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https://issues.apache.org/jira/browse/SPARK-12868?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16049814#comment-16049814
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Dayou Zhou commented on SPARK-12868:
------------------------------------
Hi [~tleftwich] and all,
I was using Spark 2.0 and when I tried to invoke Hive UDTF, I got the following
error:
Undefined function: '...'. This function is neither a registered temporary
function nor a permanent function registered in the database 'default'.;
Then I picked up Spark 2.2 with this fix and the above error went away, which
is good. However, when I tried to create new UDTFs and invoke them, I again
ran into the above error. Any idea why? Any help appreciated.
> ADD JAR via sparkSQL JDBC will fail when using a HDFS URL
> ---------------------------------------------------------
>
> Key: SPARK-12868
> URL: https://issues.apache.org/jira/browse/SPARK-12868
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.0
> Reporter: Trystan Leftwich
> Assignee: Weiqing Yang
> Fix For: 2.2.0
>
>
> When trying to add a jar with a HDFS URI, i.E
> {code:sql}
> ADD JAR hdfs:///tmp/foo.jar
> {code}
> Via the spark sql JDBC interface it will fail with:
> {code:sql}
> java.net.MalformedURLException: unknown protocol: hdfs
> at java.net.URL.<init>(URL.java:593)
> at java.net.URL.<init>(URL.java:483)
> at java.net.URL.<init>(URL.java:432)
> at java.net.URI.toURL(URI.java:1089)
> at
> org.apache.spark.sql.hive.client.ClientWrapper.addJar(ClientWrapper.scala:578)
> at org.apache.spark.sql.hive.HiveContext.addJar(HiveContext.scala:652)
> at org.apache.spark.sql.hive.execution.AddJar.run(commands.scala:89)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
> at
> org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:145)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:130)
> at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:52)
> at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:817)
> at
> org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.org$apache$spark$sql$hive$thriftserver$SparkExecuteStatementOperation$$execute(SparkExecuteStatementOperation.scala:211)
> at
> org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$1$$anon$2.run(SparkExecuteStatementOperation.scala:154)
> at
> org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$1$$anon$2.run(SparkExecuteStatementOperation.scala:151)
> at java.security.AccessController.doPrivileged(Native Method)
> at javax.security.auth.Subject.doAs(Subject.java:422)
> at
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
> at
> org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$1.run(SparkExecuteStatementOperation.scala:164)
> at
> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> 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)
> {code}
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