I am working on spark dataframes and I need to do a group by of a column and convert the column values of grouped rows into an array of elements as new column. Example :
Input:
employee | Address
------------------
Micheal | NY
Micheal | NJ
Output:
employee | Address
------------------
Micheal | (NY,NJ)
Any help is highly appreciated.!
Here is an alternate solution
Where I have converted the dataframe to an rdd for the transformations and converted it back a dataFrame using sqlContext.createDataFrame()
Sample.json
{"employee":"Michale","Address":"NY"}
{"employee":"Michale","Address":"NJ"}
{"employee":"Sam","Address":"NY"}
{"employee":"Max","Address":"NJ"}
Spark Application
val df = sqlContext.read.json("sample.json")
// Printing the original Df
df.show()
//Defining the Schema for the aggregated DataFrame
val dataSchema = new StructType(
Array(
StructField("employee", StringType, nullable = true),
StructField("Address", ArrayType(StringType, containsNull = true), nullable = true)
)
)
// Converting the df to rdd and performing the groupBy operation
val aggregatedRdd: RDD[Row] = df.rdd.groupBy(r =>
r.getAs[String]("employee")
).map(row =>
// Mapping the Grouped Values to a new Row Object
Row(row._1, row._2.map(_.getAs[String]("Address")).toArray)
)
// Creating a DataFrame from the aggregatedRdd with the defined Schema (dataSchema)
val aggregatedDf = sqlContext.createDataFrame(aggregatedRdd, dataSchema)
// Printing the aggregated Df
aggregatedDf.show()
Output :
+-------+--------+---+
|Address|employee|num|
+-------+--------+---+
| NY| Michale| 1|
| NJ| Michale| 2|
| NY| Sam| 3|
| NJ| Max| 4|
+-------+--------+---+
+--------+--------+
|employee| Address|
+--------+--------+
| Sam| [NY]|
| Michale|[NY, NJ]|
| Max| [NJ]|
+--------+--------+
If you're using Spark 2.0+, you can use collect_list or collect_set.
Your query will be something like (assuming your dataframe is called input):
import org.apache.spark.sql.functions._
input.groupBy('employee).agg(collect_list('Address))
If you are ok with duplicates, use collect_list. If you're not ok with duplicates and only need unique items in the list, use collect_set.
Hope this helps!
Input.groupBy(Input.col("employee")). You can take a look at spark API reference.collect_list()