You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Yuechen Chen (JIRA)" <ji...@apache.org> on 2017/12/16 06:37:00 UTC
[jira] [Updated] (SPARK-22814) JDBC support date/timestamp type as
partitionColumn
[ https://issues.apache.org/jira/browse/SPARK-22814?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Yuechen Chen updated SPARK-22814:
---------------------------------
External issue URL: https://github.com/apache/spark/pull/19999
> JDBC support date/timestamp type as partitionColumn
> ---------------------------------------------------
>
> Key: SPARK-22814
> URL: https://issues.apache.org/jira/browse/SPARK-22814
> Project: Spark
> Issue Type: Improvement
> Components: Input/Output
> Affects Versions: 1.6.2, 2.2.1
> Reporter: Yuechen Chen
> Original Estimate: 168h
> Remaining Estimate: 168h
>
> In spark, you can partition MySQL queries by partitionColumn.
> val df = (spark.read.jdbc(url=jdbcUrl,
> table="employees",
> columnName="emp_no",
> lowerBound=1L,
> upperBound=100000L,
> numPartitions=100,
> connectionProperties=connectionProperties))
> display(df)
> But, partitionColumn must be a numeric column from the table.
> However, there are lots of table, which has no primary key, and has some date/timestamp indexes.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org