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Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2018/07/12 21:11:00 UTC

[jira] [Resolved] (SPARK-23007) Add schema evolution test suite for file-based data sources

     [ https://issues.apache.org/jira/browse/SPARK-23007?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xiao Li resolved SPARK-23007.
-----------------------------
       Resolution: Fixed
         Assignee: Dongjoon Hyun
    Fix Version/s: 2.4.0

> Add schema evolution test suite for file-based data sources
> -----------------------------------------------------------
>
>                 Key: SPARK-23007
>                 URL: https://issues.apache.org/jira/browse/SPARK-23007
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL, Tests
>    Affects Versions: 2.2.1
>            Reporter: Dongjoon Hyun
>            Assignee: Dongjoon Hyun
>            Priority: Major
>             Fix For: 2.4.0
>
>
> A schema can evolve in several ways and the followings are already supported in file-based data sources.
>    1. Add a column
>    2. Remove a column
>    3. Change a column position
>    4. Change a column type
> This issue aims to guarantee users a backward-compatible schema evolution coverage on file-based data sources and to prevent future regressions by *adding schema evolution test suites explicitly*.
> Here, we consider safe evolution without data loss. For example, data type evolution should be from small types to larger types like `int`-to-`long`, not vice versa.
> As of today, in the master branch, file-based data sources have schema evolution coverages like the followings.
> || File Format || Coverage     || Note                                                   ||
> | TEXT         | N/A          | Schema consists of a single string column.             |
> | CSV          | 1, 2, 4      |                                                        |
> | JSON         | 1, 2, 3, 4   |                                                        |
> | ORC          | 1, 2, 3, 4   | Native vectorized ORC reader has the widest coverage.  |
> | PARQUET      | 1, 2, 3      |                                                        |



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