Reputation: 109
I have a column in my Dataset<Row>
that contains WrappedArray<WrappedArray<Double>>
. I am passing this column to an UDF
to pull out one of the values.
How would I go about getting access to the Doubles in this nested structure?
I want to do something like this :
sparkSession.udf().register(ADD_START_TOTAL, (UDF1<WrappedArray<WrappedArray<Double>>, Double>) (totals) -> totals[0][1], DataTypes.DoubleType);
Here is an example of what the column looks like when I invoke Dataset.show()
method my Dataset looks like below.
[WrappedArray(2.0...
EDIT: Found this post How to cast a WrappedArray[WrappedArray[Float]] to Array[Array[Float]] in spark (scala) but not sure how to translate this to Java.
Upvotes: 4
Views: 2542
Reputation: 15297
Consider your Dataset<Row> ds1
has value
column with following schema
root
|-- value: array (nullable = true)
| |-- element: array (containsNull = true)
| | |-- element: double (containsNull = false)
Define your UDF1
function like below.
static UDF1<WrappedArray<WrappedArray<Double>>, List<Double>> getValue = new UDF1<WrappedArray<WrappedArray<Double>>, List<Double>>() {
public List<Double> call(WrappedArray<WrappedArray<Double>> data) throws Exception {
List<Double> doubleList = new ArrayList<Double>();
for(int i=0; i<data.size(); i++){
doubleList.addAll(JavaConversions.seqAsJavaList(data.apply(i)));
}
return doubleList;
}
}
Now Register and Call UDF1
function like below.
import static org.apache.spark.sql.functions.col;
import static org.apache.spark.sql.functions.callUDF;
import scala.collection.JavaConversions;
// register UDF
spark.udf().register("getValue", getValue, DataTypes.createArrayType(DataTypes.DoubleType));
// Call UDF
Dataset<Row> ds2 = ds1.select(col("*"), callUDF("getValue", col("value")).as("udf-value"));
ds2.show(false);
Upvotes: 5