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Posted to issues@spark.apache.org by "Dongjoon Hyun (JIRA)" <ji...@apache.org> on 2018/01/09 18:33:00 UTC
[jira] [Commented] (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:comment-tabpanel&focusedCommentId=16318883#comment-16318883 ]
Dongjoon Hyun commented on SPARK-23007:
---------------------------------------
I hope this should be in Apache Spark 2.3.0 since this is only test suites.
> 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
>
> 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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