Spark Java - Merge same column multiple rows

Question

I'm using Java Spark and I have 1 Dataframe like this

+---+-----+------+
|id |color|datas |
+----------------+
|1  |blue  |data1|
|1  |red   |data2|
|1  |orange|data3|
|2  |black |data4|
|2  |      |data5|
|2  |yellow|     |
|3  |white |data7|
|3  |      |data8|
+----------------+

I need to modify this dataframe to look like this :

+---+--------------------+---------------------+
|id |color               |datas                |
+----------------------------------------------+
|1  |[blue, red, orange] |[data1, data2, data3]|
|2  |[black, yellow]     |[data4, data5]       |
|3  |[white]             |[data7, data8]       |
+----------------------------------------------+

I want to merge the data to create an 'array' of the same column but from differents rows based on the 'id' column.

I'm able to do it throught UserDefinedAggregateFunction but I can only do it one column at a time and it takes too much time to process.

Thank you

Edit : I'm using Spark 1.6

koiralo · Accepted Answer · 2017-05-23 10:25:20Z

2

you can group by "id" and then use collect_list function to get the aggregated values.

dataframe.groupBy("id").agg(collect_list(struct("color")).as("color"), collect_list(struct("dates")).as("dates") )

Hope this helps

answered May 23, 2017 at 10:25

koiralo

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4 Comments

Lucien Over a year ago

Thanks for the fast answer but unfortunately, I got a "org.apache.spark.sql.AnalysisException: undefined function collect_list" when I try with collect_list I'm using Spark 1.6

koiralo Over a year ago

did you import the function?? import static org.apache.spark.sql.functions.*;

Lucien Over a year ago

yes I did, I found this answer for the undefined function stackoverflow.com/questions/35324049/… I'm trying to solve it

koiralo Over a year ago

if you import function from spark sql it should work.

Gabriela Vaca Guzman G. · Accepted Answer · 2020-01-21 18:09:07Z

0

The actual function that works for me is:

dataframe.groupBy("id").agg(collect_list("color").as("color"), collect_list("date").as("date") ) dataframe.createOrReplaceTempView("dataframe")

Then create a new query where you can use the struct()

dffinal = spark.sql(s"""SELECT struct(a.color) AS colors, struct(a.date) AS dates FROM dataframe a """)

answered Jan 21, 2020 at 18:09

Gabriela Vaca Guzman G.

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