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  1. Spark
  2. SPARK-6116 DataFrame API improvement umbrella ticket (Spark 1.5)
  3. SPARK-7990

Add methods to facilitate equi-join on multiple join keys

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    Details

    • Type: Sub-task
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: None
    • Fix Version/s: 1.5.0
    • Component/s: SQL
    • Labels:
      None
    • Target Version/s:
    • Sprint:
      Spark 1.5 doc/QA sprint

      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:

      def join(self, other, joinExprs=None, joinType=None):
      

      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

      def join(other: DataFrame, on: Seq[String], joinType: String): DataFrame
      

      and update the existing Scala one to call this one.

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              • Assignee:
                viirya L. C. Hsieh
                Reporter:
                rxin Reynold Xin
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                • Created:
                  Updated:
                  Resolved: