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Posted to issues@spark.apache.org by "Peter Parente (JIRA)" <ji...@apache.org> on 2016/12/30 23:22:58 UTC
[jira] [Updated] (SPARK-19038) Can't find keytab file when using
Hive catalog
[ https://issues.apache.org/jira/browse/SPARK-19038?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Peter Parente updated SPARK-19038:
----------------------------------
Description:
h2. Stack Trace
{noformat}
Py4JJavaErrorTraceback (most recent call last)
<ipython-input-13-c35b9cad36ad> in <module>()
----> 1 sdf = sql.createDataFrame(df)
/opt/spark2/python/pyspark/sql/context.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
307 Py4JJavaError: ...
308 """
--> 309 return self.sparkSession.createDataFrame(data, schema, samplingRatio, verifySchema)
310
311 @since(1.3)
/opt/spark2/python/pyspark/sql/session.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
524 rdd, schema = self._createFromLocal(map(prepare, data), schema)
525 jrdd = self._jvm.SerDeUtil.toJavaArray(rdd._to_java_object_rdd())
--> 526 jdf = self._jsparkSession.applySchemaToPythonRDD(jrdd.rdd(), schema.json())
527 df = DataFrame(jdf, self._wrapped)
528 df._schema = schema
/opt/spark2/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py in __call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
/opt/spark2/python/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/opt/spark2/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling o47.applySchemaToPythonRDD.
: org.apache.spark.SparkException: Keytab file: .keytab-f0b9b814-460e-4fa8-8e7d-029186b696c4 specified in spark.yarn.keytab does not exist
at org.apache.spark.sql.hive.client.HiveClientImpl.<init>(HiveClientImpl.scala:113)
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:423)
at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:258)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:359)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:263)
at org.apache.spark.sql.hive.HiveSharedState.metadataHive$lzycompute(HiveSharedState.scala:39)
at org.apache.spark.sql.hive.HiveSharedState.metadataHive(HiveSharedState.scala:38)
at org.apache.spark.sql.hive.HiveSharedState.externalCatalog$lzycompute(HiveSharedState.scala:46)
at org.apache.spark.sql.hive.HiveSharedState.externalCatalog(HiveSharedState.scala:45)
at org.apache.spark.sql.hive.HiveSessionState.catalog$lzycompute(HiveSessionState.scala:50)
at org.apache.spark.sql.hive.HiveSessionState.catalog(HiveSessionState.scala:48)
at org.apache.spark.sql.hive.HiveSessionState$$anon$1.<init>(HiveSessionState.scala:63)
at org.apache.spark.sql.hive.HiveSessionState.analyzer$lzycompute(HiveSessionState.scala:63)
at org.apache.spark.sql.hive.HiveSessionState.analyzer(HiveSessionState.scala:62)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
at org.apache.spark.sql.SparkSession.applySchemaToPythonRDD(SparkSession.scala:666)
at org.apache.spark.sql.SparkSession.applySchemaToPythonRDD(SparkSession.scala:656)
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:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
{noformat}
h2. Steps to reproduce
1. Pass valid --principal=user@REALM and --keytab=/home/user/.keytab to spark-submit
2. Set spark.sql.catalogImplementation = 'hive'
3. Create a SparkSession and try to use session.createDataFrame()
h2. Observations
* The {{setupCredentials}} function in Client.scala sets {{spark.yarn.keytab}} to a UUID suffixed version of the base keytab filename without any path. For example, {{sparkContext.getConf().getAll()}} shows {{spark.yarn.keytab}} as having value {{.keytab-f0b9b814-460e-4fa8-8e7d-029186b696c4}}
* When listing the contents of the application staging directory on HDFS, no suffixed file exists. Rather, the keytab file appears in the listing with its original name. For instance, {{hdfs dfs -ls hdfs://home/user/.sparkStaging/appication_big_uuid/}} shows an entry {{hdfs://home/user/.sparkStaging/appication_big_uuid/.keytab}}, but not {{hdfs://home/user/.sparkStaging/appication_big_uuid/.keytab-big-uuid}}.
* The same exception noted above occurs even after I manually put a copy of the keytab with a filename matching the new value of {{spark.yarn.keytab}} onto HDFS in the staging directory.
h2. Expected Behavior
HiveClientImpl should be able to read {{spark.yarn.keytab}} to find the keytab file and initialize itself properly.
h2. References
* SPARK-8619 also noted trouble with the keytab property getting changed after app startup.
was:
## Stack Trace
{noformat}
Py4JJavaErrorTraceback (most recent call last)
<ipython-input-13-c35b9cad36ad> in <module>()
----> 1 sdf = sql.createDataFrame(df)
/opt/spark2/python/pyspark/sql/context.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
307 Py4JJavaError: ...
308 """
--> 309 return self.sparkSession.createDataFrame(data, schema, samplingRatio, verifySchema)
310
311 @since(1.3)
/opt/spark2/python/pyspark/sql/session.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
524 rdd, schema = self._createFromLocal(map(prepare, data), schema)
525 jrdd = self._jvm.SerDeUtil.toJavaArray(rdd._to_java_object_rdd())
--> 526 jdf = self._jsparkSession.applySchemaToPythonRDD(jrdd.rdd(), schema.json())
527 df = DataFrame(jdf, self._wrapped)
528 df._schema = schema
/opt/spark2/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py in __call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
/opt/spark2/python/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/opt/spark2/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling o47.applySchemaToPythonRDD.
: org.apache.spark.SparkException: Keytab file: .keytab-f0b9b814-460e-4fa8-8e7d-029186b696c4 specified in spark.yarn.keytab does not exist
at org.apache.spark.sql.hive.client.HiveClientImpl.<init>(HiveClientImpl.scala:113)
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:423)
at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:258)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:359)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:263)
at org.apache.spark.sql.hive.HiveSharedState.metadataHive$lzycompute(HiveSharedState.scala:39)
at org.apache.spark.sql.hive.HiveSharedState.metadataHive(HiveSharedState.scala:38)
at org.apache.spark.sql.hive.HiveSharedState.externalCatalog$lzycompute(HiveSharedState.scala:46)
at org.apache.spark.sql.hive.HiveSharedState.externalCatalog(HiveSharedState.scala:45)
at org.apache.spark.sql.hive.HiveSessionState.catalog$lzycompute(HiveSessionState.scala:50)
at org.apache.spark.sql.hive.HiveSessionState.catalog(HiveSessionState.scala:48)
at org.apache.spark.sql.hive.HiveSessionState$$anon$1.<init>(HiveSessionState.scala:63)
at org.apache.spark.sql.hive.HiveSessionState.analyzer$lzycompute(HiveSessionState.scala:63)
at org.apache.spark.sql.hive.HiveSessionState.analyzer(HiveSessionState.scala:62)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
at org.apache.spark.sql.SparkSession.applySchemaToPythonRDD(SparkSession.scala:666)
at org.apache.spark.sql.SparkSession.applySchemaToPythonRDD(SparkSession.scala:656)
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:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
{noformat}
## Steps to reproduce
1. Pass valid --principal=user@REALM and --keytab=/home/user/.keytab to spark-submit
2. Set spark.sql.catalogImplementation = 'hive'
3. Create a SparkSession and try to use session.createDataFrame()
## Observations
* The {{setupCredentials}} function in Client.scala sets {{spark.yarn.keytab}} to a UUID suffixed version of the base keytab filename without any path. For example, {{sparkContext.getConf().getAll()}} shows {{spark.yarn.keytab}} as having value {{.keytab-f0b9b814-460e-4fa8-8e7d-029186b696c4}}
* When listing the contents of the application staging directory on HDFS, no suffixed file exists. Rather, the keytab file appears in the listing with its original name. For instance, {{hdfs dfs -ls hdfs://home/user/.sparkStaging/appication_big_uuid/}} shows an entry {{hdfs://home/user/.sparkStaging/appication_big_uuid/.keytab}}, but not {{hdfs://home/user/.sparkStaging/appication_big_uuid/.keytab-big-uuid}}.
* The same exception noted above occurs even after I manually put a copy of the keytab with a filename matching the new value of {{spark.yarn.keytab}} onto HDFS in the staging directory.
## Expected Behavior
HiveClientImpl should be able to read {{spark.yarn.keytab}} to find the keytab file and initialize itself properly.
## References
* SPARK-8619 also noted trouble with the keytab property getting changed after app startup.
> Can't find keytab file when using Hive catalog
> ----------------------------------------------
>
> Key: SPARK-19038
> URL: https://issues.apache.org/jira/browse/SPARK-19038
> Project: Spark
> Issue Type: Bug
> Components: YARN
> Affects Versions: 2.0.2
> Environment: Hadoop / YARN 2.6, pyspark
> Reporter: Peter Parente
> Labels: hive, kerberos, pyspark
>
> h2. Stack Trace
> {noformat}
> Py4JJavaErrorTraceback (most recent call last)
> <ipython-input-13-c35b9cad36ad> in <module>()
> ----> 1 sdf = sql.createDataFrame(df)
> /opt/spark2/python/pyspark/sql/context.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
> 307 Py4JJavaError: ...
> 308 """
> --> 309 return self.sparkSession.createDataFrame(data, schema, samplingRatio, verifySchema)
> 310
> 311 @since(1.3)
> /opt/spark2/python/pyspark/sql/session.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
> 524 rdd, schema = self._createFromLocal(map(prepare, data), schema)
> 525 jrdd = self._jvm.SerDeUtil.toJavaArray(rdd._to_java_object_rdd())
> --> 526 jdf = self._jsparkSession.applySchemaToPythonRDD(jrdd.rdd(), schema.json())
> 527 df = DataFrame(jdf, self._wrapped)
> 528 df._schema = schema
> /opt/spark2/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py in __call__(self, *args)
> 1131 answer = self.gateway_client.send_command(command)
> 1132 return_value = get_return_value(
> -> 1133 answer, self.gateway_client, self.target_id, self.name)
> 1134
> 1135 for temp_arg in temp_args:
> /opt/spark2/python/pyspark/sql/utils.py in deco(*a, **kw)
> 61 def deco(*a, **kw):
> 62 try:
> ---> 63 return f(*a, **kw)
> 64 except py4j.protocol.Py4JJavaError as e:
> 65 s = e.java_exception.toString()
> /opt/spark2/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
> 317 raise Py4JJavaError(
> 318 "An error occurred while calling {0}{1}{2}.\n".
> --> 319 format(target_id, ".", name), value)
> 320 else:
> 321 raise Py4JError(
> Py4JJavaError: An error occurred while calling o47.applySchemaToPythonRDD.
> : org.apache.spark.SparkException: Keytab file: .keytab-f0b9b814-460e-4fa8-8e7d-029186b696c4 specified in spark.yarn.keytab does not exist
> at org.apache.spark.sql.hive.client.HiveClientImpl.<init>(HiveClientImpl.scala:113)
> 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:423)
> at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:258)
> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:359)
> at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:263)
> at org.apache.spark.sql.hive.HiveSharedState.metadataHive$lzycompute(HiveSharedState.scala:39)
> at org.apache.spark.sql.hive.HiveSharedState.metadataHive(HiveSharedState.scala:38)
> at org.apache.spark.sql.hive.HiveSharedState.externalCatalog$lzycompute(HiveSharedState.scala:46)
> at org.apache.spark.sql.hive.HiveSharedState.externalCatalog(HiveSharedState.scala:45)
> at org.apache.spark.sql.hive.HiveSessionState.catalog$lzycompute(HiveSessionState.scala:50)
> at org.apache.spark.sql.hive.HiveSessionState.catalog(HiveSessionState.scala:48)
> at org.apache.spark.sql.hive.HiveSessionState$$anon$1.<init>(HiveSessionState.scala:63)
> at org.apache.spark.sql.hive.HiveSessionState.analyzer$lzycompute(HiveSessionState.scala:63)
> at org.apache.spark.sql.hive.HiveSessionState.analyzer(HiveSessionState.scala:62)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
> at org.apache.spark.sql.SparkSession.applySchemaToPythonRDD(SparkSession.scala:666)
> at org.apache.spark.sql.SparkSession.applySchemaToPythonRDD(SparkSession.scala:656)
> 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:498)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at py4j.Gateway.invoke(Gateway.java:280)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:214)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> h2. Steps to reproduce
> 1. Pass valid --principal=user@REALM and --keytab=/home/user/.keytab to spark-submit
> 2. Set spark.sql.catalogImplementation = 'hive'
> 3. Create a SparkSession and try to use session.createDataFrame()
> h2. Observations
> * The {{setupCredentials}} function in Client.scala sets {{spark.yarn.keytab}} to a UUID suffixed version of the base keytab filename without any path. For example, {{sparkContext.getConf().getAll()}} shows {{spark.yarn.keytab}} as having value {{.keytab-f0b9b814-460e-4fa8-8e7d-029186b696c4}}
> * When listing the contents of the application staging directory on HDFS, no suffixed file exists. Rather, the keytab file appears in the listing with its original name. For instance, {{hdfs dfs -ls hdfs://home/user/.sparkStaging/appication_big_uuid/}} shows an entry {{hdfs://home/user/.sparkStaging/appication_big_uuid/.keytab}}, but not {{hdfs://home/user/.sparkStaging/appication_big_uuid/.keytab-big-uuid}}.
> * The same exception noted above occurs even after I manually put a copy of the keytab with a filename matching the new value of {{spark.yarn.keytab}} onto HDFS in the staging directory.
> h2. Expected Behavior
> HiveClientImpl should be able to read {{spark.yarn.keytab}} to find the keytab file and initialize itself properly.
> h2. References
> * SPARK-8619 also noted trouble with the keytab property getting changed after app startup.
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