Spark explode multiple columns. So I'm going to start here by showing the data.
Spark explode multiple columns This will flatten the lists in the specified column, creating multiple rows where each list element gets its own row. In this video, we dive into the powerful capabilities of Spark SQL, focusing on the technique of exploding multiple columns within your datasets. Sep 3, 2018 · 3 You can first make all columns struct -type by explode -ing any Array(struct) columns into struct columns via foldLeft, then use map to interpolate each of the struct column names into col. Basically I have data that looks like: What I want is - for each column, take the nth element of the array in that column and add that to a new row. Jul 14, 2025 · Nested structures like arrays and maps are common in data analytics and when working with API requests or responses. points)) This particular example explodes the arrays in the points column of a DataFrame into multiple rows. Learn how to work with complex nested data in Apache Spark using explode functions to flatten arrays and structs with beginner-friendly examples. column. What we will do is store column names of the data frame in a new data frame column by using explode () function Jul 16, 2019 · I have a dataframe (with more rows and columns) as shown below. Jan 17, 2022 · Spark Scala - How to explode a column into multiple rows in spark scala Asked 3 years, 10 months ago Modified 3 years, 10 months ago Viewed 6k times The column holding the array of multiple records is exploded into multiple rows by using the LATERAL VIEW clause with the explode () function. Flatten function combines nested arrays into a single, flat array. From below example column “subjects” is an array of ArraType which holds subjects learned. . The column holding the array of multiple records is exploded into multiple rows by using the LATERAL VIEW clause with the explode () function. Using explode, we will get a new row for each element in the array. Column ¶ Returns a new row for each element in the given array or map. How can I explode multiple columns pairs into multiple rows? I have a dataframe with the following client, type, address, type_2, address_2 abc, home, 123 Street, business, 456 Street I w Mar 27, 2024 · 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 May 24, 2022 · Spark essentials — explode and explode_outer in Scala tl;dr: Turn an array of data in one row to multiple rows of non-array data. functions import explode,map_keys,col I found the answer in this link How to explode StructType to rows from json dataframe in Spark rather than to columns but that is scala spark and not pyspark. Jul 29, 2017 · There was a question regarding this issue here: Explode (transpose?) multiple columns in Spark SQL table Suppose that we have extra columns as below: **userId someString varA varB Aug 21, 2017 · I needed to unlist a 712 dimensional array into columns in order to write it to csv. This article was written with Scala 2. e. May 24, 2025 · In this post, we’ll cover everything you need to know about four important PySpark functions: explode(), explode_outer(), posexplode(), and posexplode_outer(). Oct 13, 2025 · Use explode_outer() to retain rows even when arrays or maps are null or empty. Operating on these array columns can be challenging. Apr 27, 2025 · Sources: All files Summary Explode and flatten operations are essential tools for working with complex, nested data structures in PySpark: Explode functions transform arrays or maps into multiple rows, making nested data easier to analyze. I used @MaFF's solution first for my problem but that seemed to cause a lot of errors and additional computation time. Sep 28, 2021 · The approach uses explode to expand the list of string elements in array_column before splitting each string element using : into two different columns col_name and col_val respectively. Jun 8, 2017 · I have a dataset in the following way: FieldA FieldB ArrayField 1 A {1,2,3} 2 B {3,5} I would like to explode the data on ArrayField so the output will look i Oct 13, 2025 · Solution: PySpark explode function can be used to explode an Array of Array (nested Array) ArrayType(ArrayType(StringType)) columns to rows on PySpark DataFrame using python example. x, I think what you are looking for is the pivot operation on the spark dataframe. So I'm going to start here by showing the data. Introduced as part of PySpark’s SQL functions (pyspark. These functions help you convert array or map columns into multiple rows, which is essential when working with nested data. functions), explode takes a column containing arrays—e. PySpark: Dataframe Explode Explode function can be used to flatten array column values into rows in Pyspark. sql import SQLContext from pyspark. pyspark. PySpark explode () Function The PySpark explode() function creates a new row for each element in an array or map column. Refer official documentation here. *, as shown below: Nov 20, 2024 · Learn the syntax of the explode function of the SQL language in Databricks SQL and Databricks Runtime. Feb 19, 2025 · To explode a single column in a Polars DataFrame, you can use the explode() method, specifying the column you want to explode. Whether you're working with complex data Aug 15, 2023 · Apache Spark built-in function that takes input as an column object (array or map type) and returns a new row for each element in the given array or map type column. The explode function in Spark DataFrames transforms columns containing arrays or maps into multiple rows, generating one row per element while duplicating the other columns in the DataFrame. explode # pyspark. It is widely used when working with nested JSON or complex data types. explode(col: ColumnOrName) → pyspark. Jul 23, 2025 · Output: Method 3: Using explode () function The function that is used to explode or create array or map columns to rows is known as explode () function. explode ¶ pyspark. functions. See full list on sparkbyexamples. Jul 23, 2025 · There are a few reasons why we might want to split a struct column into multiple columns in a DataFrame: Ease of Use: Struct columns can be difficult to work with, especially when we need to access individual fields within the struct. Before we start, let’s create a DataFrame with a nested array column. You can use multiple explode() functions to expand multiple columns. This tutorial will explain multiple workarounds to flatten (explode) 2 or more array columns in PySpark. This tutorial will explain following explode methods available in Pyspark to flatten (explode) array column, click on item in the below list and it will take you to the respective section of the page: explode posexplode explode_outer posexplode_outer explode & posexplode functions will Spark: explode function The explode() function in Spark is used to transform an array or map column into multiple rows. I need to unpack the array values into rows so I can list the distinct values. The “explode” function takes an array column as input and returns a new row for each element in the array. Examples Sometimes your PySpark DataFrame will contain array-typed columns. Nov 29, 2024 · By using Pandas DataFrame explode() function you can transform or modify each element of a list-like to a row (single or multiple columns), replicating the index values. This article shows you how to flatten or explode a * StructType *column to multiple columns using Spark SQL. I am not sure what was causing it, but I used a different method which reduced the computation time considerably (22 minutes compared to more than 4 hours)! Method by @MaFF's: Sep 1, 2016 · How would I do something similar with the department column (i. 2. Uses the default column name col for elements in the array and key and value for elements in the map unless specified otherwise. 12 and Spark 3. add two additional columns to the dataframe called "id" and "name")? The methods aren't exactly the same, and I can only figure out how to create a brand new data frame using: Nov 20, 2024 · Learn the syntax of the explode function of the SQL language in Databricks SQL and Databricks Runtime. from_json For parsing json string we'll use from_json () SQL function to parse the Mar 27, 2018 · I have a spark dataframe looks like: id DataArray a array(3,2,1) b array(4,2,1) c array(8,6,1) d array(8,2,4) I want to transform this dataframe into: id col1 col2 col3 a Oct 5, 2020 · explode column with comma separated string in Spark SQL Asked 5 years, 1 month ago Modified 4 years, 4 months ago Viewed 10k times. What Does the explode Function Do? The explode function in Spark is designed to transform an array or map column into multiple rows, effectively “flattening” the nested structure. I am attaching a sample dataframe in similar schema and structure below. functions import explode #explode points column into rows df_new = df. Dec 23, 2022 · I have a table where the array column (cities) contains multiple arrays and some have multiple duplicate values. Fortunately, PySpark provides two handy functions – explode() and explode_outer() – to convert array columns into expanded rows to make your life easier! Jul 23, 2025 · In this article, we are going to discuss how to parse a column of json strings into their own separate columns. I've tried mapping an explode accross all columns in the dataframe, but that doesn't seem to work either: Jun 28, 2018 · Pyspark: explode json in column to multiple columns Asked 7 years, 5 months ago Modified 8 months ago Viewed 88k times Oct 27, 2022 · How can I explode multiple array columns with variable lengths and potential nulls? My input data looks like this: Nov 8, 2023 · You can use the following syntax to explode a column that contains arrays in a PySpark DataFrame into multiple rows: from pyspark. It is better to explode them separately and take distinct values each time. Name age subject parts xxxx 21 Maths,Physics I yyyy 22 English,French I,II I am trying to explode the above dataframe in both su Nov 29, 2017 · Assuming you are using Spark 2. from pyspark. explode(col) [source] # Returns a new row for each element in the given array or map. Split Multiple Array Columns into Rows To split multiple array column data into rows Pyspark provides a function called explode (). *, as shown below: Oct 29, 2021 · I have the below spark dataframe. Spark offers two powerful functions to help with this: explode() and posexplode(). com Jul 23, 2025 · Working with the array is sometimes difficult and to remove the difficulty we wanted to split those array data into rows. The main query then joins the original table to the CTE on id so we can combine original simple columns with exploded simple columns from the nested array. Understanding their syntax and parameters is key to using them effectively. First you could create a table with just 2 columns, the 2 letter encoding and the rest of the content in another column. Each element in the array or map becomes a separate row in the resulting DataFrame. Splitting the struct column into separate columns makes it easier to access and manipulate the data. functions import explode sqlc = SQLContext( Jun 9, 2024 · Splitting Multiple Array Columns into Rows To split multiple array columns into rows, we can use the PySpark function “explode”. , lists, JSON arrays—and Jul 9, 2022 · In Spark, we can create user defined functions to convert a column to a StructType. Jun 13, 2021 · And I would like to explode multiple columns at once, keeping the old column names in a new column, such as: Jan 19, 2025 · Enter Spark’s explode function—a simple yet powerful tool that can make your life much easier when dealing with nested columns. Jun 28, 2018 · When Exploding multiple columns, the above solution comes in handy only when the length of array is same, but if they are not. In this method, we will see how we can convert a column of type 'map' to multiple columns in a data frame using explode function. Basically I have data that looks like: 33 I am using Spark SQL (I mention that it is in Spark in case that affects the SQL syntax - I'm not familiar enough to be sure yet) and I have a table that I am trying to re-structure, but I'm getting stuck trying to transpose multiple columns at the same time. This is particularly useful when you have nested data structures (e. This function converts the list elements to a row while replacing the index values and returning the DataFrame exploded list. Various variants of explode help handle special cases like NULL values or when position What is the PySpark Explode Function? The PySpark explode function is a transformation operation in the DataFrame API that flattens array-type or nested columns by generating a new row for each element in the array, managed through SparkSession. I am not familiar with the map reduce concept to change the script here to pyspark myself. Here we will parse or read json string present in a csv file and convert it into multiple dataframe columns using Python Pyspark. In my dataframe, exploding each column basically just does a useless cross join resulting in dozens of invalid rows. Apr 24, 2024 · In this article, I will explain how to explode array or list and map DataFrame columns to rows using different Spark explode functions (explode, The explode functions are built-in Spark SQL functions designed to convert array columns into multiple rows. sql. Example 1: Parse a Column of JSON Strings Using pyspark. Sample DF: from pyspark import Row from pyspark. , arrays or maps) and want to flatten them for analysis or processing. We often need to flatten such data for easier analysis. I understand how to explode a single column of an array, but I have multiple array columns where the arrays line up with each other in terms of index-values. Aug 15, 2025 · If you have multiple columns, it’s not good to hardcode map key names, let’s see the same by programmatically. 1. Why do we need these functions? All four functions share the same core purpose: they take each element inside 33 I am using Spark SQL (I mention that it is in Spark in case that affects the SQL syntax - I'm not familiar enough to be sure yet) and I have a table that I am trying to re-structure, but I'm getting stuck trying to transpose multiple columns at the same time. withColumn('points', explode(df. g.