Spark Dataframe Rename Multiple Columns Scala

6 was the ability to pivot data, creating pivot tables, with a DataFrame (with Scala, Java, or Python). Data is organized as a distributed collection of data into named columns. bigdataetl import org. Derive multiple columns from a single column in a Spark DataFrame; Apache Spark — Assign the result of UDF to multiple dataframe columns; How to check if spark dataframe is empty; How do I check for equality using Spark Dataframe without SQL Query? Dataframe sample in Apache spark | Scala. a UDF that adds a column to the DataFrame,. Learning Objectives. Column names of an R Dataframe can be acessed using the function colnames(). Next, he looks at the DataFrame API and how it's the platform's answer to many big data challenges. 5 alone; so, we thought it is a good time for revisiting the subject, this time also utilizing the external package spark-csv, provided by Databricks. Rename multiple pandas dataframe column names. - Stack Overflow scala - Append a column to Data Frame in Apache Spark 1. 1 Documentation - udf registration. SparkSession object Test extends App { val spark = SparkSession. Create a spark dataframe from sample data; Load spark dataframe into non existing hive table; How to add new column in Spark Dataframe; How to read JSON file in Spark; How to execute Scala script in Spark without creating Jar; Spark-Scala Quiz-1; Hive Quiz – 1; Join in hive with example; Trending now. I am trying to get rid of white spaces from column names - because otherwise the DF cannot be saved as parquet file - and did not find any usefull method for renaming. Example – Spark – Add new column to Spark Dataset. A pivot is an aggregation where one (or more in the general case) of the grouping columns has its distinct values transposed into individual columns. Hence, DataFrame API in Spark SQL improves the performance and scalability of Spark. A Spark DataFrame is a distributed collection of data organized into named columns that provides operations. I won’t go into the Spark basics again here, but just highlight how to do things in Scala. replace() for string/regex based replacement. Home » Spark Scala UDF to transform single Data frame column into multiple columns Protected: Spark Scala UDF to transform single Data frame column into multiple columns This content is password protected. import org. Scala Spark demo of joining multiple dataframes on same columns using implicit classes. HOT QUESTIONS. Note that the ^ and $ surrounding alpha are there to ensure that the entire string matches. Renaming column names of a DataFrame in Spark Scala - Wikitechy. It is conceptually equivalent to a table in a relational database or a data frame. If you need to rename ALL columns at once, DataFrame. %md Combine several columns into single column of sequence of values. Please help me rename some name of my pandas dataframe. This helps Spark optimize execution plan on these queries. Removing duplicates from rows based on specific columns in an RDD/Spark DataFrame. It’s also possible to use R’s string search-and-replace functions to rename columns. withColumnRenamed("colName", "newColName"). Spark Performance: Scala or Python? In general, most developers seem to agree that Scala wins in terms of performance and concurrency: it’s definitely faster than Python when you’re working with Spark, and when you’re talking about concurrency, it’s sure that Scala and the Play framework make it easy to write clean and performant async code that is easy to reason about. A DataFrame’s schema is used when writing JSON out to file. Below is the code. A foldLeft or a map (passing a RowEncoder). Examples in Scala. Let's look at the below code snippet in spark-shell for renaming a column:. Imagine we would like to have a table with an id column describing a user and then two columns for the number of cats and dogs she has. Performing operations on multiple columns in a Spark DataFrame with foldLeft. x with saved models using spark. multiple columns stored from a List to Spark Dataframe,apache spark, scala, dataframe, List, foldLeft, lit, spark-shell, withcoumn in spark,example Here is Something !: How to add multiple withColumn to Spark Dataframe. This topic demonstrates a number of common Spark DataFrame functions using Python. A dataframe in Spark is similar to a SQL table, an R dataframe, or a pandas dataframe. withColumnRenamed("colName2", "newColName2") The benefit of using this method. Earlier versions of spark extensively used RDD for data operations. This was required to do further processing depending on some technical columns present in the list. In this post, we will see how to replace nulls in a DataFrame with Python and Scala. data that was nested as structs inside an array column and bubbled it up to a first-level column in a DataFrame. It has interfaces that provide Spark with additional information about the structure of both the data and the computation being performed. rename() with axis=1 or axis='columns' (the axis argument was introduced in v0. I am joining two data frame in spark using scala. Column names of an R Dataframe can be acessed using the function colnames(). How can I change multiple column name. Finally, we add one more column that has double type of value instead of string which we will use ourselves for the rest of this material. I want a generic reduceBy function, that works like an RDD's reduceByKey, but will let me group data by any column in a Spark DataFrame. Examples in Scala. This article describes and provides scala example on how to Pivot Spark DataFrame ( creating Pivot tables ) and Unpivot back. Is there any nicer way to prefix or rename all or multiple columns at the same time of a given SparkSQL DataFrame than calling multiple times dataFrame. builder // I. The Spark API is consistent between Scala and Python though, so all differences are really only Scala itself. Deprecated: Function create_function() is deprecated in /home/clients/f93a83433e1dd656523691215c9ec83c/web/rtpj/9ce2f. Sharing is caring!. Create a spark dataframe from sample data; Load spark dataframe into non existing hive table; How to add new column in Spark Dataframe; How to read JSON file in Spark; How to execute Scala script in Spark without creating Jar; Spark-Scala Quiz-1; Hive Quiz – 1; Join in hive with example; Trending now. How to add multiple columns in a spark dataframe using SCALA. We often need to rename one or multiple columns on Spark DataFrame, Especially when a column is nested it becomes complicated. DataFrames are composed of Row objects accompanied with a schema which describes the data types of each column. Column // Create an example dataframe. There are generally two ways to dynamically add columns to a dataframe in Spark. Data is organized as a distributed collection of data into named columns. In the couple of months since, Spark has already gone from version 1. You may access the tutorials in any order you choose. Sharing is caring!. These snippets show how to make a DataFrame from scratch, using a list of values. Use HDInsight Spark cluster to read and write data to Azure SQL database. In Spark, a DataFrame is a distributed collection of data organized into named columns. Sql in an easy way like below: Filter a DataFrame which contains "" DataFrame. sql for DataType (Scala-only). Scala supports extension methods through implicits which we will use in an example to extend Spark DataFrame with a method to save it in an Azure SQL table. Spark SQL - DataFrames - A DataFrame is a distributed collection of data, which is organized into named columns. withColumn ("Destination", df. 0, GeoSparkViz provides the DataFrame support. Explore careers to become a Big Data Developer or Architect!. DataFrame columns and dtypes The columns method returns the names of all the columns in the source DataFrame as an array of String. size res4: Int = 3 scala> df2. Spark SQL - DataFrames - A DataFrame is a distributed collection of data, which is organized into named columns. For grouping by percentiles, I suggest defining a new column via a user-defined function (UDF), and using groupBy on that column. Pyspark is a python interface for the spark API. tableExists("schemaname. One of Apache Spark's selling points is the cross-language API that allows you to write Spark code in Scala, Java, Python, R or SQL (with others supported unofficially). Append column to Data Frame (or RDD) I can think of something as below, but it completes with errors (at line 3), and anyways doesn't look like the best route possible: var dataDF = sc. Sql in an easy way like below: Filter a DataFrame which contains "" DataFrame. I have to divide a dataframe into multiple smaller dataframes based on values in columns like - gender and state , the end goal is to pick up random samples from each dataframe. columns Renaming Columns Although we can rename a column in the above manner, it's often much easier (and readable) to use the withColumnRenamed method. These examples are extracted from open source projects. Multiple column array functions. HiveWarehouseSession acts as an API to bridge Spark with Hive. In this post, we will look at withColumnRenamed() function in Apache Spark SQL API. spark drop columns column cast array scala apache-spark dataframe apache-spark-sql apache-spark-ml How to sort a dataframe by multiple column(s)? Drop data frame columns by name. The dtypes method returns the data types of all the columns in the source DataFrame as an array of tuples. You can also access the individual column names using an index to the output of colnames() just like an array. Learning Objectives. {SQLContext, Row, DataFrame, Column} import. Rename column header in a pandas dataframe Pandas dataframes are grids of rows and columns where data can be stored and easily manipulated with functions. Published 2017-03-28. spark drop columns column cast array scala apache-spark dataframe apache-spark-sql apache-spark-ml How to sort a dataframe by multiple column(s)? Drop data frame columns by name. I am joining two data frame in spark using scala. You will probably find useful information on StackOverflow (for example, here is a similar question—but don’t use the accepted answer, it may fail for non-trivial datasets). This is quite a common task we do whenever process the data using spark data frame. Click Create recipe. Spark SQL can cache tables using an in-memory columnar format by calling spark. Sql in an easy way like below: Filter a DataFrame which contains "" DataFrame. You may access the tutorials in any order you choose. The equivalent Spark DataFrame method. charAt(0) which will get the first character of the word in upper case (which will be considered as a group). Speed up: Benefit from faster results. In long list of columns we would like to change only few column names. withColumn("newColumn", lit ("newValue")) 3. A foldLeft or a map (passing a RowEncoder). col!="" """) Filter a DataFrame column which contains null. alias() method. When executing SQL queries using Spark SQL, you can reference a DataFrame by its name previously registering DataFrame as a table. You can vote up the examples you like and your votes will be used in our system to product more good examples. However the current implementation of arrow in spark is limited to two use cases. Efficient Spark Dataframe Transforms // under scala spark. One of the major abstractions in Apache Spark is the SparkSQL DataFrame, which is similar to the DataFrame construct found in R and Pandas. we will use | for or, & for and , ! for not. tableExists("schemaname. _ val newDf = xmlDf. spark drop columns column cast array scala apache-spark dataframe apache-spark-sql apache-spark-ml How to sort a dataframe by multiple column(s)? Drop data frame columns by name. {SQLContext, Row, DataFrame, Column} import. 0 Spark supports UDAFs (User Defined Aggregate Functions) which can be used to apply any commutative and associative function. Natural join for data frames in Spark Natural join is a useful special case of the relational join operation (and is extremely common when denormalizing data pulled in from a relational database). You may say that we already have that, and it's called groupBy , but as far as I can tell, groupBy only lets you aggregate using some very limited options. Hi I have a nested column in a dataframe and avro is failing to deal with it becuase there are two columns with the same name called "location" one indicates location of A and the other location of B. {FileSystem, Path} import org. The Spark way is to use map on the DataFrame, append each row with a new column applying the clockwise rotation matrix generation method and then converting the resulting pipeline RDD into DataFrame with the column names imposed back as part of the schema. 5 alone; so, we thought it is a good time for revisiting the subject, this time also utilizing the external package spark-csv, provided by Databricks. Spark DataFrame expand on a lot of these concepts, allowing you to transfer that knowledge easily by understanding the simple syntax of Spark DataFrames. Also, Python will assign automatically a dtype to the dataframe columns, while Scala doesn't do so, unless we specify. Scala, Java, which makes it easier to be used by people having. sql for DataType (Scala-only). In the couple of months since, Spark has already gone from version 1. I have DataFrame contains 100M records and simple count query over it take ~3s, whereas the same query with toDF() method take ~16s. So i have created a Scala List of 100 column names. col!="" """) Filter a DataFrame column which contains null. registerTempTable("tempDfTable") Use Jquery Datatable Implement Pagination,Searching and Sorting by Server Side Code in ASP. Derive multiple columns from a single column in a Spark DataFrame; Apache Spark — Assign the result of UDF to multiple dataframe columns; How to check if spark dataframe is empty; How do I check for equality using Spark Dataframe without SQL Query? Dataframe sample in Apache spark | Scala. Performing operations on multiple columns in a Spark DataFrame with foldLeft. Pandas UDF that allows for operations on one or more columns in the DataFrame API. Learning Objectives. Also, Python will assign automatically a dtype to the dataframe columns, while Scala doesn’t do so, unless we specify. Explore careers to become a Big Data Developer or Architect!. CRT020: Databricks Certified Associate Developer for Apache Spark 2. spark scala talks The below video is a screen cast of my talk on Anatomy of Data Frame API : Deep dive into Spark SQL Data Frame API in recent spark meetup. With using toDF() for renaming columns in DataFrame must be careful. createDataFrame (Seq ( (1, "a"), (2, "b"), (3, >> "b"), (4,. Spark SQl is a Spark module for structured data processing. Spark also contains many built-in readers for other format. New features in this component include: Near-complete support for saving and loading ML models and Pipelines is provided by DataFrame-based API, in Scala, Java, Python, and R. js: Find user by username LIKE value. But in the above case, there isn't much freedom. - Stack Overflow scala - Append a column to Data Frame in Apache Spark 1. There are multiple ways to define a. To rename a dataframe using Spark, you just have to make use of the withColumnRenamed() method. selectExpr() takes SQL expressions as a string: flights. In the middle of the code, we are following Spark requirements to bind DataFrame to a temporary view. The Spark way is to use map on the DataFrame, append each row with a new column applying the clockwise rotation matrix generation method and then converting the resulting pipeline RDD into DataFrame with the column names imposed back as part of the schema. Sorting by Column Index. Arrow is becoming an standard interchange format for columnar Structured Data. Explore careers to become a Big Data Developer or Architect!. I am trying to get rid of white spaces from column names - because otherwise the DF cannot be saved as parquet file - and did not find any usefull method for renaming. Model loading can be backwards-compatible with Apache Spark 1. Below is the code. _ import org. In this short post I will show you how you can change the name of the file / files created by Apache Spark to HDFS or simply rename or delete any file. For the standard deviation, see scala - Calculate the standard deviation of grouped data in a Spark DataFrame - Stack Overflow. col!="" """) Filter a DataFrame column which contains null. Example - Spark - Add new column to Spark Dataset. Consequently, we see our original unordered output, followed by a second output with the data sorted by column z. To support a wide variety of data sources and analytics workloads in Spark SQL, we designed an extensible query optimizer called Catalyst. Spark has moved to a dataframe API since version 2. One of the many new features added in Spark 1. Moreover, we can construct a DataFrame from a wide array of sources. Also, Python will assign automatically a dtype to the dataframe columns, while Scala doesn't do so, unless we specify. How to convert a dataframe into a nested list? How to add a column to Dataset without converting from a DataFrame and accessing it? Select Rows from a DataSet using LINQ, where the list of RowsID's are in a List; Spark DataFrame not respecting schema and considering everything as String; Cannot convert string to a long in scala. Spark doesn't provide a clean way to chain SQL function calls, so you will have to monkey patch the org. Spark SQL and DataFrames - Spark 1. To select multiple columns, you can pass multiple strings. What is difference between class and interface in C#; Mongoose. Machine Learning Deep Learning Python Statistics Scala PostgreSQL Command Line Regular Expressions Mathematics AWS. builder // I. length()) 2. Apache Spark flatMap Example As you can see in above image RDD X is the source RDD and RDD Y is a resulting RDD. {SQLContext, Row, DataFrame, Column} import. Append Spark Dataframe with a new Column by UDF To change the schema of a data frame, we can operate on its RDD, then apply a new schema. So i have created a Scala List of 100 column names. rename() with axis=1 or axis='columns' (the axis argument was introduced in v0. Create a SparkSession with Hive supported. Column = id Beside using the implicits conversions, you can create columns using col and column functions. Apache Spark ML Programming Guide. size res4: Int = 3 scala> df2. It is mostly used for structured data processing. 3 - Stack Overflow Join Two DataFrames without a Duplicated Column — Databricks Documentation tatabox2000 2018-03-29 13:35 ScalaでSparkのDataframe(一部Dataset). Column // Create an example dataframe. groupBy on Spark Data frame GROUP BY on Spark Data frame is used to aggregation on Data Frame data. fieldNames All columns name are from the array columnsNameArray and in same sequence except. We often need to rename one or multiple columns on Spark DataFrame, Especially when a column is nested it becomes complicated. Spark: Creating Machine Learning Pipelines Using Spark ML Spark ML is a new library which uses dataframes as it's first class citizen as opposed to RDD. The foldLeft way is quite popular (and elegant) but recently I came across an issue regarding its performance when the number of columns to add is not trivial. val ageCol = people( "age" ) // in Scala Column ageCol = people. Apache Spark ML Programming Guide. For grouping by percentiles, I suggest defining a new column via a user-defined function (UDF), and using groupBy on that column. Create Example DataFrame spark-shell --queue= *; To adjust logging level use sc. 2 sqlContext. How to generate demo on a randomly generated DataFrame? How to rename DataFrame columns name in pandas? Describe the summary statistics of DataFrame in Pandas; How to select multiple columns in a pandas DataFrame? Remove duplicate rows from Pandas DataFrame where only some columns have the same value. Multiple Filters in a Spark DataFrame column using Scala To filter a single DataFrame column with multiple values Filter using Spark. SparkSession import org. Spark insert / append a record to RDD / DataFrame ( S3 ) Posted on December 8, 2015 by Neil Rubens In many circumstances, one might want to add data to Spark; e. This is quite a common task we do whenever process the data using spark data frame. 10/03/2019; 7 minutes to read +1; In this article. Spark SQl is a Spark module for structured data processing. It accepts a function word => word. In this talk, we will discuss about internals of dataframe. Introduction to DataFrames - Python. (Scala-specific) Returns a new DataFrame where each row has been expanded to zero or more rows by the provided function. Apache Spark groupBy Example. groupBy retains grouping columns; Upgrading from Spark SQL 1. Features of Spark SQL. Conceptually, it is equivalent to relational tables with good optimizati. Spark-scala recipes can manipulate datasets by using SparkSQL's DataFrames. Also notice that I did not import Spark Dataframe, because I practice Scala in Databricks, and it is preloaded. Dataframe exposes the obvious method df. To rename a dataframe using Spark, you just have to make use of the withColumnRenamed() method. Lets see how to select multiple columns from a spark data frame. sdf_separate_column() Separate a Vector Column into Scalar Columns. In the example below, we are simply renaming the Donut Name column to Name. DataFrames can be constructed from a wide array of sources such as: structured data files,. A pivot is an aggregation where one (or more in the general case) of the grouping columns has its distinct values transposed into individual columns. Home » Spark Scala UDF to transform single Data frame column into multiple columns Protected: Spark Scala UDF to transform single Data frame column into multiple columns This content is password protected. Values must be of the same type. Introduction to DataFrames - Scala. When executing SQL queries using Spark SQL, you can reference a DataFrame by its name previously registering DataFrame as a table. You can read more about dataframes here. x with saved models using spark. Spark SQL can automatically infer the schema of a JSON dataset, and use it to load data into a DataFrame object. selectExpr() takes SQL expressions as a string: flights. Similar to the above method, it’s also possible to sort based on the numeric index of a column in the data frame, rather than the specific name. master("local[*]"). data frame APIs in R and Python, DataFrame operations in Spark SQL go through a relational optimizer, Catalyst. {SQLContext, Row, DataFrame, Column} import. countByValue on dataframe with multiple columns. 5, with more than 100 built-in functions introduced in Spark 1. DataFrame lets you create multiple columns with the same name, which causes problems when you try to refer to columns by name. Sql("""Select * from tempDfTable where tempDfTable. Profiling a scala spark application of arrays into multiple rows? apache. The Spark DataFrame API is different from the RDD API because it is an API for building a relational query plan that Spark's Catalyst optimizer can then execute. Example – Spark – Add new column to Spark Dataset. Sep 30, 2016. Once created, it can be manipulated using the various domain-specific-language (DSL) functions defined in: DataFrame (this class), Column, and functions. MEMORY_ONLY_SER): """Sets the storage level to persist its values across operations after the first time it is computed. foldLeft can be used to eliminate all whitespace in multiple columns or…. Current information is correct but more content will probably be added in the future. Append Spark Dataframe with a new Column by UDF To change the schema of a data frame, we can operate on its RDD, then apply a new schema. Creating a Spark-Scala recipe¶ Create a new Spark-Scala recipe, either through a dataset’s Actions menu or in +Recipe > Hadoop & Spark > Spark-Scala; Add the input Datasets and/or Folders that will be used as source data in your recipes. I have DataFrame contains 100M records and simple count query over it take ~3s, whereas the same query with toDF() method take ~16s. This was required to do further processing depending on some technical columns present in the list. Spark's new DataFrame API is inspired by data frames in R and Python (Pandas), but designed from the ground up to support modern big data and data science applications. js: Find user by username LIKE value. DataFrame columns and dtypes The columns method returns the names of all the columns in the source DataFrame as an array of String. However not all language APIs are created equal and in this post we'll look at the differences from both a syntax and performance point of view. In my work project using Spark, I have two dataframes that I am trying to do some simple math on, subject to some conditions. The Spark way is to use map on the DataFrame, append each row with a new column applying the clockwise rotation matrix generation method and then converting the resulting pipeline RDD into DataFrame with the column names imposed back as part of the schema. col("DEST_COUNTRY_NAME")). Rename multiple pandas dataframe column names. Try by using this code for changing dataframe column names in pyspark. setLogLevel(newLevel). Let's discuss all possible ways to rename column with Scala examples. Left outer join. Sql DataFrame. How to generate demo on a randomly generated DataFrame? How to rename DataFrame columns name in pandas? Describe the summary statistics of DataFrame in Pandas; How to select multiple columns in a pandas DataFrame? Remove duplicate rows from Pandas DataFrame where only some columns have the same value. Converting RDD to Data frame with header in spark-scala Published on December 27, 2016 December 27, 2016 • 16 Likes • 6 Comments. NET MVC with Entity Framework. In Spark, dataframe is actually a wrapper around RDDs, the basic data structure in Spark. This article shows you how to use Scala for supervised machine learning tasks with the Spark scalable MLlib and Spark ML packages on an Azure HDInsight Spark cluster. scala Find file Copy path HeartSaVioR [SPARK-29503][SQL] Remove conversion CreateNamedStruct to CreateNamed… bfbf282 Oct 23, 2019. Apache Spark is a cluster computing system. You may say that we already have that, and it's called groupBy , but as far as I can tell, groupBy only lets you aggregate using some very limited options. This is mainly useful when creating small DataFrames for unit tests. We shall use functions. In this post, we have learned to add, drop and rename an existing column in the spark data frame. Spark Data Frame : Check for Any Column values with ‘N’ and ‘Y’ and Convert the corresponding Column to Boolean using PySpark Assume there are many columns in a data frame that are of string type but always have a value of “N” or “Y”. Data Science using Scala and Spark on Azure. Sharing is caring!. For the standard deviation, see scala - Calculate the standard deviation of grouped data in a Spark DataFrame - Stack Overflow. Rename file / files package com. In a previous post, we glimpsed briefly at creating and manipulating Spark dataframes from CSV files. Spark Dataframe can be easily converted to python Panda's dataframe which allows us to use various python libraries like scikit-learn etc. Learning Scala Spark basics using spark shell in local Posted on Dec 10, 2018 Author Sakthi Priyan H A pache Spark™ is a unified analytics engine for large-scale data processing. Python API Docs. I want a generic reduceBy function, that works like an RDD's reduceByKey, but will let me group data by any column in a Spark DataFrame. 2 sqlContext. SparkSession object Test extends App { val spark = SparkSession. I often need to perform an inverse selection of columns in a dataframe, or exclude some columns from a query. I need to concatenate two columns in a dataframe. rename() function. It avoids the garbage-collection cost of constructing individual objects for each row in the dataset. Spark Performance: Scala or Python? In general, most developers seem to agree that Scala wins in terms of performance and concurrency: it’s definitely faster than Python when you’re working with Spark, and when you’re talking about concurrency, it’s sure that Scala and the Play framework make it easy to write clean and performant async code that is easy to reason about. However the current implementation of arrow in spark is limited to two use cases. Column names of an R Dataframe can be acessed using the function colnames(). Hi I have a dataframe (loaded CSV) where the inferredSchema filled the column names from the file. Example - Spark - Add new column to Spark Dataset. Starting from 1. DataFrames are composed of Row objects accompanied with a schema which describes the data types of each column. Spark SQL functions take org. 11/13/2017; 34 minutes to read +5; In this article. column_name. There are generally two ways to dynamically add columns to a dataframe in Spark. col( "age" ); // in Java Note that the Column type can also be manipulated through its various functions. I want a generic reduceBy function, that works like an RDD's reduceByKey, but will let me group data by any column in a Spark DataFrame. Interestingly, we can also rename a column this way. The Scala foldLeft method can be used to iterate over a data structure and perform multiple operations on a Spark DataFrame. groupBy retains grouping columns; Upgrading from Spark SQL 1. Conceptually, it is equivalent to relational tables with good optimizati. In this talk, we will discuss about internals of dataframe. Let's discuss all possible ways to rename column with Scala examples. This page shows how to operate with Hive in Spark including: Create DataFrame from existing Hive table Save DataFrame to a new Hive table Append data. That we call on SparkDataFrame. Encode and assemble multiple features in PySpark. Spark doesn't provide a clean way to chain SQL function calls, so you will have to monkey patch the org. You will probably find useful information on StackOverflow (for example, here is a similar question—but don’t use the accepted answer, it may fail for non-trivial datasets). For grouping by percentiles, I suggest defining a new column via a user-defined function (UDF), and using groupBy on that column. import org. You can vote up the examples you like and your votes will be used in our system to product more good examples. But in the above case, there isn't much freedom. You may access the tutorials in any order you choose. Filtering can be applied on one column or multiple column (also known as multiple condition ). columns = new_column_name_list However, the same doesn't work in pyspark dataframes created using sqlContext. Apache Spark groupBy Example. selectExpr("air_time/60 as duration_hrs") with the SQL as keyword being equivalent to the. spark scala talks The below video is a screen cast of my talk on Anatomy of Data Frame API : Deep dive into Spark SQL Data Frame API in recent spark meetup. Derive multiple columns from a single column in a Spark DataFrame; Apache Spark — Assign the result of UDF to multiple dataframe columns; How to check if spark dataframe is empty; How do I check for equality using Spark Dataframe without SQL Query? Dataframe sample in Apache spark | Scala. 2 sqlContext. With this explicitly set schema, we can define the columns' name as well as their types; otherwise the column name would be the default ones derived by Spark, such as _col0, etc. Rename column headers in pandas.