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Posted to user@spark.apache.org by JG Perrin <jp...@lumeris.com> on 2017/08/23 18:30:04 UTC

Joining 2 dataframes, getting result as nested list/structure in dataframe

Hi folks,

I am trying to join 2 dataframes, but I would like to have the result as a list of rows of the right dataframe (dDf in the example) in a column of the left dataframe (cDf in the example). I made it work with one column, but having issues adding more columns/creating a row(?).
    Seq<String> joinColumns = new Set2<>("c1", "c2").toSeq();
    Dataset<Row> allDf = cDf.join(dDf, joinColumns, "inner");
    allDf.printSchema();
    allDf.show();

    Dataset<Row> aggDf = allDf.groupBy(cDf.col("c1"), cDf.col("c2"))
            .agg(collect_list(col("c50")));
    aggDf.show();

Output:
+--------+-------+---------------------------+
|c1      |c2     |collect_list(c50)          |
+--------+-------+---------------------------+
|    3744|1160242|         [6, 5, 4, 3, 2, 1]|
|    3739|1150097|                        [1]|
|    3780|1159902|            [5, 4, 3, 2, 1]|
|     132|1200743|               [4, 3, 2, 1]|
|    3778|1183204|                        [1]|
|    3766|1132709|                        [1]|
|    3835|1146169|                        [1]|
+--------+-------+---------------------------+

Thanks,

jg

______________________________________________________________________
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RE: Joining 2 dataframes, getting result as nested list/structure in dataframe

Posted by JG Perrin <jp...@lumeris.com>.

Thanks Michael – this is a great article… very helpful

From: Michael Armbrust [mailto:michael@databricks.com]
Sent: Wednesday, August 23, 2017 4:33 PM
To: JG Perrin <jp...@lumeris.com>
Cc: user@spark.apache.org
Subject: Re: Joining 2 dataframes, getting result as nested list/structure in dataframe

You can create a nested struct that contains multiple columns using struct().

Here's a pretty complete guide on working with nested data: https://databricks.com/blog/2017/02/23/working-complex-data-formats-structured-streaming-apache-spark-2-1.html

On Wed, Aug 23, 2017 at 2:30 PM, JG Perrin <jp...@lumeris.com>> wrote:
Hi folks,

I am trying to join 2 dataframes, but I would like to have the result as a list of rows of the right dataframe (dDf in the example) in a column of the left dataframe (cDf in the example). I made it work with one column, but having issues adding more columns/creating a row(?).
    Seq<String> joinColumns = new Set2<>("c1", "c2").toSeq();
    Dataset<Row> allDf = cDf.join(dDf, joinColumns, "inner");
    allDf.printSchema();
    allDf.show();

    Dataset<Row> aggDf = allDf.groupBy(cDf.col("c1"), cDf.col("c2"))
            .agg(collect_list(col("c50")));
    aggDf.show();

Output:
+--------+-------+---------------------------+
|c1      |c2     |collect_list(c50)          |
+--------+-------+---------------------------+
|    3744|1160242|         [6, 5, 4, 3, 2, 1]|
|    3739|1150097|                        [1]|
|    3780|1159902|            [5, 4, 3, 2, 1]|
|     132|1200743|               [4, 3, 2, 1]|
|    3778|1183204|                        [1]|
|    3766|1132709|                        [1]|
|    3835|1146169|                        [1]|
+--------+-------+---------------------------+

Thanks,

jg

________________________________

This electronic transmission and any documents accompanying this electronic transmission contain confidential information belonging to the sender. This information may contain confidential health information that is legally privileged. The information is intended only for the use of the individual or entity named above. The authorized recipient of this transmission is prohibited from disclosing this information to any other party unless required to do so by law or regulation and is required to delete or destroy the information after its stated need has been fulfilled. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution or the taking of any action in reliance on or regarding the contents of this electronically transmitted information is strictly prohibited. If you have received this E-mail in error, please notify the sender and delete this message immediately.

Re: Joining 2 dataframes, getting result as nested list/structure in dataframe

Posted by Michael Armbrust <mi...@databricks.com>.

You can create a nested struct that contains multiple columns using
struct().

Here's a pretty complete guide on working with nested data:
https://databricks.com/blog/2017/02/23/working-complex-data-formats-structured-streaming-apache-spark-2-1.html

On Wed, Aug 23, 2017 at 2:30 PM, JG Perrin <jp...@lumeris.com> wrote:

> Hi folks,
>
>
>
> I am trying to join 2 dataframes, but I would like to have the result as a
> list of rows of the right dataframe (dDf in the example) in a column of the
> left dataframe (cDf in the example). I made it work with *one column*,
> but having issues adding more columns/creating a row(?).
>
>     Seq<String> joinColumns = new Set2<>("c1", "c2").toSeq();
>
>     Dataset<Row> allDf = cDf.join(dDf, joinColumns, "inner");
>
>     allDf.printSchema();
>
>     allDf.show();
>
>
>
>     Dataset<Row> aggDf = allDf.groupBy(cDf.col("c1"), cDf.col("c2"))
>
>             .agg(collect_list(col("c50")));
>
>     aggDf.show();
>
>
>
> Output:
>
> +--------+-------+---------------------------+
>
> |c1      |c2     |collect_list(c50)          |
>
> +--------+-------+---------------------------+
>
> |    3744|1160242|         [6, 5, 4, 3, 2, 1]|
>
> |    3739|1150097|                        [1]|
>
> |    3780|1159902|            [5, 4, 3, 2, 1]|
>
> |     132|1200743|               [4, 3, 2, 1]|
>
> |    3778|1183204|                        [1]|
>
> |    3766|1132709|                        [1]|
>
> |    3835|1146169|                        [1]|
>
> +--------+-------+---------------------------+
>
>
>
> Thanks,
>
>
>
> jg
>
>
> ------------------------------
>
> This electronic transmission and any documents accompanying this
> electronic transmission contain confidential information belonging to the
> sender. This information may contain confidential health information that
> is legally privileged. The information is intended only for the use of the
> individual or entity named above. The authorized recipient of this
> transmission is prohibited from disclosing this information to any other
> party unless required to do so by law or regulation and is required to
> delete or destroy the information after its stated need has been fulfilled.
> If you are not the intended recipient, you are hereby notified that any
> disclosure, copying, distribution or the taking of any action in reliance
> on or regarding the contents of this electronically transmitted information
> is strictly prohibited. If you have received this E-mail in error, please
> notify the sender and delete this message immediately.
>