Pyspark select distinct one column. Could some one please help me on this? I am using Spark 1.

Pyspark select distinct one column If you want to see the distinct values of a specific column in your dataframe, you would just need to write the following code. countDistinct() is a SQL function that could be used to get the count distinct of the selected multiple columns. distinct (), df. By chaining these you can get the count distinct of PySpark DataFrame. Mar 29, 2019 · Here's my spark code. Nov 16, 2025 · This comprehensive guide is designed to explore the specific methods available within PySpark to efficiently select either distinct rows or distinct values from specific columns within a DataFrame. Learn how to use the distinct () function, the nunique () function, and the dropDuplicates () function. I have a spark data frame and I want to do array = np. In this article, I pyspark. How do I do that? Apr 27, 2025 · Joining and Combining DataFrames Relevant source files Purpose and Scope This document provides a technical explanation of PySpark operations used to combine multiple DataFrames into a single DataFrame. I have a PySpark dataframe with a column URL in it. collect()) on all my columns except on the first one (which I want to select by name or number). Introduction: DataFrame in PySpark is an two dimensional data structure that will store data in two dimensional format. Examples Example 1: Removing duplicate values from a simple array df. All I want to know is how many distinct values are there. Get distinct rows from a DataFrame with null values. Jun 29, 2021 · In this article, we are going to filter the rows based on column values in PySpark dataframe. Note that calling count() on a large dataset may trigger a time-consuming computation, especially if the dataset is partitioned across many nodes. Like this in my example: Oct 10, 2023 · This tutorial explains how to select distinct rows in a PySpark DataFrame, including several examples. Jun 2, 2019 · I have an RDD and I want to find distinct values for multiple columns. Nov 29, 2023 · distinct() eliminates duplicate records (matching all columns of a Row) from DataFrame, count () returns the count of records on DataFrame. select() and . Mar 27, 2024 · How does PySpark select distinct works? In order to perform select distinct/unique rows from all columns use the distinct () method and to perform on a single column or multiple selected columns use dropDuplicates (). count () – Get the column value Mar 27, 2024 · How to create an alias in PySpark for a column, DataFrame, and SQL Table? We are often required to create aliases for several reasons, one of them would Jul 30, 2025 · PySpark union () and unionAll () transformations are used to merge two or more DataFrame’s of the same schema or structure. The primary method, dropDuplicates () (or its alias distinct ()), is straightforward and leverages Spark’s distributed computing power to handle large datasets efficiently. countDistinct deals with the null value is not intuitive for me. Examples Nov 16, 2022 · How exactly do you want to Sort? I don't see an order in your given example. columns]) but you should keep in mind that this is an expensive operation and consider if pyspark. approxCountDistinct() is suitable for you. Oct 31, 2016 · import pyspark. map(lambda r: r[0]) But unlike Panda's DataFrames, I don't believe this has an index I can reuse, it appears to just be the values. Click on each link to learn with example. But if I do: Mar 12, 2019 · Pyspark expects the left and right dataframes to have distinct sets of field names (with the exception of the join key). May 13, 2024 · PySpark has several count () functions. Aug 13, 2022 · Of the various ways that you've tried, e. collect() But this takes a lot of time. Aug 2, 2024 · Understanding the differences between distinct () and dropDuplicates () in PySpark allows you to choose the right method for removing duplicates based on your specific use case. I am trying to inner join both of them D1. array(df. Get distinct values from multiple columns in DataFrame. We can easily return all distinct values for a single column using distinct(). select(*[countDistinct(c). Creating Dataframe for demonstration:. distinct() → pyspark. It covers join operations, union operations, and pivot/unpivot transformations. countDistinct () is used to get the count of unique values of the specified column. select ¶ DataFrame. Option 2: Select by position First compute the size of the maximum array and store this in a new column max_length. Differences Between PySpark distinct vs dropDuplicates The main difference between distinct () vs dropDuplicates () functions in PySpark are the former is used to select distinct rows from all columns of the DataFrame and the latter is used select distinct on selected columns. show() These examples demonstrate how the distinct function can be used to retrieve unique values from a DataFrame, either in a single column or across multiple columns. However, if you want to apply it to all columns, there’s no need to Jan 29, 2025 · In this short article, we will explore the nuances of the distinct and dropDuplicates functions in PySpark, providing a deeper understanding of how these two essential functions work and when to Method 2: Selecting Distinct Values from Specific Columns: Combining . May 1, 2023 · The “SELECT DISTINCT” statement is used to return only unique values from the “City” column. GroupedData, and this contains the count () function to ge Mar 25, 2020 · In SQL select, in some implementation, we can provide select -col_A to select all columns except the col_A. EXCEPT EXCEPT and EXCEPT ALL return the rows that are found in one relation but not the other Parameters col Column or str name of column or expression Returns Column A new column that is an array of unique values from the input column. orderBy("fruit", ascending=False) # Show the distinct values distinct_fruits_ordered. select(*cols: ColumnOrName) → DataFrame ¶ Projects a set of expressions and returns a new DataFrame. To learn more, see our tips on writing great answers. Feb 2, 2024 · The Spark DISTINCT function doesn’t take any arguments, so you first need to select columns and then apply DISTINCT. select ('column'). count_distinct # pyspark. Jan 14, 2019 · The question is pretty much in the title: Is there an efficient way to count the distinct values in every column in a DataFrame? The describe method provides only the count but not the distinct co Method 2: Selecting Distinct Values from Specific Columns: Combining . Syntax: dataframe_name. I define a unary column as one which has at most one distinct value and for the purpose of the definition, I count null as a value as well. Sep 2, 2016 · If you want to save rows where all values in specific column are distinct, you have to call dropDuplicates method on DataFrame. distinct ¶ DataFrame. init () function in order to PySpark - select distinct rows based on max value from another column Asked 5 years, 4 months ago Modified 5 years, 4 months ago Viewed 2k times pyspark. distinct() [source] # Returns a new DataFrame containing the distinct rows in this DataFrame. Example: Row(col1=a, col2=b, col3=1), Row(col1=b, col2=2, col3=10)), Row(col1=a1, col2=4, col3=10) I would like to find have a ALL Select all matching rows from the relation and is enabled by default. functions import max The max we use here is the pySpark sql function not the python max It is better if you use use alias for it from pyspark. sum_distinct # pyspark. Get the distinct values in a column in PySpark with this easy-to-follow guide. In general, it denotes a column expression. Syntax: expression [[AS] alias] star Select distinct rows in PySpark DataFrame The distinct () method in Apache PySpark DataFrame is used to generate a new DataFrame containing only unique rows based on all columns. Spark SQL supports three types of set operators: EXCEPT or MINUS INTERSECT UNION Note that input relations must have the same number of columns and compatible data types for the respective columns. Aug 2, 2016 · 24 I have two DataFrames in Spark SQL (D1 and D2). , what is the most efficient way to extract distinct values from a column? pyspark. Dec 16, 2021 · Output: Method 1: Using distinct () method It will remove the duplicate rows in the dataframe Syntax: dataframe. DataFrame. PySpark Aggregate Functions PySpark SQL Aggregate functions are grouped as “agg_funcs” in Pyspark. functions import countDistinct Apr 27, 2025 · This document covers techniques for working with array columns and other collection data types in PySpark. In this PySpark article, I will explain both union transformations with PySpark examples. functions import max as mx Jan 19, 2024 · In this example, distinct () will consider all columns and remove any rows that are identical across all columns. Learn techniques with PySpark distinct, dropDuplicates, groupBy with count, and other methods. Nov 22, 2021 · I am using Pyspark, and I have 4 data frames, each having the same schema. Let’s see these two ways with examples. count () In this example, we will create a DataFrame df which contains Student details like Name, Course, and Marks. Jun 6, 2021 · In this article, we are going to display the distinct column values from dataframe using pyspark in Python. Aug 8, 2017 · I'm trying to get the distinct values of a column in a dataframe in Pyspark, to them save them in a list, at the moment the list contains "Row (no_children=0)" but I need only the value as I will use it for another part of my code. It is useful for removing duplicate records in a DataFrame. How do I select this columns without having to manually type the na Apr 6, 2022 · By chaining these two functions one after the other we can get the count distinct of PySpark DataFrame. May 5, 2024 · 2. DataFrame ¶ Returns a new DataFrame containing the distinct rows in this DataFrame. Get distinct non-null values from a DataFrame. alias(c) for c in df_spark. Set Operators Description Set operators are used to combine two input relations into a single one. May 12, 2024 · In PySpark, select() function is used to select single, multiple, column by index, all columns from the list and the nested columns from a DataFrame, PySpark select () is a transformation function hence it returns a new DataFrame with the selected columns. It would show the 100 distinct values (if 100 values are available) for the colname column in the df dataframe. Dec 13, 2018 · Possible duplicate of Spark DataFrame: count distinct values of every column. For this, use the Pyspark select() function to select the column and then apply the distinct() function and finally apply the show() function to display the results. select("fruit"). rdd. pyspark. Mar 28, 2019 · I have 10+ columns and want to take distinct rows by multiple columns into consideration. If one of the column names is ‘*’, that column is expanded to include all columns in the current DataFrame. e. One solution would be to prefix each field name with either a "left_" or "right_" as follows: Apr 12, 2019 · 2 I need an efficient way to list and drop unary columns in a Spark DataFrame (I use the PySpark API). Parameters colsstr, Column, or list column names (string) or expressions (Column). distinct() to find the unique set of values within one or more designated columns. posexplode but this time it's just to create a column to represent the index in each array to extract. Spark DISTINCT or spark drop duplicates is used to remove duplicate rows in the Dataframe. Jan 20, 2024 · Removing duplicate rows or data using Apache Spark (or PySpark), can be achieved in multiple ways by using operations like drop_duplicate, distinct and groupBy. I tried it in the Spark 1. In this article, we will discuss how to count distinct values in one or multiple columns in pyspark. One dimension refers to a row and second dimension refers to a column, So It will store the data in rows and columns. I'd like to transform this dataframe to a form where there are two columns, one for id (with a single row per id ) and the second column containing a list of distinct purchases for that id. distinct() but if you have other value in date column, you wont get back the distinct elements from host: May 30, 2021 · In this article we are going to get the distinct data from pyspark dataframe in Python, So we are going to create the dataframe using a nested list and get the distinct data. How does PySpark select distinct works In order to perform select distinct unique rows from all columns use the distinct method and to perform on a single column or Jun 14, 2024 · In this PySpark tutorial, we will discuss how to use sumDistinct () and countDistinct () methods on PySpark DataFrame. countDistinct("a","b","c")). I want to select all the columns except say 3-4 of the columns. Count the number of distinct values in a specific column. Jan 22, 2023 · Here is one common task in PySpark: how to filter one dataframe column are from unique values from anther dataframe? Method 1 Say we have two dataframes df1 and df2, and we want to filter df1 by column called “id”, where its values need to be from column “id” in df2. I can only display the dataframe but not May 20, 2025 · Learn how to use the subselect syntax in the SQL language in Databricks SQL and Databricks Runtime. groupby ('column'). Essentially you can do df_spark. Provide details and share your research! But avoid … Asking for help, clarification, or responding to other answers. Is there a way to replicate the following command: sqlCo Nov 16, 2025 · This comprehensive guide is designed to explore the specific methods available within PySpark to efficiently select either distinct rows or distinct values from specific columns within a DataFrame. df. This tutorial covers both the `distinct()` and `dropDuplicates()` functions, and provides code examples for each. select name from student where name in (select distin You can use the Pyspark sum_distinct() function to get the sum of all the distinct values in a column of a Pyspark dataframe. This function allows users to efficiently identify the largest value present in a specific column, making it invaluable for various data analysis tasks. Jul 29, 2016 · df = df. select(c). dropDuplicates ( [“department”,”salary”]) will only consider the Oct 6, 2025 · pyspark. All I want to do is to print "2517 degrees"but I'm not sure how to extract that 2517 into a variable. This guide also includes code examples. sql. join(D2, "some column") and get back data of only D1, not the complete data set. Oct 6, 2023 · This tutorial explains how to find unique values in a column of a PySpark DataFrame, including several examples. First, we’ll create a Pyspark dataframe that we’ll be using throughout this tutorial. Apr 17, 2025 · Filtering duplicates in PySpark means identifying and either keeping or removing rows that are identical based on all columns or a subset of columns. Jul 23, 2025 · Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more. functions as F df. I will explain how to use these two functions in this article and learn the differences with examples. named_expression An expression with an assigned name. Making statements based on opinion; back them up with references or personal experience. Then select elements from each array if a value exists at that index. distinct # DataFrame. Syntax: expression [[AS] alias] star Nov 4, 2023 · And more! Sound useful? Let‘s dive in and unlock the power of distinct () in PySpark for cleaning and optimizing your large-scale data! What is distinct () and Why Do We Need It? First, what exactly does the distinct () function do in PySpark? In simple terms, distinct () removes duplicate rows from a Spark DataFrame and returns only unique data. 1 version I need to fetch distinct values on a column and then perform some specific transformation on top of it. We focus on common operations for manipulating, transforming, and converting arrays in DataFr Pyspark Dataframe Distinct Column Values - This tutorial explains how to select distinct rows in a PySpark DataFrame including several examples I have multiple columns from which I want to collect the distinct values. Learn how to get unique values in a column in PySpark with this step-by-step guide. The column contains more than 50 million records and can grow large distinct_fruits_ordered = df. Both methods take one or more columns as arguments and return a new DataFrame after sorting. Feb 7, 2023 · In this article, we will learn how to select columns in PySpark dataframe. Distinct Operation in PySpark DataFrames: A Comprehensive Guide PySpark’s DataFrame API is a powerful framework for big data processing, and the distinct operation is a key method for eliminating duplicate rows to ensure data uniqueness. distinct () is Mar 27, 2024 · PySpark distinct() transformation is used to drop/remove the duplicate rows (all columns) from DataFrame and dropDuplicates() is used to drop rows based on selected (one or multiple) columns. Examples Oct 11, 2023 · This tutorial explains how to select a PySpark column aliased with a new name, including several examples. count_distinct(col, *cols) [source] # Returns a new Column for distinct count of col or cols. select ALL Select all matching rows from the relation and is enabled by default. For related operations on column manipulation, see Column Operations or for filtering rows, see Filtering and Nov 19, 2025 · All these aggregate functions accept input as, Column type or column name as a string and several other arguments based on the function. Learn how to use the distinct () function and the dropDuplicates () function to get the unique values in a column. Get the unique values in a PySpark column with this easy-to-follow guide. One of the most common tasks when working with DataFrames is selecting specific columns. DISTINCT Select all matching rows from the relation after removing duplicates in results. I want to count the distinct ids in them all. select('record_id'). select ( columns_names ) Note: We are specifying our path to spark directory using the findspark. Oct 30, 2023 · You can use the following syntax to count the number of distinct values in one column of a PySpark DataFrame, grouped by another column: from pyspark. show() 1 It seems that the way F. Make sure you have the correct imports, You need to import the following: from pyspark. Both D1 and D2 are having the same columns. It works fine and returns 2517. Currently i have multiple rows for a given id with each row only relating to a single purchase. Let's install pyspark module before Mar 27, 2024 · PySpark SQL collect_list() and collect_set() functions are used to create an array (ArrayType) column on DataFrame by merging rows, typically after group by or window partitions. How can we get all unique combinations of multiple columns in a PySpark DataFrame? Suppose we have a DataFrame df with columns col1 and col2. Extract unique values in a column using PySpark. distinct () Where, dataframe is the dataframe name created from the nested lists using pyspark Example 1: Python program to drop duplicate data using distinct () function Oct 16, 2023 · This tutorial explains how to count distinct values in a PySpark DataFrame, including several examples. For this, we are using distinct () and dropDuplicates () functions along with select () function. Get distinct values from a specific column in a DataFrame. GroupBy Count in PySpark To get the groupby count on PySpark DataFrame, first apply the groupBy () method on the DataFrame, specifying the column you want to group by, and then use the count () function within the GroupBy operation to calculate the number of records within each group. Here, we use the select() function to first select the column (or columns) we want to get the distinct values for and then apply the distinct() function. Mar 27, 2024 · PySpark distinct () PySpark dropDuplicates () 1. The select () function allows us to select single or multiple columns in different formats. functions provides two functions concat() and concat_ws() to concatenate DataFrame multiple columns into a single column. May 4, 2024 · In PySpark, the max () function is a powerful tool for computing the maximum value within a DataFrame column. Would it make sense to try and figure out the following workflow? Identify rows with distinct record_id, and write to MySQL Then, identify the remaining rows, and write to MySQL Or would Feb 17, 2023 · In PySpark, distinct is a transformation operation that is used to return a new DataFrame with distinct (unique) elements. 6. Could some one please help me on this? I am using Spark 1. agg(F. Mar 27, 2024 · You can use either sort() or orderBy() function of PySpark DataFrame to sort DataFrame by ascending or descending order based on single or multiple columns. Depending on your needs, you should choose which one best meets your needs. The DataFrame contains some duplicate values also. Examples Oct 31, 2016 · import pyspark. DISTINCT is very commonly used to identify possible values which exists in the dataframe for any given column. Returns DataFrame A DataFrame with subset (or all) of columns. Jul 24, 2023 · While handling data in pyspark, we often need to find the count of distinct values in one or multiple columns in a pyspark dataframe. Once again we use pyspark. I just need the number of total distinct values. distinct() and dropDuplicates() returns a new DataFrame. sum_distinct(col) [source] # Aggregate function: returns the sum of distinct values in the expression. count () etc. g. I can do it this way: for c in columns: values = dataframe. Nov 6, 2024 · Explore various methods to retrieve unique values from a PySpark DataFrame column without using SQL queries or groupby operations. Mar 21, 2016 · Let's say I have a spark data frame df1, with several columns (among which the column id) and data frame df2 with two columns, id and other. dataframe. Below is a list of functions defined under this group. Does it looks a bug or normal for you ? And if it is normal, how I can write something that output exactly the result of the first approach but in the same spirit than the second Method. How to achieve this using pyspark dataframe functions ? Jul 5, 2007 · Hi, I want select only distinct column of one column while at the same time displaying the other column attributed to the selected column. Jun 13, 2018 · I have a large number of columns in a PySpark dataframe, say 200. In this article, you will learn how to use distinct () and dropDuplicates () functions with PySpark example. I'm still fairly new to Spark/Pyspark. 0 as - 29842 May 16, 2024 · By using countDistinct () PySpark SQL function you can get the count distinct of the DataFrame that resulted from PySpark groupBy (). Examples Let’s look at some examples of getting the distinct values in a Pyspark column. This means that if there are multiple employees with the same city, the query will only return one instance of that city. Row consists of columns, if you are selecting only one column then output will be unique values for that specific column. Using Spark 1. functions. This guide also includes code examples and tips for optimizing your performance. I have tried the following df. count () – Get the count of rows in a DataFrame. Example 1: Pyspark Count Distinct from DataFrame using distinct (). Function used: In PySpark we can select columns using the select () function. The groupBy () method returns the pyspark. Jun 9, 2018 · Pyspark - Selecting Distinct Values in Column after groupby and orderBy Asked 7 years, 5 months ago Modified 6 years, 7 months ago Viewed 4k times Sep 1, 2016 · Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question. In this blog post, we will explore different ways to select columns in PySpark DataFrames, accompanied by example code for better understanding. You can also do sorting using PySpark SQL sorting functions. distinct(). ezqw vnxp ryf ebibz ilxqbqlu sxha wtiysc ekuiby mmtss xvfzr zzuhf ort aklcznq gmeunvd cojfv