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Nebojsa Savic commented on SPARK-48215: --------------------------------------- Starting work. > 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]. -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org