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https://issues.apache.org/jira/browse/SPARK-58794?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18105115#comment-18105115
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Serge Rielau commented on SPARK-58794:
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Attached Spark-centric design pack: SPARK-58794-char-varchar-design.zip
(OVERVIEW, LCT, CAST/assignment, decisions, implementation plan, test outline,
subtask list).
Created sub-tasks:
* SPARK-58795 Design pack
* SPARK-58796 Config + first-class types
* SPARK-58797 Real CAST/try_cast
* SPARK-58798 LCT lattice
* SPARK-58799 R1 transforming exprs -> STRING
* SPARK-58800 Write-side assignment
* SPARK-58801 Read-side pad + oversize error
* SPARK-58802 Single-pass analyzer parity
* SPARK-58803 Dataset/encoder/UDF
* SPARK-58804 HS2/JDBC ResultSetMetaData
* SPARK-58805 getColumns COLUMN_SIZE
* SPARK-58806 Connect JDBC type map
* SPARK-58807 CTAS/VIEW/CTE inherit
* SPARK-58808 SQL FUNCTION params/RETURNS
* SPARK-58809 Session variables
* SPARK-58810 Parameterized lengths
* SPARK-58811 ALTER/temp/external
* SPARK-58812 Collation RTRIM compares
* SPARK-58813 SQL goldens
* SPARK-58814 Format round-trips
Flag: spark.sql.charVarchar.standardSemantics.enabled (default false). Leave
preserveCharVarcharTypeInfo as Spark 4.0 experimental for now.
> Full CHAR/VARCHAR support
> -------------------------
>
> Key: SPARK-58794
> URL: https://issues.apache.org/jira/browse/SPARK-58794
> Project: Spark
> Issue Type: Task
> Components: Spark Core
> Affects Versions: 5.0.0
> Reporter: Serge Rielau
> Priority: Major
> Attachments: SPARK-58794-char-varchar-design.zip
>
>
> This set of tasks will complete support for CHAR and VARCHAR beyond teh point
> solutions in spark so far.
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