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https://issues.apache.org/jira/browse/SPARK-16275?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15371199#comment-15371199
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Reynold Xin commented on SPARK-16275:
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Note that some of these might result in slightly different behavioral changes
and as a result if possible, it'd be great for these to be in 2.0 rather than
2.1, so we don't break compatibility. The good thing is that these functions
are all very isolated and as a result doesn't impact rest of the code base.
> Implement all the Hive fallback functions
> -----------------------------------------
>
> Key: SPARK-16275
> URL: https://issues.apache.org/jira/browse/SPARK-16275
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Reporter: Reynold Xin
>
> As of Spark 2.0, Spark falls back to Hive for only the following built-in
> functions:
> {code}
> "elt", "hash", "java_method", "histogram_numeric",
> "map_keys", "map_values",
> "parse_url", "percentile", "percentile_approx", "reflect", "sentences",
> "stack", "str_to_map",
> "xpath", "xpath_boolean", "xpath_double", "xpath_float", "xpath_int",
> "xpath_long",
> "xpath_number", "xpath_short", "xpath_string",
> // table generating function
> "inline", "posexplode"
> {code}
> The goal of the ticket is to implement all of these in Spark so we don't need
> to fall back into Hive's UDFs.
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