[SPARK-26151][SQL][FOLLOWUP] Return partial results for bad CSV records #23235
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@cloud-fan Please, have a look at the PR. |
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Test build #99720 has finished for PR 23235 at commit
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HyukjinKwon
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Dec 5, 2018
docs/sql-migration-guide-upgrade.md
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| - 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`. | ||
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| - 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. |
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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.
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you are right. I will remove the part about StructType
HyukjinKwon
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Dec 5, 2018
cloud-fan
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Dec 5, 2018
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Test build #99728 has finished for PR 23235 at commit
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thanks, merging to master! |
jackylee-ch
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Feb 18, 2019
## What changes were proposed in this pull request? Updated SQL migration guide according to changes in apache#23120 Closes apache#23235 from MaxGekk/failuresafe-partial-result-followup. Lead-authored-by: Maxim Gekk <maxim.gekk@databricks.com> Co-authored-by: Maxim Gekk <max.gekk@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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What changes were proposed in this pull request?
Updated SQL migration guide according to changes in #23120