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Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2015/06/01 06:30:17 UTC
[jira] [Updated] (SPARK-7990) Add methods to facilitate equi-join
on multiple join keys
[ https://issues.apache.org/jira/browse/SPARK-7990?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Reynold Xin updated SPARK-7990:
-------------------------------
Description:
We have a variant of the join function that facilitates equi-join on a single join key, but we don't have one to do it for multiple join keys.
This is the existing Python API:
{code}
def join(self, other, joinExprs=None, joinType=None):
{code}
I think we should rename joinExprs to "on", and joinType to "how" to match Pandas. And then the "on" column should support either a string, a join condition, a list of string, or a list of join condition ("and" together).
In order to support the Python API, we'd need to add a variant for Scala as well. I think we can add another join method that looks like
{code}
def join(other: DataFrame, on: Seq[String], joinType: String): DataFrame
{code}
and update the existing Scala one to call this one.
was:
We have a variant of the join function that facilitates equi-join on a single join key, but we don't have one to do it for multiple join keys.
This is the existing Python API:
{code}
def join(self, other, joinExprs=None, joinType=None):
{code}
I think we should rename joinExprs to "on", and joinType to "how" to match Pandas. And then the "on" column should support either a string, a join condition, a list of string, or a list of join condition.
In order to support the Python API, we'd need to add a variant for Scala as well. I think we can add another join method that looks like
{code}
def join(other: DataFrame, on: Seq[String], joinType: String): DataFrame
{code}
and update the existing Scala one to call this one.
> Add methods to facilitate equi-join on multiple join keys
> ---------------------------------------------------------
>
> Key: SPARK-7990
> URL: https://issues.apache.org/jira/browse/SPARK-7990
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Reporter: Reynold Xin
>
> We have a variant of the join function that facilitates equi-join on a single join key, but we don't have one to do it for multiple join keys.
> This is the existing Python API:
> {code}
> def join(self, other, joinExprs=None, joinType=None):
> {code}
> I think we should rename joinExprs to "on", and joinType to "how" to match Pandas. And then the "on" column should support either a string, a join condition, a list of string, or a list of join condition ("and" together).
> In order to support the Python API, we'd need to add a variant for Scala as well. I think we can add another join method that looks like
> {code}
> def join(other: DataFrame, on: Seq[String], joinType: String): DataFrame
> {code}
> and update the existing Scala one to call this one.
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