To whom it may concern:
After upgrading to Zeppelin 0.6.0, I am having a couple interpreter anomalies.
Please look below, and I hope that there will be an easy fix for them.
1. Spark SQL gives me in this error in the Zeppelin Tutorial notebook, but the
Scala code to populate and register the temp table runs fine.
java.lang.NullPointerException
at
org.apache.spark.sql.hive.client.ClientWrapper.conf(ClientWrapper.scala:205)
at
org.apache.spark.sql.hive.client.ClientWrapper.client(ClientWrapper.scala:261)
at
org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$withHiveState$1.apply(ClientWrapper.scala:273)
at
org.apache.spark.sql.hive.client.ClientWrapper.liftedTree1$1(ClientWrapper.scala:228)
at
org.apache.spark.sql.hive.client.ClientWrapper.retryLocked(ClientWrapper.scala:227)
at
org.apache.spark.sql.hive.client.ClientWrapper.withHiveState(ClientWrapper.scala:270)
at org.apache.spark.sql.hive.HiveQLDialect.parse(HiveContext.scala:65)
at
org.apache.spark.sql.SQLContext$$anonfun$2.apply(SQLContext.scala:211)
at
org.apache.spark.sql.SQLContext$$anonfun$2.apply(SQLContext.scala:211)
at
org.apache.spark.sql.execution.SparkSQLParser$$anonfun$org$apache$spark$sql$execution$SparkSQLParser$$others$1.apply(SparkSQLParser.scala:114)
at
org.apache.spark.sql.execution.SparkSQLParser$$anonfun$org$apache$spark$sql$execution$SparkSQLParser$$others$1.apply(SparkSQLParser.scala:113)
at scala.util.parsing.combinator.Parsers$Success.map(Parsers.scala:136)
at scala.util.parsing.combinator.Parsers$Success.map(Parsers.scala:135)
at
scala.util.parsing.combinator.Parsers$Parser$$anonfun$map$1.apply(Parsers.scala:242)
at
scala.util.parsing.combinator.Parsers$Parser$$anonfun$map$1.apply(Parsers.scala:242)
at
scala.util.parsing.combinator.Parsers$$anon$3.apply(Parsers.scala:222)
at
scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1$$anonfun$apply$2.apply(Parsers.scala:254)
at
scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1$$anonfun$apply$2.apply(Parsers.scala:254)
at
scala.util.parsing.combinator.Parsers$Failure.append(Parsers.scala:202)
at
scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1.apply(Parsers.scala:254)
at
scala.util.parsing.combinator.Parsers$Parser$$anonfun$append$1.apply(Parsers.scala:254)
at
scala.util.parsing.combinator.Parsers$$anon$3.apply(Parsers.scala:222)
at
scala.util.parsing.combinator.Parsers$$anon$2$$anonfun$apply$14.apply(Parsers.scala:891)
at
scala.util.parsing.combinator.Parsers$$anon$2$$anonfun$apply$14.apply(Parsers.scala:891)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at
scala.util.parsing.combinator.Parsers$$anon$2.apply(Parsers.scala:890)
at
scala.util.parsing.combinator.PackratParsers$$anon$1.apply(PackratParsers.scala:110)
at
org.apache.spark.sql.catalyst.AbstractSparkSQLParser.parse(AbstractSparkSQLParser.scala:34)
at
org.apache.spark.sql.SQLContext$$anonfun$1.apply(SQLContext.scala:208)
at
org.apache.spark.sql.SQLContext$$anonfun$1.apply(SQLContext.scala:208)
at
org.apache.spark.sql.execution.datasources.DDLParser.parse(DDLParser.scala:43)
at org.apache.spark.sql.SQLContext.parseSql(SQLContext.scala:231)
at org.apache.spark.sql.hive.HiveContext.parseSql(HiveContext.scala:333)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:817)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at
org.apache.zeppelin.spark.SparkSqlInterpreter.interpret(SparkSqlInterpreter.java:117)
at
org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:94)
at
org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:341)
at org.apache.zeppelin.scheduler.Job.run(Job.java:176)
at
org.apache.zeppelin.scheduler.ParallelScheduler$JobRunner.run(ParallelScheduler.java:162)
at
java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
at
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
2. Livy Spark SQL does not work also.
<console>:32: error: overloaded method value show with alternatives:
(truncate: Boolean)Unit <and>
(numRows: Int)Unit
cannot be applied to (Null)
sqlContext.sql("select age, count(1) value from bank where age <
30 group by age order by age").show(null)
Thanks,
Ben
> On Jul 6, 2016, at 12:14 AM, mina lee <mina...@apache.org> wrote:
>
> The Apache Zeppelin community is pleased to announce the availability of the
> 0.6.0 release.
>
> Zeppelin is a collaborative data analytics and visualization tool for
> distributed, general-purpose data processing system such as Apache Spark,
> Apache Flink, etc.
>
> The community put significant effort into improving Apache Zeppelin since the
> last release, focusing on having new backend support, implementing
> authentication and authorization for enterprise. More than 70+ contributors
> provided 360+ patches for new features, improvements and bug fixes. More than
> 200+ issues have been resolved.
>
> We encourage download the latest release from
> http://zeppelin.apache.org/download.html
> <http://zeppelin.apache.org/download.html>
>
> Release note is available at
> http://zeppelin.apache.org/releases/zeppelin-release-0.6.0.html
> <http://zeppelin.incubator.apache.org/releases/zeppelin-release-0.6.0.html>
>
> We welcome your help and feedback. For more information on the project and
> how to get involved, visit our website at http://zeppelin.apache.org/
> <http://zeppelin.apache.org/>
>
> Thanks to all users and contributors who have helped to improve Apache
> Zeppelin.
>
> Regards,
> The Apache Zeppelin community
>
