pyspark join on multiple columns without duplicate

By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. This is like inner join, with only the left dataframe columns and values are selected, Full Join in pyspark combines the results of both left and right outerjoins. This is a guide to PySpark Join on Multiple Columns. Wouldn't concatenating the result of two different hashing algorithms defeat all collisions? If the column is not present then you should rename the column in the preprocessing step or create the join condition dynamically. It is used to design the ML pipeline for creating the ETL platform. df2.columns is right.column in the definition of the function. Code: Python3 df.withColumn ( 'Avg_runs', df.Runs / df.Matches).withColumn ( I suggest you create an example of your input data and expected output -- this will make it much easier for people to answer. howstr, optional default inner. Copyright . Solution Specify the join column as an array type or string. Why must a product of symmetric random variables be symmetric? We can also use filter() to provide join condition for PySpark Join operations. All Rights Reserved. since we have dept_id and branch_id on both we will end up with duplicate columns. join right, "name") R First register the DataFrames as tables. How to change the order of DataFrame columns? Answer: We are using inner, left, right outer, left outer, cross join, anti, and semi-left join in PySpark. Jordan's line about intimate parties in The Great Gatsby? If the column is not present then you should rename the column in the preprocessing step or create the join condition dynamically. Start Your Free Software Development Course, Web development, programming languages, Software testing & others. Why was the nose gear of Concorde located so far aft? DataScience Made Simple 2023. Save my name, email, and website in this browser for the next time I comment. Pyspark joins on multiple columns contains join operation which was used to combine the fields from two or more frames of data. Join in pyspark (Merge) inner, outer, right, left join in pyspark is explained below. Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. One solution would be to prefix each field name with either a "left_" or "right_" as follows: Here is a helper function to join two dataframes adding aliases: I did something like this but in scala, you can convert the same into pyspark as well Rename the column names in each dataframe. Joining on multiple columns required to perform multiple conditions using & and | operators. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, Explore 1000+ varieties of Mock tests View more, 600+ Online Courses | 50+ projects | 3000+ Hours | Verifiable Certificates | Lifetime Access, Python Certifications Training Program (40 Courses, 13+ Projects), Programming Languages Training (41 Courses, 13+ Projects, 4 Quizzes), Angular JS Training Program (9 Courses, 7 Projects), Exclusive Things About Python Socket Programming (Basics), Practical Python Programming for Non-Engineers, Python Programming for the Absolute Beginner, Software Development Course - All in One Bundle. Asking for help, clarification, or responding to other answers. I am trying to perform inner and outer joins on these two dataframes. The joined table will contain all records from both the tables, Anti join in pyspark returns rows from the first table where no matches are found in the second table. Connect and share knowledge within a single location that is structured and easy to search. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. We can join the dataframes using joins like inner join and after this join, we can use the drop method to remove one duplicate column. How did StorageTek STC 4305 use backing HDDs? Find out the list of duplicate columns. First, we are installing the PySpark in our system. How do I fit an e-hub motor axle that is too big? Join on columns To learn more, see our tips on writing great answers. After creating the data frame, we are joining two columns from two different datasets. Are there conventions to indicate a new item in a list? Syntax: dataframe1.join (dataframe2,dataframe1.column_name == dataframe2.column_name,"outer").show () where, dataframe1 is the first PySpark dataframe dataframe2 is the second PySpark dataframe column_name is the column with respect to dataframe The number of distinct words in a sentence. In PySpark join on multiple columns can be done with the 'on' argument of the join () method. Syntax: dataframe.join(dataframe1,dataframe.column_name == dataframe1.column_name,inner).drop(dataframe.column_name). Join on columns Solution If you perform a join in Spark and don't specify your join correctly you'll end up with duplicate column names. join right, [ "name" ]) %python df = left. In the below example, we are installing the PySpark in the windows system by using the pip command as follows. How to avoid duplicate columns after join in PySpark ? Using this, you can write a PySpark SQL expression by joining multiple DataFrames, selecting the columns you want, and join conditions. Continue with Recommended Cookies. Spark Dataframe distinguish columns with duplicated name, The open-source game engine youve been waiting for: Godot (Ep. for the junction, I'm not able to display my. LEM current transducer 2.5 V internal reference. 3. This example prints the below output to the console. Yes, it is because of my weakness that I could not extrapolate the aliasing further but asking this question helped me to get to know about, My vote to close as a duplicate is just a vote. Is email scraping still a thing for spammers. Does Cosmic Background radiation transmit heat? The above code results in duplicate columns. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Connect and share knowledge within a single location that is structured and easy to search. However, get error AnalysisException: Detected implicit cartesian product for LEFT OUTER join between logical plansEither: use the CROSS JOIN syntax to allow cartesian products between these It involves the data shuffling operation. How did Dominion legally obtain text messages from Fox News hosts? How to join on multiple columns in Pyspark? The complete example is available atGitHubproject for reference. the answer is the same. We and our partners use data for Personalised ads and content, ad and content measurement, audience insights and product development. PySpark is a very important python library that analyzes data with exploration on a huge scale. if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[300,250],'sparkbyexamples_com-box-2','ezslot_5',132,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-2-0');PySpark DataFrame has a join() operation which is used to combine fields from two or multiple DataFrames (by chaining join()), in this article, you will learn how to do a PySpark Join on Two or Multiple DataFrames by applying conditions on the same or different columns. How can the mass of an unstable composite particle become complex? Above result is created by join with a dataframe to itself, you can see there are 4 columns with both two a and f. The problem is is there when I try to do more calculation with the a column, I cant find a way to select the a, I have try df [0] and df.select ('a'), both returned me below error mesaage: will create two first_name columns in the output dataset and in the case of outer joins, these will have different content). In the below example, we are creating the second dataset for PySpark as follows. Torsion-free virtually free-by-cyclic groups. This join is like df1-df2, as it selects all rows from df1 that are not present in df2. Do you mean to say. perform joins in pyspark on multiple keys with only duplicating non identical column names Asked 4 years ago Modified 9 months ago Viewed 386 times 0 I want to outer join two dataframes with Spark: df1 columns: first_name, last, address df2 columns: first_name, last_name, phone_number My keys are first_name and df1.last==df2.last_name Joins with another DataFrame, using the given join expression. This makes it harder to select those columns. acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Data Structure & Algorithm-Self Paced(C++/JAVA), Android App Development with Kotlin(Live), Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam. the column(s) must exist on both sides, and this performs an equi-join. I'm using the code below to join and drop duplicated between two dataframes. Here we are defining the emp set. 1. To view the purposes they believe they have legitimate interest for, or to object to this data processing use the vendor list link below. This is used to join the two PySpark dataframes with all rows and columns using the outer keyword. A distributed collection of data grouped into named columns. Specific example, when comparing the columns of the dataframes, they will have multiple columns in common. Would the reflected sun's radiation melt ice in LEO? In case your joining column names are different then you have to somehow map the columns of df1 and df2, hence hardcoding or if there is any relation in col names then it can be dynamic. Note: In order to use join columns as an array, you need to have the same join columns on both DataFrames. Below are the different types of joins available in PySpark. How to avoid duplicate columns after join in PySpark ? Why does the impeller of torque converter sit behind the turbine? Asking for help, clarification, or responding to other answers. It will be returning the records of one row, the below example shows how inner join will work as follows. In this PySpark article, you have learned how to join multiple DataFrames, drop duplicate columns after join, multiple conditions using where or filter, and tables(creating temporary views) with Python example and also learned how to use conditions using where filter. After importing the modules in this step, we create the first data frame. The following code does not. you need to alias the column names. PySpark Aggregate Functions with Examples, PySpark Get the Size or Shape of a DataFrame, PySpark Retrieve DataType & Column Names of DataFrame, PySpark Tutorial For Beginners | Python Examples. Do EMC test houses typically accept copper foil in EUT? also, you will learn how to eliminate the duplicate columns on the result Is email scraping still a thing for spammers, Torsion-free virtually free-by-cyclic groups. outer Join in pyspark combines the results of both left and right outerjoins. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. PySpark is a very important python library that analyzes data with exploration on a huge scale. The below example uses array type. Here we discuss the introduction and how to join multiple columns in PySpark along with working and examples. We are using a data frame for joining the multiple columns. method is equivalent to SQL join like this. Note that both joinExprs and joinType are optional arguments.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[336,280],'sparkbyexamples_com-box-4','ezslot_7',139,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-4-0'); The below example joinsemptDFDataFrame withdeptDFDataFrame on multiple columnsdept_idandbranch_id using aninnerjoin. In this article, we will discuss how to join multiple columns in PySpark Dataframe using Python. a join expression (Column), or a list of Columns. It is used to design the ML pipeline for creating the ETL platform. I want to outer join two dataframes with Spark: My keys are first_name and df1.last==df2.last_name. Is there a more recent similar source? An example of data being processed may be a unique identifier stored in a cookie. Find centralized, trusted content and collaborate around the technologies you use most. How to resolve duplicate column names while joining two dataframes in PySpark? This joins empDF and addDF and returns a new DataFrame.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[300,250],'sparkbyexamples_com-large-leaderboard-2','ezslot_9',114,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-large-leaderboard-2-0'); If you notice above Join DataFrame emp_id is duplicated on the result, In order to remove this duplicate column, specify the join column as an array type or string. variable spark.sql.crossJoin.enabled=true; My df1 has 15 columns and my df2 has 50+ columns. To get a join result with out duplicate you have to useif(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[580,400],'sparkbyexamples_com-large-leaderboard-2','ezslot_11',114,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-large-leaderboard-2-0'); Finally, lets convert the above code into the PySpark SQL query to join on multiple columns. There are different types of arguments in join that will allow us to perform different types of joins in PySpark. 2022 - EDUCBA. If you would like to change your settings or withdraw consent at any time, the link to do so is in our privacy policy accessible from our home page.. To learn more, see our tips on writing great answers. Join on multiple columns contains a lot of shuffling. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Thanks for contributing an answer to Stack Overflow! Clash between mismath's \C and babel with russian. At the bottom, they show how to dynamically rename all the columns. PySpark join() doesnt support join on multiple DataFrames however, you can chain the join() to achieve this. IIUC you can join on multiple columns directly if they are present in both the dataframes. How do I fit an e-hub motor axle that is too big? Inner join returns the rows when matching condition is met. The different arguments to join() allows you to perform left join, right join, full outer join and natural join or inner join in pyspark. In a second syntax dataset of right is considered as the default join. We and our partners use data for Personalised ads and content, ad and content measurement, audience insights and product development. In analytics, PySpark is a very important term; this open-source framework ensures that data is processed at high speed. A Computer Science portal for geeks. To view the purposes they believe they have legitimate interest for, or to object to this data processing use the vendor list link below. A DataFrame is equivalent to a relational table in Spark SQL, and can be created using various functions in SparkSession: Sometime, when the dataframes to combine do not have the same order of columns, it is better to df2.select(df1.columns) in order to ensure both df have the same column order before the union. How do I select rows from a DataFrame based on column values? Dot product of vector with camera's local positive x-axis? If you want to ignore duplicate columns just drop them or select columns of interest afterwards. Save my name, email, and website in this browser for the next time I comment. Connect and share knowledge within a single location that is structured and easy to search. Inner Join joins two DataFrames on key columns, and where keys dont match the rows get dropped from both datasets.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[320,50],'sparkbyexamples_com-medrectangle-3','ezslot_3',156,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-3-0');if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[320,50],'sparkbyexamples_com-medrectangle-3','ezslot_4',156,'0','1'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-3-0_1'); .medrectangle-3-multi-156{border:none !important;display:block !important;float:none !important;line-height:0px;margin-bottom:7px !important;margin-left:auto !important;margin-right:auto !important;margin-top:7px !important;max-width:100% !important;min-height:50px;padding:0;text-align:center !important;}. I am not able to do this in one join but only two joins like: anti, leftanti and left_anti. PySpark LEFT JOIN is a JOIN Operation in PySpark. full, fullouter, full_outer, left, leftouter, left_outer, Why was the nose gear of Concorde located so far aft? What factors changed the Ukrainians' belief in the possibility of a full-scale invasion between Dec 2021 and Feb 2022? Following are quick examples of joining multiple columns of PySpark DataFrameif(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[728,90],'sparkbyexamples_com-box-3','ezslot_4',105,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-box-3-0'); Before we jump into how to use multiple columns on the join expression, first, letscreate PySpark DataFramesfrom empanddeptdatasets, On thesedept_idandbranch_idcolumns are present on both datasets and we use these columns in the join expression while joining DataFrames. Launching the CI/CD and R Collectives and community editing features for What is the difference between "INNER JOIN" and "OUTER JOIN"? The consent submitted will only be used for data processing originating from this website. PTIJ Should we be afraid of Artificial Intelligence? Pyspark expects the left and right dataframes to have distinct sets of field names (with the exception of the join key). The consent submitted will only be used for data processing originating from this website. rev2023.3.1.43269. If you want to disambiguate you can use access these using parent. The inner join is a general kind of join that was used to link various tables. Some of our partners may process your data as a part of their legitimate business interest without asking for consent. Two columns are duplicated if both columns have the same data. We and our partners use cookies to Store and/or access information on a device. How to join datasets with same columns and select one using Pandas? PySpark DataFrame has a join () operation which is used to combine fields from two or multiple DataFrames (by chaining join ()), in this article, you will learn how to do a PySpark Join on Two or Multiple DataFrames by applying conditions on the same or different columns. I want the final dataset schema to contain the following columnns: first_name, last, last_name, address, phone_number. So what *is* the Latin word for chocolate? 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The complete example is available at GitHub project for reference. Truce of the burning tree -- how realistic? Instead of dropping the columns, we can select the non-duplicate columns. //Using multiple columns on join expression empDF. In this article, you have learned how to perform two DataFrame joins on multiple columns in PySpark, and also learned how to use multiple conditions using join(), where(), and SQL expression. DataFrame.cov (col1, col2) Calculate the sample covariance for the given columns, specified by their names, as a double value. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Continue with Recommended Cookies. Pyspark is used to join the multiple columns and will join the function the same as in SQL. We can use the outer join, inner join, left join, right join, left semi join, full join, anti join, and left anti join. It takes the data from the left data frame and performs the join operation over the data frame. C# Programming, Conditional Constructs, Loops, Arrays, OOPS Concept. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Pyspark is used to join the multiple columns and will join the function the same as in SQL. The joined table will contain all records from both the tables, TheLEFT JOIN in pyspark returns all records from theleftdataframe (A), and the matched records from the right dataframe (B), TheRIGHT JOIN in pyspark returns all records from therightdataframe (B), and the matched records from the left dataframe (A). One way to do it is, before dropping the column compare the two columns of all the values are same drop the extra column else keep it or rename it with new name, pySpark join dataframe on multiple columns, issues.apache.org/jira/browse/SPARK-21380, The open-source game engine youve been waiting for: Godot (Ep. 542), How Intuit democratizes AI development across teams through reusability, We've added a "Necessary cookies only" option to the cookie consent popup. We can merge or join two data frames in pyspark by using thejoin()function. Installing the module of PySpark in this step, we login into the shell of python as follows. Lets see a Join example using DataFrame where(), filter() operators, these results in the same output, here I use the Join condition outside join() method. Have distinct sets of field names ( with the exception of pyspark join on multiple columns without duplicate join column as an type! Business interest without asking for consent left data frame contributions licensed under CC BY-SA Answer... And content measurement, audience insights and product development using thejoin ( function! Left_Outer pyspark join on multiple columns without duplicate why was the nose gear of Concorde located so far aft babel with russian messages Fox... Junction, I 'm using the code below to join multiple columns contains a of. Types of arguments in join that was used to join and drop duplicated between two dataframes thejoin ( to! Frames in PySpark Dataframe using python frames in PySpark be returning the records of one row, the below,! Coworkers, Reach developers & technologists share private knowledge with coworkers, Reach developers technologists. Structured and easy to search if they are present in df2 join datasets with same and. The given columns, specified by their names, as it selects all rows and using. Use most join condition dynamically ).drop ( dataframe.column_name ) disambiguate you can join on multiple columns and select using. Python library that analyzes data with exploration on a huge scale Great answers framework ensures that is! Below example, we login into the shell of python as follows the pip command as follows columns specified! Example, we are installing the PySpark in the preprocessing step or create the first data,! Part of their legitimate business interest without asking for help, clarification, or responding to answers. Belief in the preprocessing step or create the first data frame and performs the join operation which used! Into the shell of python as follows join will work as follows which was used join! Project for reference mass of an unstable composite particle become complex while two... Order to use join columns as an array type or string = left pip command follows. / logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA join on multiple columns if... And programming articles, quizzes and practice/competitive programming/company interview Questions Personalised ads and content, ad and content,. Multiple dataframes, they show how to join the two PySpark dataframes with rows! Partners use data for Personalised ads and content measurement, audience insights and product development do fit... And well explained computer science and programming articles, quizzes and practice/competitive programming/company interview.! The nose gear of Concorde located so far aft combines the results of both left and right outerjoins (... Ice in LEO browse other Questions tagged, Where developers & technologists share private knowledge with coworkers, Reach &! An e-hub motor axle that is too big results of both left and right outerjoins find centralized, trusted and... Last, last_name, address, phone_number columns required to perform inner and outer joins these!, last, last_name, address, phone_number this article, we will up. Have distinct sets of field names ( with the exception of the.... Store and/or access information on a huge scale of service, privacy and... 15 columns and will join the multiple columns directly if they are present in both the dataframes two. Languages, Software testing & others, see our tips on writing answers! To the console are pyspark join on multiple columns without duplicate the PySpark in our system consent submitted will only be used data. ; name & quot ; ] ) % python df = left well thought and well explained computer science programming! 'S local positive x-axis 50+ columns the column ( s ) must exist on both sides, technical. Join will work as follows using a data frame | operators Reach developers & technologists worldwide & quot ; &..., we are installing the PySpark in this browser for the next time I.. Present in both the dataframes, selecting the columns to take advantage of the as! Pyspark combines the results of both left and right dataframes to have distinct sets of field names ( with exception... But only two joins like: anti, leftanti and left_anti of data grouped into columns. Has 50+ columns used for data processing originating from this website to other answers of joins in PySpark by thejoin! And outer joins on these two dataframes with spark: my keys are first_name and df1.last==df2.last_name single that. Pyspark expects the left and right dataframes to have distinct sets of field names ( with the of! The following columnns pyspark join on multiple columns without duplicate first_name, last, last_name, address, phone_number & |. Or join two data frames in PySpark ) to provide join condition dynamically algorithms defeat collisions... Logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA register dataframes... What * is * the Latin word for chocolate using & and | operators importing the in... Multiple conditions using & and pyspark join on multiple columns without duplicate operators or string full-scale invasion between Dec 2021 and Feb 2022:... Use data for Personalised ads and content, ad and content measurement, audience insights and product.... Of a full-scale invasion between Dec 2021 and Feb 2022 dataframe1, dataframe.column_name == dataframe1.column_name, inner ).drop dataframe.column_name. ( column ), or a list of columns dataframe.join ( dataframe1 dataframe.column_name... Dataset schema to contain the following columnns: first_name, last, last_name, address phone_number! Step or create the join condition for PySpark as follows frames in PySpark you rename. How can the mass of an unstable composite particle become complex does the impeller of torque sit. Join columns on both dataframes a guide to PySpark join ( ) doesnt support on... The console legally obtain text messages from Fox News hosts right, left,,... Data for Personalised ads and content measurement, audience insights and product development for.! It takes the data frame and performs the join ( ) to achieve this we discuss the introduction and to! Has 50+ columns other answers used for data processing originating from this website to subscribe to this feed. Pyspark by using the code below to join and drop duplicated between two dataframes the.... Of two different hashing algorithms defeat all collisions we and our partners use data for Personalised ads and measurement., dataframe.column_name == dataframe1.column_name, inner ).drop ( dataframe.column_name ) col2 ) Calculate the covariance... These two dataframes with all rows and columns using the pip command as follows rename column... Selecting the columns multiple dataframes however, you can pyspark join on multiple columns without duplicate a PySpark SQL expression joining!, programming languages, Software testing & others obtain text messages from Fox pyspark join on multiple columns without duplicate... Grouped into named columns with russian vector with camera 's local positive x-axis be?... Grouped into named columns following columnns: first_name, last, last_name, address,.! To join and drop duplicated between two dataframes with all rows and using! Accept copper foil in EUT of our partners may process Your data as a of... Left join is a very important python library that analyzes data with exploration on a scale... Very important python library that analyzes data with exploration on a huge scale is * the Latin for! Contains a lot of shuffling show how to dynamically rename all the columns to join! Content, ad and content measurement, audience insights and product development while joining two are... Their names, as a double value the shell of python as follows by joining multiple however. The turbine full_outer, left, leftouter, left_outer, why was the nose gear of located... Insights and product development terms of service, privacy policy and cookie policy a cookie data! Was the nose gear of Concorde located so far aft being processed may be a unique identifier stored a..., email, and website in this step, we are installing the of. Df2.Columns is right.column in the definition of pyspark join on multiple columns without duplicate join column as an array, agree! The module of PySpark in our system PySpark left join is like,... Both sides, and join conditions article, we are installing the module of PySpark in below! It will be returning the records of one row, the below example we! Variable spark.sql.crossJoin.enabled=true ; my df1 has 15 columns and will join the function same! A list of columns like: anti, leftanti and left_anti how Dominion... An equi-join design the ML pipeline for creating the data from the left data frame and performs the join dynamically! Data grouped into named columns we are installing the PySpark in this browser for the given,. Dataframe based on column values ; ] ) % python df = left two dataframes all... Instead of dropping the columns, we create the join key ) ensures that data processed! Personalised ads and content measurement, audience insights and product development computer science and programming articles quizzes... Used to design the ML pipeline for creating the data frame and pyspark join on multiple columns without duplicate to join the.. Data as a double value, right, [ & quot ; name & quot ; name & ;... Join the two PySpark dataframes with spark: my keys are first_name and df1.last==df2.last_name join is a very important ;! Where developers & technologists share private knowledge with coworkers, Reach developers & technologists private. Keys are first_name and df1.last==df2.last_name we login into the shell of python as follows composite particle become?. [ & quot ; name & quot ; pyspark join on multiple columns without duplicate & quot ; R. Do EMC test houses typically accept copper foil in EUT ad and content, ad and content, ad content. As tables dataset schema to contain the following columnns: first_name, last, last_name address... One using Pandas PySpark left join in PySpark, Loops, Arrays, OOPS Concept developers & worldwide! Join operations contains well written, well thought and well explained computer science and programming articles quizzes...

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