[ 
https://issues.apache.org/jira/browse/CARBONDATA-2082?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

kumar vishal resolved CARBONDATA-2082.
--------------------------------------
    Resolution: Fixed

> Timeseries pre-aggregate table should support the blank space
> -------------------------------------------------------------
>
>                 Key: CARBONDATA-2082
>                 URL: https://issues.apache.org/jira/browse/CARBONDATA-2082
>             Project: CarbonData
>          Issue Type: Bug
>          Components: core, spark-integration
>    Affects Versions: 1.3.0
>            Reporter: xubo245
>            Assignee: xubo245
>            Priority: Minor
>             Fix For: 1.3.0
>
>          Time Spent: 2h 50m
>  Remaining Estimate: 0h
>
> timeseries pre-aggregate table should support the blank space
> 1.scenario 1
> {code:java}
>    test("test timeseries create table 35: support event_time and granularity 
> key with space") {
>           sql("DROP DATAMAP IF EXISTS agg1_month ON TABLE maintable")
>           sql(
>             s"""CREATE DATAMAP agg1_month ON TABLE mainTable
>                |USING '$timeSeries'
>                |DMPROPERTIES (
>                |   'event_time '=' dataTime',
>                |   'MONTH_GRANULARITY '='1')
>                |AS SELECT dataTime, SUM(age) FROM mainTable
>                |GROUP BY dataTime
>               """.stripMargin)
>           checkExistence(sql("SHOW TABLES"), true, "maintable_agg1_month")
>         }
> {code}
> problem: NPE
> {code:java}
>       java.lang.NullPointerException was thrown.
>       java.lang.NullPointerException
>               at 
> org.apache.spark.sql.execution.command.timeseries.TimeSeriesUtil$.validateTimeSeriesEventTime(TimeSeriesUtil.scala:50)
>               at 
> org.apache.spark.sql.execution.command.preaaggregate.CreatePreAggregateTableCommand.processMetadata(CreatePreAggregateTableCommand.scala:104)
>               at 
> org.apache.spark.sql.execution.command.datamap.CarbonCreateDataMapCommand.processMetadata(CarbonCreateDataMapCommand.scala:75)
>               at 
> org.apache.spark.sql.execution.command.AtomicRunnableCommand.run(package.scala:84)
>               at 
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
> {code}
> 2.scenario 2
> {code:java}
>                 test("test timeseries create table 36: support event_time and 
> granularity key with space") {
>                   sql("DROP DATAMAP IF EXISTS agg1_month ON TABLE maintable")
>                   sql(
>                     s"""CREATE DATAMAP agg1_month ON TABLE mainTable
>                        |USING '$timeSeries'
>                        |DMPROPERTIES (
>                        |   'event_time '='dataTime',
>                        |   'MONTH_GRANULARITY '=' 1')
>                        |AS SELECT dataTime, SUM(age) FROM mainTable
>                        |GROUP BY dataTime
>                       """.stripMargin)
>                   checkExistence(sql("SHOW TABLES"), true, 
> "maintable_agg1_month")
>                 }
>       
> {code}
> problem:
> {code:java}
>       Granularity only support 1
>       org.apache.carbondata.spark.exception.MalformedDataMapCommandException: 
> Granularity only support 1
>               at 
> org.apache.spark.sql.execution.command.timeseries.TimeSeriesUtil$.getTimeSeriesGranularityDetails(TimeSeriesUtil.scala:118)
>               at 
> org.apache.spark.sql.execution.command.datamap.CarbonCreateDataMapCommand.processMetadata(CarbonCreateDataMapCommand.scala:58)
>               at 
> org.apache.spark.sql.execution.command.AtomicRunnableCommand.run(package.scala:84)
>               at 
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
>               at 
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
>               at 
> org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:67)
>               at org.apache.spark.sql.Dataset.<init>(Dataset.scala:183)
>               at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:68)
>               at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:632)
> {code}



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

Reply via email to