How to add new column to Spark dataframe using a Java UDF

Question

I have a Dataset<Row> inputDS which has 4 columns namely Id, List<long> time, List<String> value, aggregateType I want to add one more column to the Dataset value_new using map function, that map function takes columns time , value and aggregateType passes that to a function getAggregate(String aggregateType, List<long> time, List<String> value) and return a double value on processing the parameters. The Double value returned by the method getAggregate will be the new column value i.e value of value_new

Dataset inputDS

 +------+---+-----------+---------------------------------------------+---------------+
 |    Id| value         |     time                                   |aggregateType  |
 +------+---------------+---------------------------------------------+---------------+
 |0001  |  [1.5,3.4,4.5]| [1551502200000,1551502200000,1551502200000] | Sum           |
 +------+---------------+---------------------------------------------+---------------+

Expected Dataset outputDS

 +------+---------------+---------------------------------------------+---------------+-----------+
 |    Id| value         |     time                                    |aggregateType  | value_new |
 +------+---------------+---------------------------------------------+---------------+-----------+
 |0001  |  [1.5,3.4,4.5]| [1551502200000,1551502200000,1551502200000] | Sum           |   9.4     |
 +------+---------------+---------------------------------------------+---------------+-----------+

Code I tried.

 inputDS.withColumn("value_new",functions.lit(inputDS.map(new MapFunction<Row,Double>(){

 public double call(Row row){
 String aggregateType = row.getAS("aggregateType");
 List<long> timeList = row.getList("time");
 List<long> valueList= row.getList("value");  

 return  getAggregate(aggregateType ,timeList,valueList);    

 }}),Encoders.DOUBLE())));

ERROR

 Unsupported literal type class org.apache.spark.sql.Dataset [value:double]

Note Sorry if I used map function wrongly and please suggest me if there is any workaround.

Thank you.!

Sim · Accepted Answer · 2019-03-26 18:22:24Z

0

You get the error because you are trying to create a function literal (lit()) using the result of Dataset.map(), which you can see in docs is a Dataset. You can see in the API for Dataset.withColumn() that you need a argument that is a column.

It seems like you need to create a user-defined function. Take a look at How do I call a UDF on a Spark DataFrame using JAVA?

answered Mar 26, 2019 at 18:22

Sim

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