Spark java: agg on multiple columns and rename them

I want to do a group by on my dataset on multiple columns that I don't know them from before hand, so the .agg() allow to pass a Map where the key is column name and the value is the aggreation name, for example I can do this:

    for(String column:columns)
        map.put(column, "sum");
    ds.groupBy("someColumn").agg(map)

It's good till here, but I want to keep the original columns name and not having something like this

'|sum(column1)|sum(column12)|...'

I have tried to do this but it didn't work:

map.put(column, "sum alias " + column);

Is it possible to do this with java api?

Try this-

I've provided the column name as alias to sum(column)

    Dataset<Row> df = spark.range(2).withColumn("value", lit(2));
        df.show(false);
        df.printSchema();

        /**
         * +---+-----+
         * |id |value|
         * +---+-----+
         * |0  |2    |
         * |1  |2    |
         * +---+-----+
         *
         * root
         *  |-- id: long (nullable = false)
         *  |-- value: integer (nullable = false)
         */
        Map<String, String> map = new HashMap<>();
        for(String column:df.columns())
            map.put(column, "sum");

        List<Column> cols = map.entrySet().stream().map(c -> expr(String.format("%s(%s) as %s", c.getValue(), c.getKey(), c.getKey())))
                .collect(Collectors.toList());


        df.agg(cols.get(0), toScalaSeq(cols.subList(1, cols.size()))).show(false);
        /**
         * +---+-----+
         * |id |value|
         * +---+-----+
         * |1  |4    |
         * +---+-----+
         */

Utility-

 <T> Buffer<T> toScalaSeq(List<T> list) {
        return JavaConversions.asScalaBuffer(list);
    }