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https://issues.apache.org/jira/browse/SPARK-22814?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16833145#comment-16833145
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Al Johri edited comment on SPARK-22814 at 5/4/19 7:37 PM:
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Cross posting my Github
[comment|https://github.com/apache/spark/pull/21834#issuecomment-489357987]
here: looks like this feature does not work with PySpark 2.4.0.
was (Author: al.johri):
Cross posting my Github
[comment]([https://github.com/apache/spark/pull/21834#issuecomment-489357987])
here: looks like this feature does not work with PySpark 2.4.0.
> 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: SQL
> Affects Versions: 1.6.2, 2.2.1
> Reporter: Yuechen Chen
> Assignee: Takeshi Yamamuro
> Priority: Major
> Fix For: 2.4.0
>
> 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.
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