Apache Spark 2.3.0 - How to merge two array<string> into one array<string>

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I tried and googled but was not able to find the solution. Merging two array<string> into one array<string> is possible and easy in 2.4.x versions but could not find a way to do it in 2.3.0 version.

Input -

[[one, two, three], [four, five, six]]

Expected Output -

[ one, two, three, four, five, six]

Can anyone explain how this can be achieved in Spark using Java?

spark-java apache-spark-sql apache-spark
1 Answers

As new arrays functions were introduced in Spark 2.4, you have to go to user-defined function (udf).

User-defined functions in java are java objects with an apply method that can be used as a built-in function in dataframe transformation. To create such object, you first create an UDFx object, where x is the number of arguments of your udf.

Then you create your udf from this UDFx object, either by registering it with method sparkSession.sqlContext().register().udf() (only method available before Spark 2.3) or by creating it with function udf (for Spark 2.3 and greater) as described in this answer.

And finally you use it with function callUdf or directly using apply. So complete code for Spark 2.3 and above is as follow:

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.api.java.UDF1;
import org.apache.spark.sql.expressions.UserDefinedFunction;
import org.apache.spark.sql.types.DataTypes;
import scala.collection.Seq;

import java.util.stream.Collectors;

import static org.apache.spark.sql.functions.col;
import static org.apache.spark.sql.functions.udf;
import static scala.collection.JavaConverters.asScalaBuffer;
import static scala.collection.JavaConverters.seqAsJavaList;


public class Flattener {

  public static Dataset<Row> flattenArray(Dataset<Row> input, String columnName) {
    // define what your user-defined function do
    UDF1<Seq<Seq<String>>, Seq<String>> flattenArray = new UDF1<Seq<Seq<String>>, Seq<String>>() {
      @Override
      public Seq<String> call(Seq<Seq<String>> s) {
        return asScalaBuffer(
          seqAsJavaList(s)
            .stream()
            .flatMap(x -> seqAsJavaList(x).stream())
            .collect(Collectors.toList())
        ).toSeq();
      }
    };

    // convert it to user-defined function
    UserDefinedFunction flatten_array = udf(
      flattenArray, 
      DataTypes.createArrayType(DataTypes.StringType) // output type of your UDF
    );

    // apply your user-defined function
    return input.withColumn(columnName, flatten_array.apply(col(columnName)));
  }
}

Note: when working with sequence on java UDF, you need to use Scala Seq instead of java List as sequence input. To convert from one to another, look at JavaConverters scala class methods.

You can then call your flattenArray method on your dataframe:

Flattener.flattenArray(dataframe, "name_of_column_you_want_to_flatten");
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