SparkSQL and explode on DataFrame in Java

Question

Is there an easy way how use explode on array column on SparkSQL DataFrame? It's relatively simple in Scala, but this function seems to be unavailable (as mentioned in javadoc) in Java.

An option is to use SQLContext.sql(...) and explode function inside the query, but I'm looking for a bit better and especially cleaner way. DataFrames are loaded from parquet files.

Answer 1

I solved it in this manner: say that you have an array column containing job descriptions named "positions", for each person with "fullName".

Then you get from initial schema :

root
|-- fullName: string (nullable = true)
|-- positions: array (nullable = true)
    |    |-- element: struct (containsNull = true)
    |    |    |-- companyName: string (nullable = true)
    |    |    |-- title: string (nullable = true)
...

to schema:

root
 |-- personName: string (nullable = true)
 |-- companyName: string (nullable = true)
 |-- positionTitle: string (nullable = true)

by doing:

    DataFrame personPositions = persons.select(persons.col("fullName").as("personName"),
          org.apache.spark.sql.functions.explode(persons.col("positions")).as("pos"));

    DataFrame test = personPositions.select(personPositions.col("personName"),
    personPositions.col("pos").getField("companyName").as("companyName"), personPositions.col("pos").getField("title").as("positionTitle"));

Answer 2

It seems it is possible to use a combination of org.apache.spark.sql.functions.explode(Column col) and DataFrame.withColumn(String colName, Column col) to replace the column with the exploded version of it.