py", line 45, in deco
> return f(*a, **kw)
> File "spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o435.showString.
> : java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext.
> This stopped SparkContext was created at:
> org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
> sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
> java.lang.reflect.Constructor.newInstance(Constructor.java:422)
> py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> py4j.Gateway.invoke(Gateway.java:214)
> py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:79)
> py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
> py4j.GatewayConnection.run(GatewayConnection.java:209)
> java.lang.Thread.run(Thread.java:745)
> The currently active SparkContext was created at:
> org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
> sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
> java.lang.reflect.Constructor.newInstance(Constructor.java:422)
> py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> py4j.Gateway.invoke(Gateway.java:214)
> py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:79)
> py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
> py4j.GatewayConnection.run(GatewayConnection.java:209)
> java.lang.Thread.run(Thread.java:745)
>
> at org.apache.spark.SparkContext.org$apache$spark$SparkContext$$assertNotStopped(SparkContext.scala:106)
> at org.apache.spark.SparkContext.broadcast(SparkContext.scala:1325)
> at org.apache.spark.sql.execution.datasources.DataSourceStrategy$.apply(DataSourceStrategy.scala:126)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner$$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$13.hasNext(Iterator.scala:371)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:349)
> 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$13.hasNext(Iterator.scala:371)
> at org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:47)
> at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:45)
> at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:52)
> at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:52)
> at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2095)
> at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1374)
> at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1456)
> at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:170)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> 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:209)
> at java.lang.Thread.run(Thread.java:745)
> >>> sc.parallelize(['{{ "name": "Adam" }}']).collect()
> ['{{ "name": "Adam" }}']
> {code}
> It doesn't fail in spark-shell.
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