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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-21513) SQL to_json should support all column types
Date Mon, 28 Aug 2017 17:35:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-21513?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-21513:
------------------------------------

    Assignee: Apache Spark

> SQL to_json should support all column types
> -------------------------------------------
>
>                 Key: SPARK-21513
>                 URL: https://issues.apache.org/jira/browse/SPARK-21513
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.2.0
>            Reporter: Aaron Davidson
>            Assignee: Apache Spark
>              Labels: Starter
>
> The built-in SQL UDF "to_json" currently supports serializing StructType columns, as
well as Arrays of StructType columns. If you attempt to use it on a different type, for example
a map, you get an error like this:
> {code}
> AnalysisException: cannot resolve 'structstojson(`tags`)' due to data type mismatch:
Input type map<string,string> must be a struct or array of structs.;;
> {code}
> This limitation seems arbitrary; if I were to go through the effort of enclosing my map
in a struct, it would be serializable. Same thing with any other non-struct type.
> Therefore the desired improvement is to allow to_json to operate directly on any column
type. The associated code is [here|https://github.com/apache/spark/blob/86174ea89b39a300caaba6baffac70f3dc702788/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala#L653].



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