Pyspark order by multiple columns. sql import SparkSession from pyspark.
Pyspark order by multiple columns Mar 23, 2024 · Example: How to Order PySpark DataFrame by Multiple Columns Suppose we have the following PySpark DataFrame that contains information about various basketball players: Sorting the data in a PySpark DataFrame using the orderBy() method allows you to organize the data in a specific order based on one or more columns, facilitating analysis and downstream processing. orderBy ¶ DataFrame. column. Sort ascending vs. Reordering columns in a DataFrame is essential for organizing data to facilitate efficient data analysis, visualization, and other operations. functions import row_number # Create a spark session using getOrCreate() function spark_session = SparkSession. OrderBy Operation in PySpark DataFrames: A Comprehensive Guide PySpark’s DataFrame API is a powerful tool for big data processing, and the orderBy operation is a key method for sorting data based on one or more columns. Parameters 1. com Returns DataFrame Sorted DataFrame. It allows users to customize their data structure to meet specific requirements and preferences. Introduction: Mastering Column Reordering in PySpark Data scientists and engineers frequently need to manipulate the structure of their datasets to ensure optimal analysis and compatibility with downstream systems. If a column ordinal is Jun 10, 2018 · I am trying to use OrderBy function in pyspark dataframe before I write into csv but I am not sure to use OrderBy functions if I have a list of columns. I am attempting to resolve how to order by multiple columns in the dataframe, when one of these is a count. Other Parameters ascendingbool or list, optional, default True boolean or list of boolean. These are handy when making aggregate operations in a specific window frame on DataFrame columns. Nov 8, 2023 · This tutorial explains how to use the partitionBy() function with multiple columns in a PySpark DataFrame, including an example. Jul 27, 2023 · The PySpark sort () Method The sort () method in pyspark is used to sort a dataframe by one or multiple columns. window import Window from pyspark. Window. sql. To do this, we use the orderBy () method of PySpark. 7. As an example, say I have a dataframe (df) with three columns, A,B,and C. Collecting Multiple Columns into Lists You can collect the values of multiple columns into multiple lists after grouping the data by one or more Sep 5, 2025 · In PySpark, the row_number () window function in PySpark is used to return a new column containing a unique sequential number to each row based on a specified order. It supports both single-column and multi-column sorting. I have a data frame in python/pyspark with columns id time city zip and so on Now I added a new column name to this data frame. See full list on sparkbyexamples. Whether you’re arranging records alphabetically, ranking values numerically, or preparing data for presentation, orderBy provides a flexible way to order your dataset Understanding Multi-Column Sorting in PySpark The ability to sort a PySpark DataFrame based on the values across multiple columns is a fundamental requirement for effective data analysis and presentation. Method 1 : Using orderBy () This function will return the dataframe after ordering the multiple columns. We pass a list with the names of the columns to sort by and a list with the boolean values identifing the orders as Jul 7, 2020 · Column_1 Column_2 Column_3 Column_4 1 A U1,A1 549BZ4G,12345 I also tried using monotonically increasing id to create an index and then order by the index and then did a group by and collect set to get the output. Notes A column ordinal starts from 1, which is different from the 0-based __getitem__(). Jun 30, 2021 · Syntax: dataframe. It has the following syntax. Dec 19, 2021 · Output: orderby means we are going to sort the dataframe by multiple columns in ascending or descending order. getOrCreate() Apr 25, 2019 · Spark Rdd - using sortBy with multiple column values Asked 6 years, 7 months ago Modified 6 years, 7 months ago Viewed 834 times Jan 4, 2022 · I'm fairly new to PySpark, but I am trying to use best practices in my code. orderBy # static Window. Jun 6, 2025 · How to reorder the columns in a PySpark DataFrame? You can use the select() function to reorder columns by passing them in a specific order. functions import sum, desc Step 2: Now, create a spark session using the getOrCreate function. When sorting on multiple columns, you can also specify certain columns to sort on ascending and certain columns on descending. But still no luck. Oct 7, 2020 · df. When working with large-scale data processing using Apache Spark, specifically through its Python API, known as PySpark DataFrame s, column order becomes a critical concern. getOrCreate() # Read the CSV file data Feb 7, 2016 · I've successfully create a row_number() and partitionBy() by in Spark using Window, but would like to sort this by descending, instead of the default ascending. Parameters colsstr, list, or Column, optional list of Column or column names to sort by. Nov 8, 2023 · This tutorial explains how to use the Window. from pyspark. we can do this by using the following methods. This is especially useful when preparing data for reports, finding top or bottom records, or organizing results before writing to an output. sql import SparkSession from pyspark. cols | string or list or Column | optional A column or columns by which to sort. Aug 11, 2024 · Sorting or ordering records by columns can help in pre-processing data, ensuring that your data is organised and ready for analysis. For this, we are using sort () and orderBy () functions along with select () function. We’ll tackle key errors to keep your pipelines robust. appName("MultiPartitionWindow"). You can also create UDF to Case 14: PySpark dataframe Sort by multiple columns You can pass multiple columns in the sort function and also mention order style – ascending (default) or descending. sort ( ['column1','column2','column n'],ascending=True) Where, dataframe is the dataframe name created from the nested lists using pyspark where columns are the llst of columns ascending = True specifies order the dataframe in increasing order, ascending=False specifies order the dataframe in decreasing order Example 1: Python code to sort dataframe by passing a list of Jun 17, 2021 · In this article, we are going to order the multiple columns by using orderBy () functions in pyspark dataframe. In this article, I will explain how to reorder columns in a specific order using Polars. How does this arrangement inform your pricing strategy for different product categories? Problem 3: Basic Filtering Task Returns DataFrame Sorted DataFrame. May 12, 2024 · PySpark Groupby on Multiple Columns can be performed either by using a list with the DataFrame column names you wanted to group or by sending multiple column names as parameters to PySpark groupBy () method. Nov 27, 2018 · A,B 2,6 1,2 1,3 1,5 2,3 I want to sort it with ascending order for column A but within that I want to sort it in descending order of column B, like this: i have json file that contain some data, i converted this json to pyspark dataframe(i chose some columns not all of them) this is my code: import os from pyspark import SparkContext from pyspark. Apr 17, 2025 · It ensures data is presented in a meaningful order, enhancing insights and processing efficiency. 3. If a column ordinal is Dec 6, 2018 · When partition is specified using a column, one window per distinct value of the column is created. Jun 3, 2023 · Z Ordering is an amazing Delta Lake feature unavailable in data lakes. Jan 15, 2017 · A B Rank --------------- A1 B1 1 A1 B2 2 A1 B3 3 A2 B1 1 A2 B2 2 A2 B3 2 A3 B1 3 A3 B2 2 A3 B3 1 The ultimate state I want to reach is to aggregate column B and store the ranks for each A: Example: 5. This guide dives into the syntax and steps for sorting a PySpark DataFrame by one or more columns, with examples covering simple, multi-column, nested, and SQL-based scenarios. 2. orderBy(*cols: Union[str, pyspark. When multiple rows have the same value for the order column, they receive the same rank, but subsequent ranks are skipped. Here is my working code: from pyspark Jun 29, 2024 · Here you have learned how to Sort PySpark DataFrame columns using sort(), orderBy() and using SQL sort functions and used this function with PySpark SQL along with Ascending and Descending sorting Oct 22, 2019 · I'd like to have a column, the row_number (), based on 2 columns in an existing dataframe using PySpark. partitionBy # static Window. DataFrame ¶ Returns a new DataFrame sorted by the specified column (s). Jul 23, 2025 · # Python program to partition by multiple # columns in PySpark with columns in a list # Import the SparkSession, Window and row_number libraries from pyspark. In this article, we will discuss different ways to orderby a pyspark dataframe using the orderBy () method. Jan 15, 2025 · Problem 2: Multiple Column Sorting Imagine you have a DataFrame with columns product, category, and price. show() Sorting by multiple Columns Now, we would like to sort the DataFrame by the column "language" in ascending order and the column "users" in descending order. 9/Spark 1. DataFrame. Feb 1, 2023 · The result of this code will be a dataframe with three columns: column1, column2, and list_column3. The values of column column3 will be collected into a list named list_column3 for each unique combination of values in columns column1 and column2. You learned about the best columns to use when Z Ordering data and the tradeoffs when you Z Order on multiple columns. I want to group by A and B, and then count these instances. The colsMap is a map of column name and column, the column must only refer to attributes supplied by this Dataset. Is it due to alphanumeric and numeric values ? How to retain the order of column 3 and column 4 as it is there in input with no change of ordering. , over a range of input rows. The pyspark. partitionBy(*cols) [source] # Creates a WindowSpec with the partitioning defined. I have a PySpark dataframe and I would like to lag multiple columns, replacing the original values with the lagged values. Alternatively, you can rearrange columns using df[column_order], where column_order is a list of column names in the desired order. orderBy () function. This could be a single column or multiple columns based on your requirements. If only partition is specified, then when a when is evaluated for a row, all the rows in that partition would taken into account. show see Changing Nulls Ordering in Spark SQL. Syntax: Learn how to order PySpark DataFrame by multiple columns with the . Ordering the rows means arranging the rows in ascending or descending order, so we are going to create the dataframe using nested list and get the distinct data. Jun 6, 2021 · In this article, we will discuss how to select and order multiple columns from a dataframe using pyspark in Python. It’s concise and readable, especially for simple sorts, and Spark’s optimizer ensures the same efficient execution plan as the Column -based approach. In this article, I’ve explained the concept of window functions, syntax, and finally how to use them with PySpark SQL and PySpark DataFrame API. This blog post showed you how to Z Order data by one or multiple columns. Ordering the rows means arranging the rows in ascending or descending order. Jul 23, 2025 · The SparkSession library is used to create the session, the sum is used to sum the columns on which groupby is applied, while desc is used to sort the list in descending order. builder. Thats why you see all 4 values [10, 15, 10, 25] for all the rows in partition x. Sorting by Multiple Columns Often, you need to sort by more than one column to break ties or enforce a specific order. May 11, 2023 · The PySpark DataFrame also provides the orderBy () function to sort on one or more columns. Returns a new DataFrame by adding multiple columns or replacing the existing columns that have the same names. Nov 7, 2022 · In this article, we are going to apply OrderBy with multiple columns over pyspark dataframe in Python. Window with Multiple Partitions and Orders The window operation can use multiple columns in partitionBy and orderBy for complex windows. Other Parameters ascendingbool or list, optional In this blog post, we'll dive into PySpark's orderBy() and sort() functions, understand their differences, and see how they can be used to sort data in DataFrames. May 5, 2024 · Specify the column (s) to group by within the groupBy () operation. and it orders by ascending by default. I'd like to have the order so one column is sorted ascending, and the other descending. Jul 3, 2025 · In PySpark, the rank() window function adds a new column by assigning a rank to each row within a partition of a dataset based on the specified order criteria. It will sort first based on the column name given. Both the functions sort () or orderBy () of the PySpark DataFrame are used to sort the DataFrame by ascending or descending order based on the single or multiple columns. Aug 12, 2023 · PySpark DataFrame's orderBy(~) method returns a new DataFrame that is sorted based on the specified columns. It can handle single or multiple columns and allows flexibility with ascending or descending order settings. select('*'). descending. Oct 24, 2023 · df_sorted. Trying to achieve it via this piece of code. When sorting by multiple columns, PySpark will prioritize them in the order you specify. Unlike single-column sorting, multi-column sorting establishes a hierarchy: the data is sorted first by the primary column, and then, any rows sharing the same value in the primary column are Jul 30, 2023 · While working with pyspark dataframes, we often need to order the rows according to one or multiple columns. orderBy(column. orderBy() function to sort descending, including an example. If a list of booleans is passed Nov 7, 2016 · How to select and order multiple columns in a Pyspark Dataframe after a join Asked 9 years ago Modified 3 years, 2 months ago Viewed 45k times Nov 2, 2023 · This tutorial explains how to sort rows by a particular column in a PySpark pivot table, including an example. My question is similar to this thread: Partitioning by multiple columns in Spark SQL but I'm working in Pyspark rather than Scala and I want to pass in my list of columns as a list. What does window partitionBy do in PySpark? pyspark. If desired, you can optionally sort the results based on the count or other criteria to analyze the data more effectively. Nov 4, 2021 · I want the sell price inside the `collect_list` to be sorted based on the specified column, but even though I mention it in the query, it still doesn't maintain the order. Method 1: Using OrderBy () OrderBy () function is used to sort an object by its index value. If a list is specified, the length of the list must equal the length of the cols. orderBy(*cols) [source] # Creates a WindowSpec with the ordering defined. You also learned how to use Z Ordering with or instead of Hive-style partitioning. If False, then the sort will be in descending order. Example: How to Order PySpark DataFrame by Multiple Columns Suppose we have the following PySpark DataFrame that contains information about various basketball players: Aug 31, 2023 · Learn how to order a PySpark DataFrame by multiple columns effectively with this comprehensive guide. I'm using PySpark (Python 2. ascending | boolean or list of boolean | optional If True, then the sort will be in ascending order. Mar 10, 2025 · In Polars, you can use the select() function to reorder columns in a specific order, allowing you to explicitly define the desired column sequence for your DataFrame. Create a scenario where you need to sort first by category in ascending order and then by price in descending order. 1) and have a dataframe GroupObject which I need to filter & sort in the descending order. functions import rank spark = SparkSession. Specify list for multiple sort orders. Column]]], **kwargs: Any) → pyspark. This function is especially useful in data analysis tasks such as identifying top performers within a group Mar 27, 2024 · In Spark , sort, and orderBy functions of the DataFrame are used to sort multiple DataFrame columns, you can also specify asc for ascending and desc for descending to specify the order of the sorting. How would you do this in pyspark? I'm specifically using this to do a "window over" sort of thing: pyspark. Code: Cols = ['col1','col2','col3'] df = df. orderBy () Function in pyspark sorts the dataframe in by single column and multiple column. window module provides functions like row_number(), rank (), and dense_rank () to add ranking-based columns to a DataFrame. pyspark. Whether you’re arranging records alphabetically, ranking values numerically, or preparing data for presentation, orderBy provides a flexible way to order your dataset Jan 1, 2010 · 0 I am currently working on understanding Pyspark, and am running into a problem. dataframe. Whether In order to sort the dataframe in pyspark we will be using orderBy () function. This tutorial covers the syntax and examples of sorting DataFrames by a single column, multiple columns, and descending order. The orderBy () function in PySpark is a powerful tool to sort data efficiently. Jun 10, 2018 · I am trying to use OrderBy function in pyspark dataframe before I write into csv but I am not sure to use OrderBy functions if I have a list of columns. Now I have to arrange the Sep 23, 2025 · PySpark Window functions are used to calculate results, such as the rank, row number, etc. asc_nulls_last). 1. Column, List[Union[str, pyspark.