Split array struct to single value column Spark scala

Question

I have a dataframe with single array struct column where I want to split the nested values and added as a comma separated string new column(s) Example dataframe: tests

{id:1,name:foo},{id:2,name:bar}

Expected result dataframe

tests                            tests_id  tests_name
[id:1,name:foo],[id:2,name:bar]  1, 2     foo, bar

I tried the below code but got an error

df.withColumn("tests_name", concat_ws(",", explode(col("tests.name"))))

Error:

org.apache.spark.sql.AnalysisException: Generators are not supported when it's nested in expressions, but got: concat_ws(,, explode(tests.name AS `name`));

can you share the schema of dataframe, what version of spark are you using? — koiralo
– koiralo, Commented Jun 22, 2020 at 14:54

koiralo · Accepted Answer · 2020-06-22 15:09:50Z

Depends on the Spark version you are using. Assuming the dataframe scheme as below

root
 |-- test: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- id: long (nullable = true)
 |    |    |-- name: string (nullable = true)

Spark 3.0.0

df.withColumn("id", concat_ws(",", transform($"test", x => x.getField("id"))))
  .withColumn("name", concat_ws(",", transform($"test", x => x.getField("name"))))
.show(false)

Spark 2.4.0+

df.withColumn("id", concat_ws(",", expr("transform(test, x -> x.id)")))
.withColumn("name", concat_ws(",", expr("transform(test, x -> x.name)")))
.show(false)

Spark < 2.4

val extract_id = udf((test: Seq[Row]) => test.map(_.getAs[Long]("id")))
val extract_name = udf((test: Seq[Row]) => test.map(_.getAs[String]("name")))

df.withColumn("id", concat_ws(",", extract_id($"test")))
  .withColumn("name", concat_ws(",", extract_name($"test")))
  .show(false)

Output:

+--------------------+---+-------+
|test                |id |name   |
+--------------------+---+-------+
|[[1, foo], [2, bar]]|1,2|foo,bar|
|[[3, foo], [4, bar]]|3,4|foo,bar|
+--------------------+---+-------+

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