You are currently viewing How to Convert Struct type to Columns in Spark

I have a Spark DataFrame with StructType and would like to convert it to Columns, could you please explain how to do it?

Converting Struct type to columns is one of the most commonly used transformations in Spark DataFrame. In order to explain I will create the Spark DataFrame with Struct columns

val structureData = Seq(
    Row(Row("James ","","Smith"),Row(Row("CA","Los Angles"),Row("CA","Sandiago"))),
    Row(Row("Michael ","Rose",""),Row(Row("NY","New York"),Row("NJ","Newark"))),
    Row(Row("Robert ","","Williams"),Row(Row("DE","Newark"),Row("CA","Las Vegas"))),
    Row(Row("Maria ","Anne","Jones"),Row(Row("PA","Harrisburg"),Row("CA","Sandiago"))),
    Row(Row("Jen","Mary","Brown"),Row(Row("CA","Los Angles"),Row("NJ","Newark")))

val structureSchema = new StructType()
    .add("name",new StructType()
    .add("address",new StructType()
      .add("current",new StructType()
      .add("previous",new StructType()

val df = spark.createDataFrame(

From the above example, df.printSchema() yields the below output.

 |-- name: struct (nullable = true)
 |    |-- firstname: string (nullable = true)
 |    |-- middlename: string (nullable = true)
 |    |-- lastname: string (nullable = true)
 |-- address: struct (nullable = true)
 |    |-- current: struct (nullable = true)
 |    |    |-- state: string (nullable = true)
 |    |    |-- city: string (nullable = true)
 |    |-- previous: struct (nullable = true)
 |    |    |-- state: string (nullable = true)
 |    |    |-- city: string (nullable = true)

As you see, the above DataFrame schema consists of two struct columns name and address. Let’s convert name struct type these into columns.

val df2 ="name.*"),
val df2Flatten = df2.toDF("fname","mename","lname","currAddState",

The above example converts the Spark DataFrame struct column into multiple columns.

 |-- name_firstname: string (nullable = true)
 |-- name_middlename: string (nullable = true)
 |-- name_lastname: string (nullable = true)
 |-- address_current_state: string (nullable = true)
 |-- address_current_city: string (nullable = true)
 |-- address_previous_state: string (nullable = true)
 |-- address_previous_city: string (nullable = true)

|fname   |mename|lname   |currAddState|currAddCity|prevAddState|prevAddCity|
|James   |      |Smith   |CA          |Los Angles |CA          |Sandiago   |
|Michael |Rose  |        |NY          |New York   |NJ          |Newark     |
|Robert  |      |Williams|DE          |Newark     |CA          |Las Vegas  |
|Maria   |Anne  |Jones   |PA          |Harrisburg |CA          |Sandiago   |
|Jen     |Mary  |Brown   |CA          |Los Angles |NJ          |Newark     |

In case you wanted to Flatten many struct columns automatically, refer to this page.

Hope this helps !!

Naveen Nelamali

Naveen Nelamali (NNK) is a Data Engineer with 20+ years of experience in transforming data into actionable insights. Over the years, He has honed his expertise in designing, implementing, and maintaining data pipelines with frameworks like Apache Spark, PySpark, Pandas, R, Hive and Machine Learning. Naveen journey in the field of data engineering has been a continuous learning, innovation, and a strong commitment to data integrity. In this blog, he shares his experiences with the data as he come across. Follow Naveen @ LinkedIn and Medium