[jira] [Resolved] (SPARK-16275) Implement all the Hive fallback functions

["Sean Owen (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-16275?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-16275.
-------------------------------
    Target Version/s:   (was: 3.0.0)
          Resolution: Done

> 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
>            Priority: Major
>
> 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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