shivsood opened a new pull request #25146: Fix for SPARK-28152: ShortType and FloatTypes are not mapped correctly for read/write of SQLServer Tables URL: https://github.com/apache/spark/pull/25146 ShortType and FloatTypes are not correctly mapped to right JDBC types when using JDBC connector. This results in tables and spark data frame being created with unintended types. The issue was observed when validating against SQLServer. Some example issue - Write from df with column type results in a SQL table of with column type as INTEGER as opposed to SMALLINT. Thus a larger table that expected. - Read results in a dataframe with type INTEGER as opposed to ShortType FloatTypes have a issue with read path. In the write path Spark data type 'FloatType' is correctly mapped to JDBC equivalent data type 'Real'. But in the read path when JDBC data types need to be converted to Catalyst data types ( getCatalystType) 'Real' gets incorrectly gets mapped to 'DoubleType' rather than 'FloatType'. ## What changes were proposed in this pull request? Correct mappings added to MsSqlServerDialect.scala. ShortType is mapped to SMALLINT and FloatType is mapped to REAL (Please fill in changes proposed in this fix) ## How was this patch tested? UnitTest added in JDBCSuite.scala and these were tested. Integration test updated and passed in MsSqlServerDialect.scala E2E test done with SQLServer (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Please review https://spark.apache.org/contributing.html before opening a pull request.
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