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https://issues.apache.org/jira/browse/HUDI-528?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bhavani Sudha updated HUDI-528:
-------------------------------
    Fix Version/s: 0.6.0

> Incremental Pull fails when latest commit is empty
> --------------------------------------------------
>
>                 Key: HUDI-528
>                 URL: https://issues.apache.org/jira/browse/HUDI-528
>             Project: Apache Hudi (incubating)
>          Issue Type: Bug
>          Components: Incremental Pull
>            Reporter: Javier Vega
>            Assignee: Yanjia Gary Li
>            Priority: Minor
>              Labels: bug-bash-0.6.0, help-requested, pull-request-available
>             Fix For: 0.6.0, 0.5.3
>
>
> When trying to create an incremental view of a dataset, an exception is 
> thrown when the latest commit in the time range is empty. In order to 
> determine the schema of the dataset, Hudi will grab the [latest commit file, 
> parse it, and grab the first metadata file 
> path|https://github.com/apache/incubator-hudi/blob/480fc7869d4d69e1219bf278fd9a37f27ac260f6/hudi-spark/src/main/scala/org/apache/hudi/IncrementalRelation.scala#L78-L80].
>  If the latest commit was empty though, the field which is used to determine 
> file paths (partitionToWriteStats) will be empty causing the following 
> exception:
>  
>  
> {code:java}
> java.util.NoSuchElementException
>   at java.util.HashMap$HashIterator.nextNode(HashMap.java:1447)
>   at java.util.HashMap$ValueIterator.next(HashMap.java:1474)
>   at org.apache.hudi.IncrementalRelation.<init>(IncrementalRelation.scala:80)
>   at org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:65)
>   at org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:46)
>   at 
> org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:318)
>   at 
> org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:223)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178)
> {code}



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