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Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2017/06/01 23:02:14 UTC
[jira] [Updated] (SPARK-16275) Implement all the Hive fallback
functions
[ https://issues.apache.org/jira/browse/SPARK-16275?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Armbrust updated SPARK-16275:
-------------------------------------
Target Version/s: 2.3.0 (was: 2.2.0)
> 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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