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https://issues.apache.org/jira/browse/SPARK-30608?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-30608.
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Resolution: Invalid
> Postgres Column Interval converts to string and cant be written back to
> postgres
> --------------------------------------------------------------------------------
>
> Key: SPARK-30608
> URL: https://issues.apache.org/jira/browse/SPARK-30608
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.4
> Reporter: Sumit
> Priority: Major
>
> If we read a "Interval" type column from postgres and try to save it back to
> postgres, an exception is occured as during read operation postgres column is
> converted to String and while saving back it gives an error
>
> java.sql.BatchUpdateException: Batch entry 0 INSERT INTO test_table
> ("dob","dob_time","dob_time_zone","duration") VALUES ('2019-05-29
> -04','2016-08-12 10:22:31.100000-04','2016-08-12 13:22:31.100000-04','3 days
> 10:00:00') was aborted: ERROR: column "duration" is of type interval but
> expression is of type character varying
> Hint: You will need to rewrite or cast the expression.
> Position: 86 Call getNextException to see other errors in the batch.
> at
> org.postgresql.jdbc.BatchResultHandler.handleError(BatchResultHandler.java:151)
> at
> org.postgresql.core.ResultHandlerDelegate.handleError(ResultHandlerDelegate.java:45)
> at
> org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2159)
> at
> org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:463)
> at org.postgresql.jdbc.PgStatement.executeBatch(PgStatement.java:794)
> at
> org.postgresql.jdbc.PgPreparedStatement.executeBatch(PgPreparedStatement.java:1662)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:672)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:834)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:834)
> at
> org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:935)
> at
> org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:935)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:123)
> at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
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