[GitHub] spark pull request #23235: [SPARK-26151][SQL][FOLLOWUP] Return partial resul...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/23235 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #23235: [SPARK-26151][SQL][FOLLOWUP] Return partial resul...
Github user MaxGekk commented on a diff in the pull request: https://github.com/apache/spark/pull/23235#discussion_r239055208 --- Diff: docs/sql-migration-guide-upgrade.md --- @@ -35,6 +35,8 @@ displayTitle: Spark SQL Upgrading Guide - Since Spark 3.0, CSV datasource uses java.time API for parsing and generating CSV content. New formatting implementation supports date/timestamp patterns conformed to ISO 8601. To switch back to the implementation used in Spark 2.4 and earlier, set `spark.sql.legacy.timeParser.enabled` to `true`. + - In Spark version 2.4 and earlier, CSV datasource converts a malformed CSV string to a row with all `null`s in the PERMISSIVE mode if specified schema is `StructType`. Since Spark 3.0, returned row can contain non-`null` fields if some of CSV column values were parsed and converted to desired types successfully. --- End diff -- you are right. I will remove the part about `StructType` --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #23235: [SPARK-26151][SQL][FOLLOWUP] Return partial resul...
Github user HyukjinKwon commented on a diff in the pull request: https://github.com/apache/spark/pull/23235#discussion_r239049825 --- Diff: docs/sql-migration-guide-upgrade.md --- @@ -35,6 +35,8 @@ displayTitle: Spark SQL Upgrading Guide - Since Spark 3.0, CSV datasource uses java.time API for parsing and generating CSV content. New formatting implementation supports date/timestamp patterns conformed to ISO 8601. To switch back to the implementation used in Spark 2.4 and earlier, set `spark.sql.legacy.timeParser.enabled` to `true`. + - In Spark version 2.4 and earlier, CSV datasource converts a malformed CSV string to a row with all `null`s in the PERMISSIVE mode if specified schema is `StructType`. Since Spark 3.0, returned row can contain non-`null` fields if some of CSV column values were parsed and converted to desired types successfully. --- End diff -- Ah, `from_csv` and `to_csv` are added in 3.0 so it's intentionally not mentioned. BTW, I think CSV functionalities can only have `StructType` so maybe we don't have to mention. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #23235: [SPARK-26151][SQL][FOLLOWUP] Return partial resul...
GitHub user MaxGekk opened a pull request: https://github.com/apache/spark/pull/23235 [SPARK-26151][SQL][FOLLOWUP] Return partial results for bad CSV records ## What changes were proposed in this pull request? Updated SQL migration guide according to changes in https://github.com/apache/spark/pull/23120 You can merge this pull request into a Git repository by running: $ git pull https://github.com/MaxGekk/spark-1 failuresafe-partial-result-followup Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/23235.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #23235 commit 8c115f7871d4db66b13ee21ea3a1231f7153791e Author: Maxim Gekk Date: 2018-12-05T12:13:26Z Updating the migration guide --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
