Drop Two Columns In Spark Dataframe

In this blog we describe two schemes that can be used to partially cache the data by vertical and/or horizontal partitioning of the Distributed Data Frame (DDF) representing the data. Proposal: If a column is added to a DataFrame with a column of the same name, then the new column should replace the old column. June 01, 2019. So the output will be. Home > Removing duplicates from rows based on specific columns in an RDD/Spark DataFrame Removing duplicates from rows based on specific columns in an RDD/Spark DataFrame Let's say I have a rather large dataset in the following form:. How to do Diff of Spark dataframe Apache spark does not provide diff or subtract method for Dataframes. A way to Merge Columns of DataFrames in Spark with no Common Column Key March 22, 2017 Made post at Databricks forum, thinking about how to take two DataFrames of the same number of rows and combine, merge, all columns into one DataFrame. How to add new column in Spark Dataframe. In one of the assignments of Computing for Data Analysis we needed to sort a data frame based on the values in two of the columns and then return the top value. So i have created a Scala List of 100 column names. What I want to do is that by using Spark functions, replace the nulls in the "sum" column with the mean value of the previous and next variable in the "sum" column. Of course, whether this is referring to columns or rows in the DataFrame is dependent on the value of the axis parameter. this could be done by specifying columns with. But I have one more similar question. So the resultant dataframe will be. Tagged: spark dataframe like, spark dataframe not like, spark dataframe rlike With: 5 Comments LIKE condition is used in situation when you don't know the exact value or you are looking for some specific pattern in the output. So, for each row, search if an item is in the item list. I need to concatenate two columns in a dataframe. See GroupedData for all the available aggregate functions. If a list of dict/series is passed and the keys are all contained in the DataFrame’s index, the order of the columns in the resulting DataFrame will be unchanged. {SQLContext, Row, DataFrame, Column} import. Whether to drop rows in the resulting Frame/Series with missing values. 335485 1 -1. The Column. newdf = df. If we recall our word count example in Spark, RDD X has the distributed array of the words, with the map transformation we are mapping each element with integer 1 and creating a tuple like (word, 1). 0 and above uses the Spark Core RDD API, but in the past nine to ten months, two new APIs have been introduced that are, DataFrame and DataSets. What’s New in 0. Spark SQL - DataFrames - A DataFrame is a distributed collection of data, which is organized into named columns. Step 3: Remove duplicates from Pandas DataFrame. Think about it as a table in a relational database. name != 'Tina']. Refer to SPARK-7990: Add methods to facilitate equi-join on multiple join keys. You can vote up the examples you like and your votes will be used in our system to generate more good examples. partitionBy() from removing partitioned columns from schema 1 Answer Can I save an RDD as Parquet Files? 2 Answers join multiple tables and partitionby the result by columns 1 Answer Spark DataFrame groupby, sql, cube - alternatives and optimization 0 Answers. col("col1", "col2")) – JKC Sep 5 '17 at 5:46. Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. This is a variant of groupBy that can only group by existing columns using column names (i. def split_data_frame_list (df, target_column, output_type = float): ''' Accepts a column with multiple types and splits list variables to several rows. The list of columns and the types in those columns the schema. Drop duplicate columns on a dataframe in spark. See SPARK-11884 ( Drop multiple columns in the DataFrame API ) and SPARK-12204 ( Implement drop method for DataFrame in SparkR ) for detials. Thankfully this is very easy to do in Spark using Spark SQL DataFrames. Filtering a row in Spark DataFrame based on matching values from a list How do I get number of columns in each line from a delimited file?? Cannot resolve. frame that preserved the original order of, one of the two merged, data. A simple but efficient way to drop columns. Two data frames are made. In similar to deleting a column of a data frame, to delete multiple columns of a data frame, we simply need to put all desired column into a vector and set them to NULL, for example, to delete the 2nd, 4th columns of the above data frame:. select(concat_ws(",",dfSource. That will return X values, each of which needs to be stored in their own separate column. drop() method as a list of strings. But I am not sure how to resolve this since I am still on a learnig proccess in spark. So i have created a Scala List of 100 column names. Since the difference is 94, there were 94 rows which had at least 1 Null value in any column. Proposal: If a column is added to a DataFrame with a column of the same name, then the new column should replace the old column. Filter multiple rows using isin in DataFrame; How to specify an index and column while creating DataFrame in Pandas? Calculate sum across rows and columns in Pandas DataFrame; How to check if a column exists in Pandas? How dynamically add rows to DataFrame? Drop columns with missing data in Pandas DataFrame. Drop a row if it contains a certain value (in this case, “Tina”) Specifically: Create a new dataframe called df that includes all rows where the value of a cell in the name column does not equal “Tina”. 5 Answers 5. R Tutorial - We shall learn to sort a data frame by column in ascending order and descending order with example R scripts using R with function and R order function. The groups are chosen from SparkDataFrames column(s). Drop a variable (column) Note: axis=1 denotes that we are referring to a column, not a row. Dropping multiple columns from Spark dataframe by Iterating through the columns from a Scala List of Column names. df: dataframe to split target_column: the column containing the values to split output_type: type of all outputs returns: a dataframe with each entry for the target column separated, with each element moved into a new row. Column = id Beside using the implicits conversions, you can create columns using col and column functions. Create Spark DataFrame From List[Any]. I am facing an issue here that I have a dataframe with 2 columns, "ID" and "Amount". 6 was the ability to pivot data, creating pivot tables, with a DataFrame (with Scala, Java, or Python). 2 Answers how to select top and last ranked record 0 Answers how to do column join in pyspark as like in oracle query as below 0 Answers column wise sum in PySpark dataframe 1 Answer. You can flatten multiple aggregations on a single columns using the following procedure:. To check if this is the case, we will first create a new boolean column, pickup_1st, based on the two datetime columns (creating new columns from existing ones in Spark dataframes is a frequently raised question – see Patrick’s comment in our previous post); then, we will check in how many records this is false (i. This post provides an example to show how to create a new dataframe by adding a new column to an existing dataframe. What’s New in 0. packages value set in spark_config(). Defaults to formula(x) in the data frame method for unstack. For every numerical column, we can see information such as count, mean, median, deviation, so on and so forth, to see immediately if there is something that doesn't look right. How to add new column in Spark Dataframe. Similarly, if columns are selected column names will be transformed to be unique if necessary (e. Column Age Deleted from DataFrame Drop Multiple Columns by Label Names in DataFrame. 6 was the ability to pivot data, creating pivot tables, with a DataFrame (with Scala, Java, or Python). Similar is the data frame in Python, which is labeled as two-dimensional data structures having different types of columns. Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. Pandas is one of those packages and makes importing and analyzing data much easier. display renders columns containing image data types as rich HTML. drop_duplicates¶ DataFrame. A data frame is a set of equal length objects. Observations in Spark DataFrame are organised under named columns, which helps Apache Spark to understand the schema of a DataFrame. Apache Spark map Example As you can see in above image RDD X is the source RDD and RDD Y is a resulting RDD. Spark; SPARK-7182 [SQL] Can't remove columns from DataFrame or save DataFrame from a join due to duplicate columns I'm having trouble saving a dataframe as. I got the output by using the below code, but I hope we can do the same with less code — perhaps in a single line. Tagged: spark dataframe like, spark dataframe not like, spark dataframe rlike With: 5 Comments LIKE condition is used in situation when you don’t know the exact value or you are looking for some specific pattern in the output. 0 with Python. SOLUTION 1 : Try something like this:. While join in Apache spark is very common. Problem; Solution. Let’s Start with a simple example of renaming the columns and then we will check the re-ordering and other actions we can perform using these functions. , data is organized into a set of columns as in RDBMS. Generally it retains the first row when duplicate rows are present. One of the many new features added in Spark 1. SparkSession(sparkContext, jsparkSession=None)¶. What I want to do is that by using Spark functions, replace the nulls in the "sum" column with the mean value of the previous and next variable in the "sum" column. You may need to add new columns in the existing SPARK dataframe as per the requirement. Column Age Deleted from DataFrame Drop Multiple Columns by Label Names in DataFrame. Sometimes after reading in data and cleaning it, you will end up with factor columns that have levels that should no longer be there. How To Drop Multiple Columns from a Dataframe? Pandas' drop function can be used to drop multiple columns as well. Drop column from a data frame. concatenating 2 text columns in a data. Filtering a row in Spark DataFrame based on matching values from a list How do I get number of columns in each line from a delimited file?? Cannot resolve. 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. Sorting by Column Index. To merge these two data frames, we add the argument by to the merge() function and set it at the number 0, which specifies the row names. DataFrames also allow you to intermix operations seamlessly with custom Python, R, Scala, and SQL code. The Scala foldLeft method can be used to iterate over a data structure and perform multiple operations on a Spark DataFrame. These are generic functions with methods for other R classes. Tehcnically, we're really creating a second DataFrame with the correct names. For example, drop the columns ‘Age’ & ‘Name’ from the dataframe object dfObj i. drop with two columns in Spark. id: Data frame identifier. Optimized Row Columnar (ORC) file format is a highly efficient columnar format to store Hive data with more than 1,000 columns and improve performance. Let us take an example Data frame as shown in the following :. It will reduce the redundancy in your code and decrease your code complexity. But the result is a dataframe with hierarchical columns, which are not very easy to work with. By default the data frames are merged on the columns with names they both have, but separate specifications of the columns can be given by by. Two columns returned as a DataFrame Picking certain values from a column. You can vote up the examples you like and your votes will be used in our system to generate more good examples. While being very powerful, the merge function does not (as of yet) offer to return a merged data. Package overview; 10 Minutes to pandas; Essential Basic Functionality; Intro to Data Structures. In both cases this will return a dataframe, where the columns are the numerical columns of the original dataframe, and the rows are the statistical values. In order to remove certain columns from dataframe, we can use pandas drop function. This is an expected behavior. If how is "all", then drop rows only if every specified column is null or NaN for that row. select multiple columns given a Sequence of column names joe Asked on January 12, 2019 in Apache-spark. Convert between DataFrame and SpatialRDD¶ DataFrame to SpatialRDD¶ Use GeoSparkSQL DataFrame-RDD Adapter to convert a DataFrame to an SpatialRDD. class pyspark. repartition('id') creates 200 partitions with ID partitioned based on Hash Partitioner. Hi I have a dataframe (loaded CSV) where the inferredSchema filled the column names from the file. As you can tell from my question, I am pretty new to Spark. HOT QUESTIONS. The goal is to extract calculated features from each array, and place in a new column in the same dataframe. Here is an example on how to use crosstab to obtain the contingency table. any() will work for a DataFrame object to indicate if any value is missing, in some cases it may be useful to also count the number of missing values across the entire DataFrame. def with_shares(dataframe): """ Assign each client a weight for the contribution toward the rollup aggregates. frame without the removed columns. Groups the DataFrame using the specified columns, so we can run aggregation on them. Spark DataFrame expand on a lot of these concepts, allowing you to transfer that knowledge easily by understanding the simple syntax of Spark DataFrames. In this blog post, I’ll help you get started using Apache Spark’s spark. So how do I add a new column (based on Python vector) to an existing DataFrame with PySpark? You cannot add an arbitrary column to a DataFrame in Spark. The following are top voted examples for showing how to use org. 5 Answers 5. Delete Multiple Columns By Index. Explain how to retrieve a data frame cell value with the square bracket operator. There are generally two ways to dynamically add columns to a dataframe in Spark. See Examples section. Is there any function in spark sql to do the same? Announcement! Career Guide 2019 is out now. Apart from that i also tried to save the joined dataframe as a table by registerTempTable and run the action on it to avoid lot of shuffling it didnt work either. Filtering a row in Spark DataFrame based on matching values from a list How do I get number of columns in each line from a delimited file?? Cannot resolve. Adding a column to a dataframe in R is not hard, but there are a few ways to do it. When column-binding, rows are matched by position, so all data frames must have the same number of rows. The Python Pandas data frame consists of the main three principal components, namely the data, index and the columns. For clusters running Databricks Runtime 4. How to Add Rows To A Dataframe (Multiple) If we needed to insert multiple rows into a r data frame, we have several options. Whenever you’re applying a similar operation to multiple columns in a Spark DataFrame, try to use foldLeft. DataFrame and Dataset Examples in Spark REPL. Introduction to Datasets The Datasets API provides the benefits of RDDs (strong typing, ability to use powerful lambda functions) with the benefits of Spark SQL's optimized execution engine. Spark SQL - DataFrames - A DataFrame is a distributed collection of data, which is organized into named columns. To remove duplicates from pandas DataFrame, you may use the following syntax that you saw at the beginning of this tutorial: DataFrame. Spark DataFrames provide an API to operate on tabular data. One typically drops columns, if the columns are not needed for further analysis. active oldest votes. Reading the Spark documentation I found an easier solution. dropoff seems to happen. We use the built-in functions and the withColumn() API to add new columns. Filtering a row in Spark DataFrame based on matching values from a list How do I get number of columns in each line from a delimited file?? Cannot resolve. Column // The target type triggers the implicit conversion to Column scala> val idCol: Column = $ "id" idCol: org. Have you ever been confused about the "right" way to select rows and columns from a DataFrame? pandas gives you an incredible number of options for doing so, but in this video, I'll outline the. cannot construct expressions). In order to remove certain columns from dataframe, we can use pandas drop function. What is difference between class and interface in C#; Mongoose. class pyspark. Change the order of columns in Pandas dataframe. Dplyr package in R is provided with select() function which is used to select or drop the columns based on conditions. %md Combine several columns into single column of sequence of values. A dataframe in Spark is similar to a SQL table, an R dataframe, or a pandas dataframe. Examine the DataFrame's. Specifically we can use createDataFrame and pass in the local R data. In preparation for this tutorial you need to download two The columns of a row in the result can be accessed by. Create a Spark DataFrame from Pandas or NumPy with Arrow If you are a Pandas or NumPy user and have ever tried to create a Spark DataFrame from local data, you might have noticed that it is an unbearably slow process. DataFrame API Examples. drop (self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') [source] ¶ Drop specified labels from rows or columns. rename() function and second by using df. You may want to separate a column in to multiple columns in a data frame or you may want to split a column of text and keep only a part of it. Data Frame Column Vector We reference a data frame column with the double square bracket "[[]]" operator. In Python's pandas library there are direct APIs to find out the duplicate rows, but there is no direct API to find the duplicate columns. ix[x,y] = new_value. , if columns are selected more than once, or if more than one column of a given name is selected if the data frame has duplicate column names). 1 and above, display attempts to render image thumbnails for DataFrame columns matching Spark’s ImageSchema. createDataFrame(Seq( (1, 1, 2, 3, 8, 4, 5). In such case, where each array only contains 2 items. What I want to do is that by using Spark functions, replace the nulls in the "sum" column with the mean value of the previous and next variable in the "sum" column. we will use | for or, & for and , ! for not. The Python Pandas data frame consists of the main three principal components, namely the data, index and the columns. this could be done by specifying columns with. DISTINCT or dropDuplicates is used to remove duplicate rows in the Dataframe. append() & loc[] , iloc[] Python Pandas : How to Drop rows in DataFrame by conditions on column values. Scalable Machine Learning on Big Data using Apache Spark. Observations in Spark DataFrame are organized under named columns, which helps Apache Spark to understand the schema of a DataFrame. However, I don't know if it is. Apache Spark map Example As you can see in above image RDD X is the source RDD and RDD Y is a resulting RDD. As a column-based abstraction, it is only fitting that a DataFrame can be read from or written to a real relational database table. I got the output by using the below code, but I hope we can do the same with less code — perhaps in a single line. GeoSpark 1. I would like to know , how to fix this. The column names are derived from the DataFrame’s schema field names, and must match the Phoenix column names. For In conclusion, I need to cast type of multiple columns manually:. These examples are extracted from open source projects. Also that code returns a character value for newValue because there's a character column in the data frame, but lop that out and everything is numeric again. You have to know the exact column and row references you want to extract. Explore careers to become a Big Data Developer or Architect!. Now, these basic ways of subsetting a data frame in R can become tedious with large data sets. the data in these data structures is to extract and “explode” the column into a new DataFrame using the explode. Dropping rows and columns in pandas dataframe. I have a dataframe which has columns around 400, I want to drop 100 columns as per my requirement. SparkSession import org. (length) values in a column. concatenating 2 text columns in a data. We use the built-in functions and the withColumn() API to add new columns. My columns I want to delete are listed in a vector called "delete". Problem; Solution. This new column can be initialized with a default value or you can assign some dynamic value to it depending on some logical conditions. SELECT primarily has two options: You can either SELECT all columns by specifying "*" in the SQL query; You can mention specific columns in the SQL query to pick only required columns; Now how do we do it in Spark ? 1) Show all columns from DataFrame. In order to test this directly in the pyspark shell, omit the line where sc is created. A DataFrame is a distributed collection of data organized into named columns. Or generate another data frame, then join with the original data frame. The classifier will be saved as an output and will be used in a Spark Structured Streaming realtime app to predict new test data. {SQLContext, Row, DataFrame, Column} import. It is conceptually equal to a table in a relational database. 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. newdf = df. def with_shares(dataframe): """ Assign each client a weight for the contribution toward the rollup aggregates. spark_read_csv: Read a CSV file into a Spark DataFrame in sparklyr: R Interface to Apache Spark rdrr. As a result I need to get back the modified data. As you already know, we can create new columns by calling withColumn() operation on a DataFrame, while passing the name of the new column (the first argument), as well as an operation for which values should live in each row of that column (second argument). Is there any function in spark sql to do the same? Announcement! Career Guide 2019 is out now. 2 thoughts on " Quick function to drop duplicated columns in Pandas DataFrame " Charlie June 23, 2017 at 11:57 AM. You want to re-compute factor levels of all factor columns in a data frame. The Column class represents a tree of operations to be applied to each input record: things like mathematical operations, comparisons, etc. As you can tell from my question, I am pretty new to Spark. DataFrame It is appeared in Spark Release 1. join(df2, usingColumns=Seq("col1", …), joinType="left"). We use the built-in functions and the withColumn() API to add new columns. select(myDF. 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. The goal is to extract calculated features from each array, and place in a new column in the same dataframe. Column names are verified to see if the Null column was inserted properly. Proposal: If a column is added to a DataFrame with a column of the same name, then the new column should replace the old column. But the result is a dataframe with hierarchical columns, which are not very easy to work with. A DataFrame is a Dataset organized into named columns. col("col1", "col2")) – JKC Sep 5 '17 at 5:46. Get the unique values (rows) of the dataframe in python pandas. I can write a function something like. Scala Spark DataFrame : dataFrame. They give slightly different results for two reasons: In Pandas, NaN values are excluded. How to Extract Nested JSON Data in Spark. Pandas drop function allows you to drop/remove one or more columns from a dataframe. The Column. As long as it is unique, you’re good to go. Let us load pandas and load gapminder data from a URL. DataFrame lets you create multiple columns with the same name, which causes problems when you try to refer to columns by name. VectorAssembler(). It consists of rows and columns. Which have two columns and both of them are of Int type. Had there been fewer columns, I could have used the select method in the. createDataFrame(Seq( (1, 1, 2, 3, 8, 4, 5). Users can use DataFrame API to perform various relational operations on both external data sources and Spark’s built-in distributed collections without providing specific procedures for processing data. Think about it as a table in a relational database. As a result I need to get back the modified data. With droplevels; With vapply and lapply; See also; Problem. I would like to know , how to fix this. libPaths() packages to each node, a list of packages to distribute, or a package bundle created with spark_apply_bundle(). Data scientist and armchair sabermetrician. Drop a row if it contains a certain value (in this case, “Tina”) Specifically: Create a new dataframe called df that includes all rows where the value of a cell in the name column does not equal “Tina”. DataFrame It is appeared in Spark Release 1. Step 3: Remove duplicates from Pandas DataFrame. Removing rows by the row index 2. Spark DataFrames API is a distributed collection of data organized into named columns and was created to support modern big data and data science applications. users can run a complex SQL query on top of an HBase table inside Spark, perform a table join against Dataframe, or integrate with Spark Streaming to implement a more complicated system. active oldest votes. Dataframe basics for PySpark. As a result I need to get back the modified data. A way to Merge Columns of DataFrames in Spark with no Common Column Key March 22, 2017 Made post at Databricks forum, thinking about how to take two DataFrames of the same number of rows and combine, merge, all columns into one DataFrame. I often need to perform an inverse selection of columns in a dataframe, or exclude some columns from a query. Spark Tutorial: Validating Data in a Spark DataFrame Part Two - DZone Big Data / Big. A foldLeft or a map (passing a RowEncoder). We can get the ndarray of column names from this Index object i. Step -2: Create a UDF which concatenates columns inside dataframe. I need to concatenate two columns in a dataframe. Drop column in R using Dplyr: Drop column in R can be done by using minus before the select function. Generally it retains the first row when duplicate rows are present. Appending multiple samples of a column into dataframe in spark. In this tutorial we will learn how to rename the column of dataframe in pandas. The names of the arguments to the case class are read using reflection and they become the names of the columns. Apache Spark filter Example As you can see in above image RDD X is the source RDD and contains elements 1 to 5 and has two partitions. 3, and Spark 1. Think about it as a table in a relational database. Optimized Row Columnar (ORC) file format is a highly efficient columnar format to store Hive data with more than 1,000 columns and improve performance. Delete Multiple Columns Of A Data Frame 4. So the resultant dataframe will be. I can perform almost all the SQL operations on it in SPARK-SQL. join method is equivalent to SQL join like this. Delete Multiple Columns By Index. I have been using spark’s dataframe API for quite sometime and often I would want to add many columns to a dataframe(for ex : Creating more features from existing features for a machine learning model) and find it hard to write many withColumn statements. 0 (which is currently unreleased), Here we can join on multiple DataFrame columns. Lowercase all columns with reduce. Drop column in R using Dplyr: Drop column in R can be done by using minus before the select function. drop_duplicates¶ DataFrame. Here pyspark. If that count is less than the number of columns, then that row does not have all rows. drop with two columns in Spark. Python Pandas - DataFrame - A Data frame is a two-dimensional data structure, i. In [8]: df = DataFrame(randn(10,2),columns=['foo','bar']) In [9]: df. To the udf “addColumnUDF” we pass 2 columns of the DataFrame “inputDataFrame”. But I have one more similar question. How to select all columns of a dataframe in join - Spark-scala side dataframe from a joined dataframe. How to select all columns of a dataframe in join - Spark-scala side dataframe from a joined dataframe. frame without the removed columns. columns, which is the list representation of all the columns in dataframe. split() can be used - When there is need to flatten the nested ArrayType column into multiple top-level columns. Filtering a row in Spark DataFrame based on matching values from a list How do I get number of columns in each line from a delimited file?? Cannot resolve. So i have created a Scala List of 100 column names. _ import org. This function returns a class ClassXYZ, with multiple variables, and each of. Each row is a measurement of some instance while column is a vector which contains data for some specific attribute/variable. toPandas() method should only be used if the resulting Pandas's DataFrame is expected to be small, as all the data is loaded into the driver's memory (you can look at the code at: apache/spark). See SPARK-11884 (Drop multiple columns in the DataFrame API) and SPARK-12204 (Implement drop method for DataFrame in SparkR) for detials. Thumbnail rendering works for any images successfully read in through the readImages function. setLogLevel(newLevel). SOLUTION 1 : Try something like this:. This is a variant of groupBy that can only group by existing columns using column names (i. Most operations require a copy to avoid data aliasing. The column names of the returned data. drop(['A'], axis=1) To delete the column permanently from original dataframe df, you can use the option inplace=True df. As a column-based abstraction, it is only fitting that a DataFrame can be read from or written to a real relational database table. In this article, we discuss how to validate data in a Spark DataFrame using User Defined Functions in Scala. Column = id Beside using the implicits conversions, you can create columns using col and column functions. join function: [code]df1. The columns can also be renamed by directly assigning a list containing the new names to the columns attribute of the dataframe object for which we want to rename the columns. frame to create a SparkDataFrame. Example #2: Changing axis and using how and inplace Parameters. Is there a direct SPARK Data Frame API call to do this? In R Data Frames, I see that there a merge function to merge two data frames. 4, you can finally port pretty much any relevant piece of Pandas’ DataFrame computation to Apache Spark parallel computation framework using Spark SQL’s DataFrame. This post provides an example to show how to create a new dataframe by adding a new column to an existing dataframe. How to add new column in Spark Dataframe. Groups the DataFrame using the specified columns, so we can run aggregation on them. Apache Spark (big Data) DataFrame - Things to know One of the feature in Dataframe is if you cache a Dataframe , it can compress the column value based on the type defined in the column. In essence, a Spark DataFrame is functionally equivalent to a relational database table, which is reinforced by the Spark DataFrame interface and is designed for SQL-style queries. Row consists of columns, if you are selecting only one column then output will be unique values for that specific column. In Spark, dataframe is actually a wrapper around RDDs, the basic data structure in Spark.