[jira] [Commented] (PHOENIX-6268) NoSuchMethodError when writing from Spark Dataframe to Phoenix with phoenix-spark connector

["Istvan Toth (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/PHOENIX-6268?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17519386#comment-17519386 ] 

Istvan Toth commented on PHOENIX-6268:
--------------------------------------

Removed the Release note, as it seems that this is not actual bug that we fixed.

> NoSuchMethodError when writing from Spark Dataframe to Phoenix with phoenix-spark connector
> -------------------------------------------------------------------------------------------
>
>                 Key: PHOENIX-6268
>                 URL: https://issues.apache.org/jira/browse/PHOENIX-6268
>             Project: Phoenix
>          Issue Type: Bug
>          Components: spark-connector
>    Affects Versions: 5.0.0
>            Reporter: Rico Bergmann
>            Priority: Critical
>             Fix For: connectors-6.0.0
>
>
> I opened a spark shell (including the phoenix-spark jar as --jars argument), loaded a dataframe (df) and wanted to store the dataframe in a phoenix server (backed by HBase).
> df.write.format("org.apache.phoenix.spark").mode(org.apache.spark.sql.SaveMode.Overwrite).options(
>  Map("zkUrl" -> "<zkserver1>:<port>,<zkserver2>:<port>"
>  , "table" -> "targetTablename")).save()
>  
> The table exists within Phoenix.
> I get below error in spark-shell. Can you help or fix this?
> spark version is 3.0.1
> java.lang.NoSuchMethodError: 'scala.collection.mutable.ArrayOps scala.Predef$.refArrayOps(java.lang.Object[])'
>  at org.apache.phoenix.spark.DataFrameFunctions.getFieldArray(DataFrameFunctions.scala:76)
>  at org.apache.phoenix.spark.DataFrameFunctions.saveToPhoenix(DataFrameFunctions.scala:35)
>  at org.apache.phoenix.spark.DataFrameFunctions.saveToPhoenix(DataFrameFunctions.scala:28)
>  at org.apache.phoenix.spark.DefaultSource.createRelation(DefaultSource.scala:47)
>  at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
>  at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
>  at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
>  at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
>  at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:175)
>  at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:213)
>  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:210)
>  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:171)
>  at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:122)
>  at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:121)
>  at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:963)
>  at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
>  at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
>  at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
>  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
>  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>  at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:963)
>  at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:415)
>  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:399)
>  ... 49 elided



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