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Apache Spark commented on SPARK-36490: -------------------------------------- User 'sarutak' has created a pull request for this issue: https://github.com/apache/spark/pull/33719 > Make from_csv/to_csv to handle timestamp_ntz type properly > ---------------------------------------------------------- > > Key: SPARK-36490 > URL: https://issues.apache.org/jira/browse/SPARK-36490 > Project: Spark > Issue Type: Sub-task > Components: SQL > Affects Versions: 3.3.0 > Reporter: Kousuke Saruta > Assignee: Kousuke Saruta > Priority: Major > > In the current master, to_csv/from_csv can handle timestamp type like as > follows. > {code} > SELECT to_csv(struct(TIMESTAMP"2021-11-23 11:22:33")); > 2021-11-23T11:22:33.000+09:00 > SELECT from_csv("2021-11-23 11:22:33", "a TIMESTAMP"); > {"a":2021-11-23 11:22:33} > {code} > But they cannot handle timestamp_ntz type properly. > {code} > SELECT to_csv(struct(TIMESTAMP_NTZ"2021-11-23 11:22:33")); > -- 2021-11-23T11:22:33.000 is expected. > 1637666553000000 > SELECT from_csv("2021-11-23 11:22:33", "a TIMESTAMP_NTZ"); > 21/08/12 16:12:49 ERROR SparkSQLDriver: Failed in [SELECT > from_csv("2021-11-23 11:22:33", "a TIMESTAMP_NTZ")] > java.lang.Exception: Unsupported type: timestamp_ntz > at > org.apache.spark.sql.errors.QueryExecutionErrors$.unsupportedTypeError(QueryExecutionErrors.scala:777) > at > org.apache.spark.sql.catalyst.csv.UnivocityParser.makeConverter(UnivocityParser.scala:234) > at > org.apache.spark.sql.catalyst.csv.UnivocityParser.$anonfun$valueConverters$1(UnivocityParser.scala:134) > {code} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org