Pyspark count distinct Column [source] ¶ Returns a new Column for distinct count of col or cols. count () method. agg(F. I just tried doing a countDistinct over a window and got this error: AnalysisException: u'Distinct window functions are not supported: count (distinct color#1926) Is there a way to do a distinct c Dec 23, 2020 · Week count_total_users count_vegetable_users 2020-40 2345 457 2020-41 5678 1987 2020-42 3345 2308 2020-43 5689 4000 This desired output should be the count distinct for 'users' values inside the column it belongs to. When we use Spark to do that, it calculates the number of unique words in every partition, reshuffles the data using the words as the partitioning keys (so all counts of a particular word end up in the same cluster), and sums the Jan 19, 2023 · Recipe Objective - Explain Count Distinct from Dataframe in PySpark in Databricks? The distinct (). Then I want to calculate the distinct values on every column. countDistinct("a","b","c")). com Oct 16, 2023 · This tutorial explains how to count distinct values in a PySpark DataFrame, including several examples. Column ¶ Aggregate function: returns a new Column for approximate distinct count of column col. Oct 31, 2023 · This tutorial explains how to count the number of values in a column that meet a condition in PySpark, including an example. distinct ¶ DataFrame. 4+ you can use array_distinct and then just get the size of that, to get count of distinct values in your array. countDistinct(col: ColumnOrName, *cols: ColumnOrName) → pyspark. when takes a Boolean Column as its condition. agg ()” function allows for more customization by allowing the use of Oct 30, 2023 · This tutorial explains how to use groupBy with count distinct in PySpark, including several examples. columns = Aug 1, 2016 · 2 I just did something perhaps similar to what you guys need, using drop_duplicates pyspark. 0. unique(). 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 (). builder. dataframe. Apr 6, 2022 · In Pyspark, there are two ways to get the count of distinct values. The goal is simple: calculate distinct number of orders and total order value by order date and status from the following table: This has to be done in Spark's Dataframe API (Python or Scala), not SQL. agg(fn. countDistinct ¶ pyspark. Oct 24, 2016 · What is the equivalent in Pyspark for LIKE operator? For example I would like to do: SELECT * FROM table WHERE column LIKE "*somestring*"; looking for something easy like this (but this is not wor Jun 9, 2024 · Fix Issue was due to mismatched data types. DataFrame. , matching all the columns of the Row) from the DataFrame, and the count () returns the count of the records on the Sep 1, 2020 · As you can see in the source code pyspark. I generate a dictionary for aggregation with something like: from pyspark. Dec 13, 2018 · How it is possible to calculate the number of unique elements in each column of a pyspark dataframe: import pandas as pd from pyspark. This comprehensive tutorial outlines three distinct and highly efficient methodologies for calculating the count of unique values within a DataFrame using specialized PySpark SQL functions. This tutorial covers the basics of using the `countDistinct ()` function, including how to specify the column to group by and how to handle null values. sql. Nov 7, 2020 · Why does counting the unique elements in Spark take so long? Let’s look at the classical example used to demonstrate big data problems: counting words in a book. So regardless the one you use, the very same code runs in the end. Column ¶ Returns a new Column for distinct count of col or cols. DataFrame ¶ Returns a new DataFrame containing the distinct rows in this DataFrame. This gives me the list and count of all unique values, and I only want to know how many are there overall. approx_count_distinct, nothing more except giving you a warning. Jul 7, 2021 · I am trying to run aggregation on a dataframe. When I try starting it up, I get the error: Exception: Java gateway process exited before sending the driver its port number when sc = SparkContext() is python apache-spark pyspark apache-spark-sql edited Dec 10, 2017 at 1:43 Community Bot 1 1 Aug 24, 2016 · The selected correct answer does not address the question, and the other answers are all wrong for pyspark. Logical operations on PySpark columns use the bitwise operators: & for and | for or ~ for not When combining these with comparison operators such as <, parenthesis are often needed. approx_count_distinct # pyspark. Jun 17, 2021 · In this article, we will discuss how to count unique ID after group by in PySpark Dataframe. schema = StructType([ StructField("_id", StringType(), True), StructField(" I'm trying to run PySpark on my MacBook Air. Situation is this. from pyspark. Another way is to use SQL countDistinct () function which will provide the distinct value count of all the selected columns. count () method and the countDistinct () function of PySpark. Feb 25, 2017 · I don't know a thing about pyspark, but if your collection of strings is iterable, you can just pass it to a collections. There is no "!=" operator equivalent in pyspark for this solution. Oct 10, 2023 · This tutorial explains how to select distinct rows in a PySpark DataFrame, including several examples. Examples Jun 23, 2025 · This can be easily done in Pyspark using the groupBy () function, which helps to aggregate or count values in each group. You'll also find tips on how to optimize your code for performance. Counter, which exists for the express purpose of counting distinct values. Oct 22, 2022 · A Neat Way to Count Distinct Rows with Window functions in PySpark If you use PySpark you are likely aware that as well as being able group by and count elements you are also able to group by and count distinct elements. Oct 23, 2023 · This tutorial explains how to use the equivalent of pandas value_counts() function in PySpark, including several examples. An alias of count_distinct(), and it is encouraged to use count_distinct() directly. distinct() → pyspark. distinct () function gets the distinct rows from the DataFrame by eliminating all duplicates and on top of that use count () function to get the distinct count of records. Also, still according to the source code, approx_count_distinct is based on the HyperLogLog++ algorithm. For spark2. functions pyspark. Dec 19, 2023 · Count distinct values with conditions Asked 6 years, 11 months ago Modified 1 year, 11 months ago Viewed 12k times May 16, 2024 · By using countDistinct () PySpark SQL function you can get the count distinct of the DataFrame that resulted from PySpark groupBy (). For this, we are using distinct () and dropDuplicates () functions along with select () function. array_distinct(col) [source] # Array function: removes duplicate values from the array. show() 1 It seems that the way F. Jun 6, 2021 · In this article, we are going to display the distinct column values from dataframe using pyspark in Python. DISTINCT and GROUP BY in simple contexts of selecting unique values for a column, execute the same way, i. In this article, we will explore how to use the groupBy () function in Pyspark for counting occurrences and performing various aggregation operations. When I try starting it up, I get the error: Exception: Java gateway process exited before sending the driver its port number when sc = SparkContext() is 107 pyspark. 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. I want to list out all the unique values in a pyspark dataframe column. sql import SparkSession spark = SparkSession. Returns a new Column for distinct count of col or cols. functions as F df. Here we discuss the introduction, syntax, and working of DISTINCT COUNT in PySpark along with examples. functions as fn gr = Df2. I come from pandas background and am used to reading data from CSV files into a dataframe and then simply changing the column names to something useful using the simple command: df. You can use the Pyspark countDistinct() function to get a count of the distinct values in a column of a Pyspark dataframe. I'm trying to run PySpark on my MacBook Air. Oct 24, 2016 · What is the equivalent in Pyspark for LIKE operator? For example I would like to do: SELECT * FROM table WHERE column LIKE "*somestring*"; looking for something easy like this (but this is not wor I'm trying to run PySpark on my MacBook Air. distinct() [source] # Returns a new DataFrame containing the distinct rows in this DataFrame. as an aggregation. Any clue? With pyspark dataframe, how do you do the equivalent of Pandas df['col']. Note:In pyspark t is important to enclose every expressions within parenthesis () that combine to form the condition May 20, 2016 · Utilize simple unionByName method in pyspark, which concats 2 dataframes along axis 0 as done by pandas concat method. 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 Jun 14, 2024 · In this example, we are creating pyspark dataframe with 11 rows and 3 columns and get the distinct count from rollno and marks column. In this article, I will explain different examples of how to select distinct values of a column from DataFrame. I want something like this - col (URL) has x distinct values. array_distinct # pyspark. They allow computations like sum, average, count, maximum, May 16, 2021 · I have a DataFrame with two columns, id1, id2 and what I'd like to get is to count the number of distinct values of these two columns. For this, we will use two different methods: Using distinct (). column. Oct 25, 2024 · Introduction In this tutorial, we want to count the distinct values of a PySpark DataFrame column. 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. I have 2 dataframes (coming from 2 files) which are exactly same except 2 columns file_date (file date extracted from the file name) and data_date (row date stamp). The Distinct () is defined to eliminate the duplicate records (i. distinct # DataFrame. approx_count_distinct(col: ColumnOrName, rsd: Optional[float] = None) → pyspark. Pyspark: display a spark data frame in a table format Asked 9 years, 3 months ago Modified 2 years, 3 months ago Viewed 413k times Jun 8, 2016 · Very helpful observation when in pyspark multiple conditions can be built using & (for and) and | (for or). Explicitly declaring schema type resolved the issue. Jul 4, 2021 · In this article, we will discuss how to find distinct values of multiple columns in PySpark dataframe. # import the below modules pyspark. © Copyright Databricks. 107 pyspark. distinct values of these two column values. getOrCre Jun 9, 2024 · Fix Issue was due to mismatched data types. 4. functions import col import pyspark. Nov 22, 2025 · Learn practical PySpark groupBy patterns, multi-aggregation with aliases, count distinct vs approx, handling null groups, and ordering results. In order to get a third df3 with columns id, uniform, normal, normal_2. When using PySpark, it's often useful to think "Column Expression" when you read "Column". Note:In pyspark t is important to enclose every expressions within parenthesis () that combine to form the condition Pyspark: display a spark data frame in a table format Asked 9 years, 3 months ago Modified 2 years, 3 months ago Viewed 413k times May 20, 2016 · Utilize simple unionByName method in pyspark, which concats 2 dataframes along axis 0 as done by pandas concat method. groupby(['Year']) df_grouped = gr. Using UDF will be very slow and inefficient for big data, always try to use spark in-built functions. Aug 24, 2016 · The selected correct answer does not address the question, and the other answers are all wrong for pyspark. Created using Sphinx 3. python apache-spark pyspark apache-spark-sql edited Dec 10, 2017 at 1:43 Community Bot 1 1 Jun 8, 2016 · Very helpful observation when in pyspark multiple conditions can be built using & (for and) and | (for or). Not the SQL type way (registertemplate the Aug 13, 2022 · This is because Apache Spark has a logical optimization rule called ReplaceDistinctWithAggregate that will transform an expression with distinct keyword by an aggregation. functions. Learn techniques with PySpark distinct, dropDuplicates, groupBy with count, and other methods. approx_count_distinct(col, rsd=None) [source] # This aggregate function returns a new Column, which estimates the approximate distinct count of elements in a specified column or a group of columns. But at first, let's Create Dataframe for demonstration: pyspark. alias('total_student_by_year')) The problem that I discovered that so many ID's are repeated, so the result is wrong and huge. approxCountDistinct simply calls pyspark. countDistinct deals with the null value is not intuitive for me. Oct 6, 2023 · This tutorial explains how to find unique values in a column of a PySpark DataFrame, including several examples. Oct 31, 2016 · import pyspark. countDistinct () is used to get the count of unique values of the specified column. distinct ()” function returns a new DataFrame with unique rows, making it a simple and efficient way to count distinct values. Now suppose you have df1 with columns id, uniform, normal and also you have df2 which has columns id, uniform and normal_2. Oct 24, 2016 · What is the equivalent in Pyspark for LIKE operator? For example I would like to do: SELECT * FROM table WHERE column LIKE "*somestring*"; looking for something easy like this (but this is not wor. I want to agregate the students by year, count the total number of student by year and avoid the repetition of ID's. Let's create a sample dataframe for demonstration: pyspark. count () of DataFrame or countDistinct () SQL function in Apache Spark are popularly used to get count distinct. In order to do this, we use the distinct (). We can use distinct () and count () functions of DataFrame to get the count distinct of PySpark DataFrame. Oct 24, 2023 · You can use the following methods to count distinct values in a PySpark DataFrame: Nov 29, 2022 · Spark SQL approx_count_distinct Window Function as a Count Distinct Alternative The approx_count_distinct windows function returns the estimated number of distinct values in a column within the group. Extract unique values in a column using PySpark. Apr 6, 2023 · Guide to PySpark count distinct. agg ()” function, and the “pivot” function. The “. pyspark. See full list on sparkbyexamples. Nov 19, 2025 · Aggregate functions in PySpark are essential for summarizing data across distributed datasets. count(col('Student_ID')). Apr 3, 2024 · Counting the distinct values in PySpark can be done using three different methods: the “. Learn how to count distinct values grouped by a column in PySpark with this easy-to-follow guide. Using SQL Query. In this article, we will discuss how to count distinct values in one or multiple columns in pyspark. May 13, 2024 · DataFrame. e. distinct ()” function, the “. Essentially this is count (set (id1+id2)). geolbo hlxfo miwbu rttnaw sqmt cqhdxwy uqqokk ujpv mockr ume rqbacp tpoou lpqsa yjnav pcculy