[
https://issues.apache.org/jira/browse/SPARK-12110?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15036960#comment-15036960
]
Patrick Wendell commented on SPARK-12110:
-----------------------------------------
Hey Andrew, could you show exactly the command you are running to run this
example? Also, if you simply download Spark 1.5.1 and run the same command
locally rather than in your modified EC2 cluster, does it work?
> spark-1.5.1-bin-hadoop2.6; pyspark.ml.feature Exception: ("You must build
> Spark with Hive
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-12110
> URL: https://issues.apache.org/jira/browse/SPARK-12110
> Project: Spark
> Issue Type: Bug
> Components: EC2
> Affects Versions: 1.5.1
> Environment: cluster created using
> spark-1.5.1-bin-hadoop2.6/ec2/spark-ec2
> Reporter: Andrew Davidson
>
> I am using spark-1.5.1-bin-hadoop2.6. I used
> spark-1.5.1-bin-hadoop2.6/ec2/spark-ec2 to create a cluster and configured
> spark-env to use python3. I can not run the tokenizer sample code. Is there a
> work around?
> Kind regards
> Andy
> {code}
> /root/spark/python/pyspark/sql/context.py in _ssql_ctx(self)
> 658 raise Exception("You must build Spark with Hive. "
> 659 "Export 'SPARK_HIVE=true' and run "
> --> 660 "build/sbt assembly", e)
> 661
> 662 def _get_hive_ctx(self):
> Exception: ("You must build Spark with Hive. Export 'SPARK_HIVE=true' and run
> build/sbt assembly", Py4JJavaError('An error occurred while calling
> None.org.apache.spark.sql.hive.HiveContext.\n', JavaObject id=o38))
> http://spark.apache.org/docs/latest/ml-features.html#tokenizer
> from pyspark.ml.feature import Tokenizer, RegexTokenizer
> sentenceDataFrame = sqlContext.createDataFrame([
> (0, "Hi I heard about Spark"),
> (1, "I wish Java could use case classes"),
> (2, "Logistic,regression,models,are,neat")
> ], ["label", "sentence"])
> tokenizer = Tokenizer(inputCol="sentence", outputCol="words")
> wordsDataFrame = tokenizer.transform(sentenceDataFrame)
> for words_label in wordsDataFrame.select("words", "label").take(3):
> print(words_label)
> ---------------------------------------------------------------------------
> Py4JJavaError Traceback (most recent call last)
> /root/spark/python/pyspark/sql/context.py in _ssql_ctx(self)
> 654 if not hasattr(self, '_scala_HiveContext'):
> --> 655 self._scala_HiveContext = self._get_hive_ctx()
> 656 return self._scala_HiveContext
> /root/spark/python/pyspark/sql/context.py in _get_hive_ctx(self)
> 662 def _get_hive_ctx(self):
> --> 663 return self._jvm.HiveContext(self._jsc.sc())
> 664
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> __call__(self, *args)
> 700 return_value = get_return_value(answer, self._gateway_client,
> None,
> --> 701 self._fqn)
> 702
> /root/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
> 35 try:
> ---> 36 return f(*a, **kw)
> 37 except py4j.protocol.Py4JJavaError as e:
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in
> get_return_value(answer, gateway_client, target_id, name)
> 299 'An error occurred while calling {0}{1}{2}.\n'.
> --> 300 format(target_id, '.', name), value)
> 301 else:
> Py4JJavaError: An error occurred while calling
> None.org.apache.spark.sql.hive.HiveContext.
> : java.lang.RuntimeException: java.io.IOException: Filesystem closed
> at
> org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522)
> at
> org.apache.spark.sql.hive.client.ClientWrapper.<init>(ClientWrapper.scala:171)
> at
> org.apache.spark.sql.hive.HiveContext.executionHive$lzycompute(HiveContext.scala:162)
> at
> org.apache.spark.sql.hive.HiveContext.executionHive(HiveContext.scala:160)
> at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:167)
> at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
> at
> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
> at
> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
> at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
> at py4j.Gateway.invoke(Gateway.java:214)
> at
> py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:79)
> at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
> at py4j.GatewayConnection.run(GatewayConnection.java:207)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.io.IOException: Filesystem closed
> at org.apache.hadoop.hdfs.DFSClient.checkOpen(DFSClient.java:323)
> at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:1057)
> at
> org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:554)
> at
> org.apache.hadoop.hive.ql.session.SessionState.createRootHDFSDir(SessionState.java:599)
> at
> org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(SessionState.java:554)
> at
> org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:508)
> ... 15 more
> During handling of the above exception, another exception occurred:
> Exception Traceback (most recent call last)
> <ipython-input-1-0beb490d573c> in <module>()
> 5 (1, "I wish Java could use case classes"),
> 6 (2, "Logistic,regression,models,are,neat")
> ----> 7 ], ["label", "sentence"])
> 8 tokenizer = Tokenizer(inputCol="sentence", outputCol="words")
> 9 wordsDataFrame = tokenizer.transform(sentenceDataFrame)
> /root/spark/python/pyspark/sql/context.py in createDataFrame(self, data,
> schema, samplingRatio)
> 406 rdd, schema = self._createFromLocal(data, schema)
> 407 jrdd =
> self._jvm.SerDeUtil.toJavaArray(rdd._to_java_object_rdd())
> --> 408 jdf = self._ssql_ctx.applySchemaToPythonRDD(jrdd.rdd(),
> schema.json())
> 409 df = DataFrame(jdf, self)
> 410 df._schema = schema
> /root/spark/python/pyspark/sql/context.py in _ssql_ctx(self)
> 658 raise Exception("You must build Spark with Hive. "
> 659 "Export 'SPARK_HIVE=true' and run "
> --> 660 "build/sbt assembly", e)
> 661
> 662 def _get_hive_ctx(self):
> Exception: ("You must build Spark with Hive. Export 'SPARK_HIVE=true' and run
> build/sbt assembly", Py4JJavaError('An error occurred while calling
> None.org.apache.spark.sql.hive.HiveContext.\n', JavaObject id=o38))
> {code}
--
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
