Mohammed,
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.
Reynold,
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,
AARON ILOVICI
Software Engineer
Marketing Engineering
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From: Reynold Xin
Date: Thursday, May 26, 2016 at 6:11 PM
To: Mohammed Guller
Cc: Aaron Ilovici , "user@spark.apache.org"
, "d...@spark.apache.org"
Subject: Re: JDBC Dialect for saving DataFrame into Vertica Table
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
mailto:moham...@glassbeam.com>> 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?
Mohammed
Author: Big Data Analytics with
Spark<http://www.amazon.com/Big-Data-Analytics-Spark-Practitioners/dp/1484209656/>
From: Aaron Ilovici [mailto:ailov...@wayfair.com<mailto:ailov...@wayfair.com>]
Sent: Thursday, May 26, 2016 8:08 AM
To: user@spark.apache.org<mailto:user@spark.apache.org>;
d...@spark.apache.org<mailto:d...@spark.apache.org>
Subject: JDBC Dialect for saving DataFrame into Vertica Table
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,
AARON ILOVICI
Software Engineer
Marketing Engineering
[cid:image002.png@01D1B7F9.A3949B20]
WAYFAIR
4 Copley Place
Boston, MA 02116
(617) 532-6100 x1231
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