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https://issues.apache.org/jira/browse/SPARK-13721?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15464427#comment-15464427
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Ewan Leith commented on SPARK-13721:
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Assuming Don's use case is the same as ours, we have to do odd looking queries
like this pseudo-code to get the full set of entries when using explode with
records where the nested array is not always populated (with the .filter's to
make it explicit what's happening):
val df1 = df
.filter("column.nested_array is not null")
.withColumn("element", explode(col("column.nested_array")))
.select("other_column", "element")
val df2 = df
.filter("column.nested_array is null")
.select("other_column", lit("") as "element")
df1.unionAll(df2)
> Add support for LATERAL VIEW OUTER explode()
> --------------------------------------------
>
> Key: SPARK-13721
> URL: https://issues.apache.org/jira/browse/SPARK-13721
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Ian Hellstrom
>
> Hive supports the [LATERAL VIEW
> OUTER|https://cwiki.apache.org/confluence/display/Hive/LanguageManual+LateralView#LanguageManualLateralView-OuterLateralViews]
> syntax to make sure that when an array is empty, the content from the outer
> table is still returned.
> Within Spark, this is currently only possible within the HiveContext and
> executing HiveQL statements. It would be nice if the standard explode()
> DataFrame method allows the same. A possible signature would be:
> {code:scala}
> explode[A, B](inputColumn: String, outputColumn: String, outer: Boolean =
> false)
> {code}
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