[ https://issues.apache.org/jira/browse/SPARK-10186?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Reynold Xin updated SPARK-10186: -------------------------------- Labels: (was: array json postgres sql struct) > Add support for more postgres column types > ------------------------------------------ > > Key: SPARK-10186 > URL: https://issues.apache.org/jira/browse/SPARK-10186 > Project: Spark > Issue Type: New Feature > Components: SQL > Affects Versions: 1.4.1 > Environment: Ubuntu on AWS > Reporter: Simeon Simeonov > > The specific observations below are based on Postgres 9.4 tables accessed via > the postgresql-9.4-1201.jdbc41.jar driver. However, based on the behavior, I > would expect the problem to exists for all external SQL databases. > - *json and jsonb columns generate {{java.sql.SQLException: Unsupported type > 1111}}*. While it is reasonable to not support dynamic schema discovery of > JSON columns automatically (it requires two passes over the data), a better > behavior would be to create a String column and return the JSON. > - *Array columns generate {{java.sql.SQLException: Unsupported type 2003}}*. > This is true even for simple types, e.g., {{text[]}}. A better behavior would > be be create an Array column. > - *Custom type columns are mapped to a String column.* This behavior is > harder to understand as the schema of a custom type is fixed and therefore > mappable to a Struct column. The automatic conversion to a string is also > inconsistent when compared to json and array column handling. > The exceptions are thrown by > {{org.apache.spark.sql.jdbc.JDBCRDD$.org$apache$spark$sql$jdbc$JDBCRDD$$getCatalystType(JDBCRDD.scala:100)}} > so this definitely looks like a Spark SQL and not a JDBC problem. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org