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https://issues.apache.org/jira/browse/SPARK-31557?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17530477#comment-17530477
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Apache Spark commented on SPARK-31557:
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User 'bersprockets' has created a pull request for this issue:
https://github.com/apache/spark/pull/28345
> Legacy parser incorrectly interprets pre-Gregorian dates
> --------------------------------------------------------
>
> Key: SPARK-31557
> URL: https://issues.apache.org/jira/browse/SPARK-31557
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0, 3.1.0
> Reporter: Bruce Robbins
> Assignee: Bruce Robbins
> Priority: Major
> Fix For: 3.0.0
>
>
> With CSV:
> {noformat}
> scala> sql("set spark.sql.legacy.timeParserPolicy=LEGACY")
> res0: org.apache.spark.sql.DataFrame = [key: string, value: string]
> scala> val seq = Seq("0002-01-01", "1000-01-01", "1500-01-01",
> "1800-01-01").map(x => s"$x,$x")
> seq: Seq[String] = List(0002-01-01,0002-01-01, 1000-01-01,1000-01-01,
> 1500-01-01,1500-01-01, 1800-01-01,1800-01-01)
> scala> val ds = seq.toDF("value").as[String]
> ds: org.apache.spark.sql.Dataset[String] = [value: string]
> scala> spark.read.schema("expected STRING, actual DATE").csv(ds).show
> +----------+----------+
> | expected| actual|
> +----------+----------+
> |0002-01-01|0001-12-30|
> |1000-01-01|1000-01-06|
> |1500-01-01|1500-01-10|
> |1800-01-01|1800-01-01|
> +----------+----------+
> scala>
> {noformat}
> Similarly, with JSON:
> {noformat}
> scala> sql("set spark.sql.legacy.timeParserPolicy=LEGACY")
> res0: org.apache.spark.sql.DataFrame = [key: string, value: string]
> scala> val seq = Seq("0002-01-01", "1000-01-01", "1500-01-01",
> "1800-01-01").map { x =>
> s"""{"expected": "$x", "actual": "$x"}"""
> }
> | | seq: Seq[String] = List({"expected": "0002-01-01", "actual":
> "0002-01-01"}, {"expected": "1000-01-01", "actual": "1000-01-01"},
> {"expected": "1500-01-01", "actual": "1500-01-01"}, {"expected":
> "1800-01-01", "actual": "1800-01-01"})
> scala>
> scala> val ds = seq.toDF("value").as[String]
> ds: org.apache.spark.sql.Dataset[String] = [value: string]
> scala> spark.read.schema("expected STRING, actual DATE").json(ds).show
> +----------+----------+
> | expected| actual|
> +----------+----------+
> |0002-01-01|0001-12-30|
> |1000-01-01|1000-01-06|
> |1500-01-01|1500-01-10|
> |1800-01-01|1800-01-01|
> +----------+----------+
> scala>
> {noformat}
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