The Spark Connector for Vertica is still in Beta and while that is still an option I would prefer native support from Spark. Considering all data types seem to map with the aggregated dialect except for NULL types, I imagine the work involved would be relatively minimal. I would be happy to code it out and submit a pull request, but I a question about the dialect:
- Are NULL data types implicitly defined somewhere? I don’t see NULL cases in the other dialects.
I have come up with answers to the other questions below, and found Java->Vertica data type conversions. The only piece I am missing is the NULL value, which is the root of the necessity to have this dialect in the first place.
I agree. Vertica seemed to have a MVP GA, then make it performant in later releases, so I doubt the performance loss would be drastic.
Thank you for any help,
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It's probably a good idea to have the vertica dialect too, since it doesn't seem like it'd be too difficult to maintain. It is not going to be as performant as the native Vertica data source, but is going to be much lighter weight.
On Thu, May 26, 2016 at 3:09 PM, Mohammed Guller <firstname.lastname@example.org> wrote:
Vertica also provides a Spark connector. It was not GA the last time I looked at it, but available on the Vertica community site. Have you tried using the Vertica Spark connector instead of the JDBC driver?
Author: Big Data Analytics with Spark
I am attempting to write a DataFrame of Rows to Vertica via DataFrameWriter's jdbc function in the following manner:
dataframe.write().mode(SaveMode.Append).jdbc(url, table, properties);
This works when there are no NULL values in any of the Rows in my DataFrame. However, when there are rows, I get the following error:
ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 24)
java.sql.SQLFeatureNotSupportedException: [Vertica][JDBC](10220) Driver not capable.
at com.vertica.exceptions.ExceptionConverter.toSQLException(Unknown Source)
at com.vertica.jdbc.common.SPreparedStatement.checkTypeSupported(Unknown Source)
at com.vertica.jdbc.common.SPreparedStatement.setNull(Unknown Source)
This appears to be Spark's attempt to set a null value in a PreparedStatement, but Vertica does not understand the type upon executing the transaction. I see in JdbcDialects.scala that there are dialects for MySQL, Postgres, DB2, MsSQLServer, Derby, and Oracle.
1 - Would writing a dialect for Vertica eleviate the issue, by setting a 'NULL' in a type that Vertica would understand?
2 - What would be the best way to do this without a Spark patch? Scala, Java, make a jar and call 'JdbcDialects.registerDialect(VerticaDialect)' once created?
3 - Where would one find the proper mapping between Spark DataTypes and Vertica DataTypes? I don't see 'NULL' handling for any of the dialects, only the base case 'case _ => None' - is None mapped to the proper NULL type elsewhere?
My environment: Spark 1.6, Vertica Driver 7.2.2, Java 1.7
I would be happy to create a Jira and submit a pull request with the VerticaDialect once I figure this out.
Thank you for any insight on this,
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