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https://issues.apache.org/jira/browse/SPARK-48215?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Uroš Bojanić updated SPARK-48215:
---------------------------------
Description:
Enable collation support for the *DateFormatClass* built-in function in Spark.
First confirm what is the expected behaviour for this expression when given
collated strings, and then move on to implementation and testing. You will find
this expression in the *datetimeExpressions.scala* file, and it should be
considered a pass-through function with respect to collation awareness.
Implement the corresponding E2E SQL tests (CollationSQLExpressionsSuite) to
reflect how this function should be used with collation in SparkSQL, and feel
free to use your chosen Spark SQL Editor to experiment with the existing
functions to learn more about how they work. In addition, look into the
possible use-cases and implementation of similar functions within other other
open-source DBMS, such as [PostgreSQL|https://www.postgresql.org/docs/].
The goal for this Jira ticket is to implement the *DateFormatClass* expression
so that it supports all collation types currently supported in Spark. To
understand what changes were introduced in order to enable full collation
support for other existing functions in Spark, take a look at the Spark PRs and
Jira tickets for completed tasks in this parent (for example: Ascii, Chr,
Base64, UnBase64, Decode, StringDecode, Encode, ToBinary, FormatNumber,
Sentences).
Read more about ICU [Collation Concepts|http://example.com/] and
[Collator|http://example.com/] class. Also, refer to the Unicode Technical
Standard for string
[collation|https://www.unicode.org/reports/tr35/tr35-collation.html#Collation_Type_Fallback].
> DateFormatClass (all collations)
> --------------------------------
>
> Key: SPARK-48215
> URL: https://issues.apache.org/jira/browse/SPARK-48215
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 4.0.0
> Reporter: Uroš Bojanić
> Priority: Major
>
> Enable collation support for the *DateFormatClass* built-in function in
> Spark. First confirm what is the expected behaviour for this expression when
> given collated strings, and then move on to implementation and testing. You
> will find this expression in the *datetimeExpressions.scala* file, and it
> should be considered a pass-through function with respect to collation
> awareness. Implement the corresponding E2E SQL tests
> (CollationSQLExpressionsSuite) to reflect how this function should be used
> with collation in SparkSQL, and feel free to use your chosen Spark SQL Editor
> to experiment with the existing functions to learn more about how they work.
> In addition, look into the possible use-cases and implementation of similar
> functions within other other open-source DBMS, such as
> [PostgreSQL|https://www.postgresql.org/docs/].
>
> The goal for this Jira ticket is to implement the *DateFormatClass*
> expression so that it supports all collation types currently supported in
> Spark. To understand what changes were introduced in order to enable full
> collation support for other existing functions in Spark, take a look at the
> Spark PRs and Jira tickets for completed tasks in this parent (for example:
> Ascii, Chr, Base64, UnBase64, Decode, StringDecode, Encode, ToBinary,
> FormatNumber, Sentences).
>
> Read more about ICU [Collation Concepts|http://example.com/] and
> [Collator|http://example.com/] class. Also, refer to the Unicode Technical
> Standard for string
> [collation|https://www.unicode.org/reports/tr35/tr35-collation.html#Collation_Type_Fallback].
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