-1
Unable to use Hive meta-store in pyspark shell. Tried both HiveContext and
SparkSession. Both failed. It always uses in-memory catalog. Anybody else
hit the same issue?
Method 1: SparkSession
>>> from pyspark.sql import SparkSession
>>> spark = SparkSession.builder.enableHiveSupport().getOrCreate()
>>>
>>> spark.sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING)")
DataFrame[]
>>> spark.sql("LOAD DATA LOCAL INPATH 'examples/src/main/resources/kv1.txt'
INTO TABLE src")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/session.py",
line 494, in sql
return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py",
line 933, in __call__
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py",
line 57, in deco
return f(*a, **kw)
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py",
line 312, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o21.sql.
: java.lang.UnsupportedOperationException: loadTable is not implemented
at
org.apache.spark.sql.catalyst.catalog.InMemoryCatalog.loadTable(InMemoryCatalog.scala:297)
at
org.apache.spark.sql.catalyst.catalog.SessionCatalog.loadTable(SessionCatalog.scala:280)
at org.apache.spark.sql.execution.command.LoadData.run(tables.scala:263)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:57)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:55)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:69)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
at
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:85)
at
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:85)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:187)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:168)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:541)
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:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:211)
at java.lang.Thread.run(Thread.java:745)
Method 2: Using HiveContext:
>>> from pyspark.sql import HiveContext
>>> sqlContext = HiveContext(sc)
>>> sqlContext.sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING)")
DataFrame[]
>>> sqlContext.sql("LOAD DATA LOCAL INPATH
'examples/src/main/resources/kv1.txt' INTO TABLE src")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/context.py",
line 346, in sql
return self.sparkSession.sql(sqlQuery)
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/session.py",
line 494, in sql
return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py",
line 933, in __call__
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py",
line 57, in deco
return f(*a, **kw)
File
"/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py",
line 312, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o21.sql.
: java.lang.UnsupportedOperationException: loadTable is not implemented
at
org.apache.spark.sql.catalyst.catalog.InMemoryCatalog.loadTable(InMemoryCatalog.scala:297)
at
org.apache.spark.sql.catalyst.catalog.SessionCatalog.loadTable(SessionCatalog.scala:280)
at org.apache.spark.sql.execution.command.LoadData.run(tables.scala:263)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:57)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:55)
at
org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:69)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
at
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:85)
at
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:85)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:187)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:168)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:541)
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:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:211)
at java.lang.Thread.run(Thread.java:745)
2016-05-19 12:49 GMT-07:00 Herman van Hövell tot Westerflier <
[email protected]>:
> +1
>
>
> 2016-05-19 18:20 GMT+02:00 Xiangrui Meng <[email protected]>:
>
>> +1
>>
>> On Thu, May 19, 2016 at 9:18 AM Joseph Bradley <[email protected]>
>> wrote:
>>
>>> +1
>>>
>>> On Wed, May 18, 2016 at 10:49 AM, Reynold Xin <[email protected]>
>>> wrote:
>>>
>>>> Hi Ovidiu-Cristian ,
>>>>
>>>> The best source of truth is change the filter with target version to
>>>> 2.1.0. Not a lot of tickets have been targeted yet, but I'd imagine as we
>>>> get closer to 2.0 release, more will be retargeted at 2.1.0.
>>>>
>>>>
>>>>
>>>> On Wed, May 18, 2016 at 10:43 AM, Ovidiu-Cristian MARCU <
>>>> [email protected]> wrote:
>>>>
>>>>> Yes, I can filter..
>>>>> Did that and for example:
>>>>>
>>>>> https://issues.apache.org/jira/browse/SPARK-15370?jql=project%20%3D%20SPARK%20AND%20resolution%20%3D%20Unresolved%20AND%20affectedVersion%20%3D%202.0.0
>>>>> <https://issues.apache.org/jira/browse/SPARK-15370?jql=project%20=%20SPARK%20AND%20resolution%20=%20Unresolved%20AND%20affectedVersion%20=%202.0.0>
>>>>>
>>>>> To rephrase: for 2.0 do you have specific issues that are not a
>>>>> priority and will released maybe with 2.1 for example?
>>>>>
>>>>> Keep up the good work!
>>>>>
>>>>> On 18 May 2016, at 18:19, Reynold Xin <[email protected]> wrote:
>>>>>
>>>>> You can find that by changing the filter to target version = 2.0.0.
>>>>> Cheers.
>>>>>
>>>>> On Wed, May 18, 2016 at 9:00 AM, Ovidiu-Cristian MARCU <
>>>>> [email protected]> wrote:
>>>>>
>>>>>> +1 Great, I see the list of resolved issues, do you have a list of
>>>>>> known issue you plan to stay with this release?
>>>>>>
>>>>>> with
>>>>>> build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.7.1 -Phive
>>>>>> -Phive-thriftserver -DskipTests clean package
>>>>>>
>>>>>> mvn -version
>>>>>> Apache Maven 3.3.9 (bb52d8502b132ec0a5a3f4c09453c07478323dc5;
>>>>>> 2015-11-10T17:41:47+01:00)
>>>>>> Maven home: /Users/omarcu/tools/apache-maven-3.3.9
>>>>>> Java version: 1.7.0_80, vendor: Oracle Corporation
>>>>>> Java home:
>>>>>> /Library/Java/JavaVirtualMachines/jdk1.7.0_80.jdk/Contents/Home/jre
>>>>>> Default locale: en_US, platform encoding: UTF-8
>>>>>> OS name: "mac os x", version: "10.11.5", arch: "x86_64", family: “mac"
>>>>>>
>>>>>> [INFO] Reactor Summary:
>>>>>> [INFO]
>>>>>> [INFO] Spark Project Parent POM ........................... SUCCESS
>>>>>> [ 2.635 s]
>>>>>> [INFO] Spark Project Tags ................................. SUCCESS
>>>>>> [ 1.896 s]
>>>>>> [INFO] Spark Project Sketch ............................... SUCCESS
>>>>>> [ 2.560 s]
>>>>>> [INFO] Spark Project Networking ........................... SUCCESS
>>>>>> [ 6.533 s]
>>>>>> [INFO] Spark Project Shuffle Streaming Service ............ SUCCESS
>>>>>> [ 4.176 s]
>>>>>> [INFO] Spark Project Unsafe ............................... SUCCESS
>>>>>> [ 4.809 s]
>>>>>> [INFO] Spark Project Launcher ............................. SUCCESS
>>>>>> [ 6.242 s]
>>>>>> [INFO] Spark Project Core ................................. SUCCESS
>>>>>> [01:20 min]
>>>>>> [INFO] Spark Project GraphX ............................... SUCCESS
>>>>>> [ 9.148 s]
>>>>>> [INFO] Spark Project Streaming ............................ SUCCESS [
>>>>>> 22.760 s]
>>>>>> [INFO] Spark Project Catalyst ............................. SUCCESS [
>>>>>> 50.783 s]
>>>>>> [INFO] Spark Project SQL .................................. SUCCESS
>>>>>> [01:05 min]
>>>>>> [INFO] Spark Project ML Local Library ..................... SUCCESS
>>>>>> [ 4.281 s]
>>>>>> [INFO] Spark Project ML Library ........................... SUCCESS [
>>>>>> 54.537 s]
>>>>>> [INFO] Spark Project Tools ................................ SUCCESS
>>>>>> [ 0.747 s]
>>>>>> [INFO] Spark Project Hive ................................. SUCCESS [
>>>>>> 33.032 s]
>>>>>> [INFO] Spark Project HiveContext Compatibility ............ SUCCESS
>>>>>> [ 3.198 s]
>>>>>> [INFO] Spark Project REPL ................................. SUCCESS
>>>>>> [ 3.573 s]
>>>>>> [INFO] Spark Project YARN Shuffle Service ................. SUCCESS
>>>>>> [ 4.617 s]
>>>>>> [INFO] Spark Project YARN ................................. SUCCESS
>>>>>> [ 7.321 s]
>>>>>> [INFO] Spark Project Hive Thrift Server ................... SUCCESS [
>>>>>> 16.496 s]
>>>>>> [INFO] Spark Project Assembly ............................. SUCCESS
>>>>>> [ 2.300 s]
>>>>>> [INFO] Spark Project External Flume Sink .................. SUCCESS
>>>>>> [ 4.219 s]
>>>>>> [INFO] Spark Project External Flume ....................... SUCCESS
>>>>>> [ 6.987 s]
>>>>>> [INFO] Spark Project External Flume Assembly .............. SUCCESS
>>>>>> [ 1.465 s]
>>>>>> [INFO] Spark Integration for Kafka 0.8 .................... SUCCESS
>>>>>> [ 6.891 s]
>>>>>> [INFO] Spark Project Examples ............................. SUCCESS [
>>>>>> 13.465 s]
>>>>>> [INFO] Spark Project External Kafka Assembly .............. SUCCESS
>>>>>> [ 2.815 s]
>>>>>> [INFO]
>>>>>> ------------------------------------------------------------------------
>>>>>> [INFO] BUILD SUCCESS
>>>>>> [INFO]
>>>>>> ------------------------------------------------------------------------
>>>>>> [INFO] Total time: 07:04 min
>>>>>> [INFO] Finished at: 2016-05-18T17:55:33+02:00
>>>>>> [INFO] Final Memory: 90M/824M
>>>>>> [INFO]
>>>>>> ------------------------------------------------------------------------
>>>>>>
>>>>>> On 18 May 2016, at 16:28, Sean Owen <[email protected]> wrote:
>>>>>>
>>>>>> I think it's a good idea. Although releases have been preceded before
>>>>>> by release candidates for developers, it would be good to get a formal
>>>>>> preview/beta release ratified for public consumption ahead of a new
>>>>>> major release. Better to have a little more testing in the wild to
>>>>>> identify problems before 2.0.0 is finalized.
>>>>>>
>>>>>> +1 to the release. License, sigs, etc check out. On Ubuntu 16 + Java
>>>>>> 8, compilation and tests succeed for "-Pyarn -Phive
>>>>>> -Phive-thriftserver -Phadoop-2.6".
>>>>>>
>>>>>> On Wed, May 18, 2016 at 6:40 AM, Reynold Xin <[email protected]> wrote:
>>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> In the past the Apache Spark community have created preview packages
>>>>>> (not
>>>>>> official releases) and used those as opportunities to ask community
>>>>>> members
>>>>>> to test the upcoming versions of Apache Spark. Several people in the
>>>>>> Apache
>>>>>> community have suggested we conduct votes for these preview packages
>>>>>> and
>>>>>> turn them into formal releases by the Apache foundation's standard.
>>>>>> Preview
>>>>>> releases are not meant to be functional, i.e. they can and highly
>>>>>> likely
>>>>>> will contain critical bugs or documentation errors, but we will be
>>>>>> able to
>>>>>> post them to the project's website to get wider feedback. They should
>>>>>> satisfy the legal requirements of Apache's release policy
>>>>>> (http://www.apache.org/dev/release.html) such as having proper
>>>>>> licenses.
>>>>>>
>>>>>>
>>>>>> Please vote on releasing the following candidate as Apache Spark
>>>>>> version
>>>>>> 2.0.0-preview. The vote is open until Friday, May 20, 2015 at 11:00
>>>>>> PM PDT
>>>>>> and passes if a majority of at least 3 +1 PMC votes are cast.
>>>>>>
>>>>>> [ ] +1 Release this package as Apache Spark 2.0.0-preview
>>>>>> [ ] -1 Do not release this package because ...
>>>>>>
>>>>>> To learn more about Apache Spark, please see http://spark.apache.org/
>>>>>>
>>>>>> The tag to be voted on is 2.0.0-preview
>>>>>> (8f5a04b6299e3a47aca13cbb40e72344c0114860)
>>>>>>
>>>>>> The release files, including signatures, digests, etc. can be found
>>>>>> at:
>>>>>>
>>>>>> http://home.apache.org/~pwendell/spark-releases/spark-2.0.0-preview-bin/
>>>>>>
>>>>>> Release artifacts are signed with the following key:
>>>>>> https://people.apache.org/keys/committer/pwendell.asc
>>>>>>
>>>>>> The documentation corresponding to this release can be found at:
>>>>>>
>>>>>> http://home.apache.org/~pwendell/spark-releases/spark-2.0.0-preview-docs/
>>>>>>
>>>>>> The list of resolved issues are:
>>>>>>
>>>>>> https://issues.apache.org/jira/browse/SPARK-15351?jql=project%20%3D%20SPARK%20AND%20fixVersion%20%3D%202.0.0
>>>>>>
>>>>>>
>>>>>> If you are a Spark user, you can help us test this release by taking
>>>>>> an
>>>>>> existing Apache Spark workload and running on this candidate, then
>>>>>> reporting
>>>>>> any regressions.
>>>>>>
>>>>>>
>>>>>> ---------------------------------------------------------------------
>>>>>> To unsubscribe, e-mail: [email protected]
>>>>>> For additional commands, e-mail: [email protected]
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>
>
