[jira] [Created] (SPARK-30608) Postgres Column Interval converts to string and cant be written back to postgres

["Sumit (Jira)" <ji...@apache.org>]

Sumit created SPARK-30608:
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             Summary: 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


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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