How can I convert an array column to a string in PySpark?

In this PySpark article, I will explain how to convert an array of String column on DataFrame to a String column (separated or concatenated with a comma, space, or any delimiter character) using PySpark function concat_ws() (translates to concat with separator), and with SQL expression using Scala example.

When curating data on DataFrame we may want to convert the Dataframe with complex struct datatypes, arrays and maps to a flat structure. here we will see how to convert array type to string type.

Before we start, first let’s create a DataFrame with array of string column.

spark = SparkSession.builder.appName('SparkByExamples.com').getOrCreate()

columns = ["name","languagesAtSchool","currentState"]
data = [("James,,Smith",["Java","Scala","C++"],"CA"), 
    ("Michael,Rose,",["Spark","Java","C++"],"NJ"), 
    ("Robert,,Williams",["CSharp","VB"],"NV")]

df = spark.createDataFrame(data=data,schema=columns)
df.printSchema()
df.show(truncate=False)

In this example “languagesAtSchool” is a column of type array. In the next section, we will convert this to a String. This example yields below schema and DataFrame.

root
 |-- name: string (nullable = true)
 |-- languagesAtSchool: array (nullable = true)
 |    |-- element: string (containsNull = true)
 |-- currentState: string (nullable = true)

+----------------+------------------+------------+
|name            |languagesAtSchool |currentState|
+----------------+------------------+------------+
|James,,Smith    |[Java, Scala, C++]|CA          |
|Michael,Rose,   |[Spark, Java, C++]|NJ          |
|Robert,,Williams|[CSharp, VB]      |NV          |
+----------------+------------------+------------+

Convert an array of String to String column using concat_ws()

In order to convert array to a string, PySpark SQL provides a built-in function concat_ws() which takes delimiter of your choice as a first argument and array column (type Column) as the second argument.

Syntax

concat_ws(sep, *cols)

Usage

In order to use concat_ws() function, you need to import it using pyspark.sql.functions.concat_ws . Since this function takes the Column type as a second argument, you need to use col().

from pyspark.sql.functions import col, concat_ws
df2 = df.withColumn("languagesAtSchool",
   concat_ws(",",col("languagesAtSchool")))
df2.printSchema()
df2.show(truncate=False)

This yields below output

root
 |-- name: string (nullable = true)
 |-- languagesAtSchool: string (nullable = false)
 |-- currentState: string (nullable = true)

+----------------+-----------------+------------+
|name            |languagesAtSchool|currentState|
+----------------+-----------------+------------+
|James,,Smith    |Java,Scala,C++   |CA          |
|Michael,Rose,   |Spark,Java,C++   |NJ          |
|Robert,,Williams|CSharp,VB        |NV          |
+----------------+-----------------+------------+

Using PySpark SQL expression

You can also use concat_ws() function with SQL expression.

df.createOrReplaceTempView("ARRAY_STRING")
spark.sql("select name, concat_ws(',',languagesAtSchool) as languagesAtSchool," + 
    " currentState from ARRAY_STRING") 
    .show(truncate=False)

Complete Example

Below is a complete PySpark DataFrame example of converting an array of String column to a String using a Scala example.

import pyspark
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('SparkByExamples.com').getOrCreate()

columns = ["name","languagesAtSchool","currentState"]
data = [("James,,Smith",["Java","Scala","C++"],"CA"), 
    ("Michael,Rose,",["Spark","Java","C++"],"NJ"), 
    ("Robert,,Williams",["CSharp","VB"],"NV")]

df = spark.createDataFrame(data=data,schema=columns)
df.printSchema()
df.show(truncate=False)

from pyspark.sql.functions import col, concat_ws
df2 = df.withColumn("languagesAtSchool",
   concat_ws(",",col("languagesAtSchool")))
df2.printSchema()
df2.show(truncate=False)

df.createOrReplaceTempView("ARRAY_STRING")
spark.sql("select name, concat_ws(',',languagesAtSchool) as languagesAtSchool," + 
    " currentState from ARRAY_STRING") 
    .show(truncate=False)

This example is also available at the PySpark Github example project for reference.

Hope it helps you !! Thanks for reading.

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