How to avoid duplicate columns in spark sql. dropDuplicates ( ['id', 'name']) .

How to avoid duplicate columns in spark sql Aug 9, 2021 · If id is the only column name in common, you can take advantage of the USING clause: spark. While handling a lot of data, we observe that not all data is coming from one data frame, thus there is a need to merge two or more data frames together. May 10, 2022 · A common issue when performing append operations on Delta tables is duplicate data. The general idea behind the solution is to create a key based on the values of the columns that identify duplicates. Handling Duplicate Column Names in Spark Join Operations: A Comprehensive Guide This tutorial assumes you’re familiar with Spark basics, such as creating a SparkSession and standard joins (Spark DataFrame Join). when on is a join expression, it will result in duplicate columns. More detail can be refer to below Spark Dataframe API: pyspark. getOrCreate Jun 19, 2024 · In this article, I share how an SQL Server filtered index solved the problem of preventing duplicates for new rows in a table. Example: Sep 5, 2024 · Method 2: Using join () Another approach is to join the DataFrames and then explicitly select the columns you need, excluding duplicates. id == df2. builder. In Apache Spark, you can use the dropDuplicates function to eliminate duplicate rows from a DataFrame using Scala. In … If you want to ignore duplicate columns just drop them or select columns of interest afterwards. If you’re new to Spark, I recommend starting with Spark Tutorial to build a foundation. dropDuplicates(subset=None) [source] # Return a new DataFrame with duplicate rows removed, optionally only considering certain columns. Sep 17, 2019 · Remove Duplicate Records from Hive Table Apache Hive does not provide support to many functions or internal columns that are supported in modern day relations database systems such as Netezza, Vertica, etc. Sample Data Jul 23, 2025 · In this article, we are going to learn how to rename duplicate columns after join in Pyspark data frame in Python. When using select *, the column appears only once. Not sure whether to pursue troubleshooting if these solutions wont work for Select * 16 votes, 15 comments. distinct() and dropDuplicates() returns a new DataFrame. join (dataframe1, ['ID']) performs a join on the 'ID' column. As a data scientist or engineer working with PySpark DataFrames, you‘ll eventually have to tackle duplicate rows that need to be identified and removed. The choice of operation to remove Aug 1, 2016 · Question: in pandas when dropping duplicates you can specify which columns to keep. While joining on a single column is common, many real-world scenarios require joining on **multiple columns** to ensure accuracy (e. You can also specify which columns to use to identify duplicates by passing a list of column names to the dropDuplicates( Could someone please teach me how to remove duplicates from a column when joining two tables? I have been searching and trying different scripts, but they are still not working. In order to remove Sep 6, 2024 · Duplicate data can lead to problems in analysis and reporting, especially when dealing with large datasets. withColumnRenamed However, I think Learn how to perform a join operation in a Spark DataFrame using Java while avoiding duplicate columns in the result. This will return a new DataFrame with duplicate rows removed. e. id) and on="id" in a join stems from how Spark resolves and handles column naming during the join operation. A dispersed collection of data grouped into named columns is known as the Pyspark data frame. How to make Spark Dataframe distinguish columns with duplicate names to avoid References ambiguous problem, Programmer Sought, the best programmer technical posts sharing site. If both tables contain the same column name, Spark appends suffixes like _1, _2, leading to messy datasets that are difficult to work with. Jul 23, 2025 · In this article, we are going to learn how to distinguish columns with duplicated names in the Pyspark data frame in Python. The pyspark. The DISTINCT clause requires sorting and comparing records, which can increase the processing load on the query engine. dropDuplicates ( ['id', 'name']) . Window to add a column that counts the number of duplicates for each row's ("ID", "ID2", "Number") combination. Create the first dataframe for demonstration: Python3 # importing module import pyspark # importing sparksession from pyspark. Just 2 grosze. join(other, on, how) when on is a column name string, or a list of column names strings, the returned dataframe will prevent duplicate columns. This article and notebook demonstrate how to perform a join so that you don’t have duplicated columns. The failure is caused by: The target table h Introduction When working with large datasets in Apache Spark, data engineers often encounter duplicate records that need to be removed to ensure data accuracy and improve processing efficiency. 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. Here is some code to get you started: Nov 6, 2023 · Duplicate data is a common issue that can creep into datasets and cause major headaches in analysis. 12K subscribers in the apachespark community. While working in Pyspark, there occurs various situations in which we get the data frame that has various columns with duplicate names or the user even mistakenly creates a data Apr 25, 2024 · How to avoid duplicate columns on Spark DataFrame after joining? Apache Spark is a distributed computing framework designed for processing large-scale Jul 11, 2025 · In SQL, removing duplicate records is a common task, but the DISTINCT keyword can sometimes lead to performance issues, especially with large datasets. Select * From ['BP Ref _ Sep 23, 2024 · Hello I've seen posts that show how to remove duplicates, something like this: MERGE into [deltatable] as target USING ( select *, ROW_NUMBER () OVER (Partition By [primary keys] Order By [date] desc) as rn from [deltatable] qualify rn> 1 ) as source ON [merge primary keys and date column between source and target] WHEN MATCHED THEN DELETE Problem is this is reliant upon the rows having Mar 27, 2024 · 3. If you want to disambiguate you can use access these using parent DataFrames: The dropDuplicates method chooses one record from the duplicates and drops the rest. Jun 20, 2024 · Learn how to ensure accurate analysis by identifying and removing duplicates in PySpark, using practical examples and best practices for handling large datasets. 1. Jul 28, 2024 · In this article, we will discuss how to avoid duplicate columns in DataFrame after join in PySpark using Python. . The table contains duplicates with rows that are exactly the same. sql("select * from tbl1 join tbl2 using (id) ") The using clause matches columns that have the same name in both tables. Following are some samples with join columns: df1. Row Order: The row retained for each duplicate group is arbitrary unless explicitly ordered beforehand. how to avoid join column to appear twice in the output and 2. This tutorial will guide you through the process of using this function with practical examples and explanations. sql import SparkSession # creating sparksession and giving an app name spark = SparkSession. Below are some of the methods that you can use. , combining sales data by both `order_id` and `customer_id` to avoid mismatches). dropDuplicates method is a powerful tool in Spark's arsenal for dealing with duplicates in DataFrames. Please can someone guide me through this process. The query below works, however it duplicates a lot of columns that are in both tables. What is a self-join in SQL? A self-join is when a table is joined with itself to compare rows and identify duplicates or related data. Apr 30, 2025 · To remove duplicate columns in Polars, you need to identify the columns with identical values across all rows and retain only the unique ones. 1 dropDuplicate Syntax drop_duplicates() is an alias for Mar 14, 2024 · Hi Thanks for using Fabric Community. In this comprehensive guide, you‘ll learn how to use PySpark‘s powerful drop_duplicates() and dropDuplicates() […] Feb 27, 2025 · Removing duplicates in PySpark isn’t just about calling distinct () — it’s about understanding Spark’s execution model. dataframe. Jul 21, 2023 · Joining DataFrames is a common operation in PySpark, but it can often result in duplicate columns. This helps avoid column name collisions and ensures that you have a clean result DataFrame without duplicate columns. This makes it harder to select those columns. We can use . Given that I already have a DataFrame with ambiguous columns, how do I remove a specific column? For example, given: May 15, 2015 · From your question, it is unclear as-to which columns you want to use to determine duplicates. Mar 14, 2024 · You can also specify which columns to use to identify duplicates by passing a list of column names to the dropDuplicates () function. Try these techniques in your next Spark project and let us know how it goes on X. A distributed collection of data grouped into named columns is known as a Pyspark data frame. Nov 13, 2025 · In data processing, joining datasets is a fundamental operation to combine related information from multiple tables. select () allows you to specify the columns to include in the result, thus avoiding duplicate columns. Create the first dataframe for demonstration: Jul 3, 2018 · Extending upon use case given here: How to avoid duplicate columns after join? I have two dataframes with the 100s of columns. sort_values('actual_datetime', ascending=False). sql. But here in spark, we have some in-built methods to handle duplicates elegantly. For example, to remove duplicate rows based on the id and name columns, you would use the following code: dataframe. This is useful for simple use cases, but collapsing records is better for analyses that can't afford to lose any valuable data. Apache Spark’s SparkSQL is a powerful tool for querying Jul 23, 2025 · How do I remove duplicate rows from a table in SQL? Remove duplicates using the DELETE statement combined with a self-join to compare the column values and delete the extra occurrences. We’ll cover step-by-step examples, best practices, and common pitfalls to help you handle duplicates with confidence. sql module from pyspark. In this article, you will learn how to use distinct () and dropDuplicates () functions with PySpark example. Nov 8, 2025 · This blog post explores practical techniques to identify, manage, and resolve duplicated column names in Spark DataFrames. dropDuplicates() method is used to drop the duplicate rows from the single or multiple columns. PySpark dropDuplicates pyspark. pyspark. Dec 6, 2023 · Our query has resulted in duplicate rows; the first two rows have the same values in both columns (Bark, aged 10). Sep 2, 2020 · Find duplicate values in SQL with ease. Nov 28, 2022 · ProjectPro can easily teach you the correct way to handle Ambiguous column error during join in spark. From basic column selection to advanced renaming, nested data, SQL expressions, null handling, and performance optimizations, you’ve got a comprehensive toolkit. Dec 22, 2022 · Recipe Objective: How to eliminate Row Level Duplicates in Spark SQL? As we know, handling Duplicates is the primary concern in the data world. I think this question is about 2. By using the drop() function, you can easily remove these duplicates and keep your data clean and understandable. Killing duplicates We can use the spark-daria killDuplicates() method to completely remove all duplicates from a DataFrame. Is there an equivalent in Spark Dataframes? Pandas: df. Articles and discussion regarding anything to do with Apache Spark. Jul 16, 2022 · How to avoid duplicate columns after join in PySpark ?, How to resolve duplicate column names while joining two dataframes in PySpark?, pyspark duplicate a column on pyspark data frame, How to May 19, 2025 · Discover the top 10 Spark coding mistakes that slow down your jobs—and how to avoid them to improve performance, reduce cost, and optimize execution. Dec 29, 2021 · In this article, we will discuss how to remove duplicate columns after a DataFrame join in PySpark. For a streaming DataFrame, it will keep all data across triggers as intermediate state to drop duplicates rows. g. This process involves comparing the columns’ data and selecting the distinct ones for the Jul 26, 2017 · This will not duplicate the column and behave like a pandas merge. Typically SQL servers use the groupBY clause and count function or generate row_number to identify and drop duplicates. alias pyspark. Distributed Computation: Deduplication is performed across partitions, ensuring scalability. If there is no special reason why you have to write it as an sql command, I would recommend this. Aug 10, 2017 · When performing joins in Spark, one question keeps coming up: When joining multiple dataframes, how do you prevent ambiguous column name errors? 1) Let's start off by preparing a couple of simple example dataframes // Create first example dataframe val firstDF = spark. By using window functions, partitioning, salting, and bucketing, you Apr 17, 2025 · Whether you’re using distinct () for full-row deduplication, dropDuplicates () for specific columns, SQL expressions for flexibility, or optimizing for performance, you now have the tools to tackle duplicates effectively. Join DataFrames without duplicate columns # We can specify the join column using an array or a string to prevent duplicate columns. distinct () is Using dropDuplicates in Spark Scala Removing duplicate rows is a common operation in data processing. It returns a new DataFrame with duplicate rows removed, when columns are used as arguments, it only considers the selected columns. dropDuplicates # DataFrame. After that, the merge_duplicate_col() method is invoked to merge the duplicate columns. Apr 17, 2025 · Wrapping Up Your Duplicate Column Handling Mastery Handling duplicate column names after a join in PySpark is a vital skill for clear, error-free data integration. May 1, 2018 · Is there a simple and efficient way to check a python dataframe just for duplicates (not drop them) based on column(s)? I want to check if a dataframe has dups based on a combination of columns an As all the examples im finding have the columns set and when i run it with select * it doesnt work. Oct 13, 2022 · If you perform a join in Spark and don’t specify your join correctly you’ll end up with duplicate column names. Dec 23, 2024 · I n Apache Spark, the difference in behavior between on (df1. Jan 30, 2025 · Joining tables in Databricks (Apache Spark) often leads to a common headache: duplicate column names. For Python users, related PySpark operations are discussed at PySpark DataFrame Join and Feb 2, 2024 · Spark and SQL — Identifying and Eliminating Duplicate Rows Duplicate data can often pose a significant challenge in data processing and analysis, resulting in inaccuracies and skewed results. Then, you can use the reduceByKey or reduce operations to eliminate duplicates. Then select only the rows where the number of duplicate is greater than 1. I am attempting to insert many records using T-SQL's MERGE statement, but my query fails to INSERT when there are duplicate records in the source table. columns // Array( A little off topic, but if you want to migrate the data to a new table, and the possible duplicates are in the original table, and the column possibly duplicated is not an id, a GROUP BY will do: Nov 18, 2015 · After digging into the Spark API, I found I can first use alias to create an alias for the original dataframe, then I use withColumnRenamed to manually rename every column on the alias, this will do the join without causing the column name duplication. how to access columns of the same name that are not part of join condition. . 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. In Apache Spark, if you're joining DataFrames and end up with duplicate columns due to overlapping column names, you can use the alias () function to provide unique aliases to the columns. The other questions that I have gone through contain a col or two as duplicate, my issue is that the whole files are duplicates of each other: both in data and in column names. The merge or join can be inner May 11, 2018 · I don't think the question is a duplicate of the one given as there are two issues related, i. createDataFrame(Seq( (1, 1, 2, 3, 8, 4, 5) 35 One way to do this is by using a pyspark. In this guide, we’ll explore practical techniques to resolve duplicate columns after a JOIN in Databricks, separately for Spark SQL and PySpark. drop_dupli Jun 22, 2020 · 1 There are many questions similar to this that are asking a different question with regard to avoid duplicate columns in a join; that is not what I am asking here. For example, assume user 1 performs a write operation on Delta table A. Oct 26, 2017 · 51 df. Click here to learn how to fix ambiguous column name sql. 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. Dec 29, 2024 · How Spark Handles Deduplication Behind the Scenes Hashing: Spark computes a hash for the specified columns (or all columns by default). This concise guide covers using GROUP BY and HAVING clauses to effectively identify and resolve duplicates. Since Polars doesn’t offer a built-in function like drop_duplicates() for columns, you’ll need to apply different techniques to filter out the duplicates. appName('sparkdf'). In this article, we’ll explain various alternatives to remove duplicates in SQL, including using ROW_NUMBER (), self-joins Jan 14, 2024 · Let's say I have a table "people" with three columns: name (String), age (Integer), direction (String). You have to use different methods to identify and delete duplicate rows from Hive table. DataFrame. For a static batch DataFrame, it just drops duplicate rows. You can use withWatermark() to limit Nov 3, 2023 · Then, we call the identify_duplicate_col() method to find and store information about duplicate columns. You can use the dropDuplicates() function in pyspark to drop the duplicates. drop(df. If you’re using Delta tables… Jul 3, 2020 · I'm very new to ms sql and joins. a) to drop duplicate columns. Mar 12, 2019 · Since I have all the columns as duplicate columns, the existing answers were of no help. 3. Having duplicate rows isn’t necessarily a bad thing. iyd kye fltojt brck dcmpryf uqyeyi ocpzqk fkmbcq mmk hvsd tjarh zew zunkg abgf pye