![]() ![]() An important point to note during the execution of the WordCount example is that the mapper class in the WordCount program will execute completely on the entire input file and not just a single sentence. This is how the MapReduce word count program executes and outputs the number of occurrences of a word in any given input file. After the execution of the reduce phase of MapReduce WordCount example program, appears as a key only once but with a count of 2 as shown below - (an,2) In our example “An elephant is an animal.” is the only word that appears twice in the sentence. The reducer phase takes the output of shuffle phase as input and then reduces the key-value pairs to unique keys with values added up. It is like an aggregation phase for the keys generated by the map phase. ![]() In the reduce phase, all the keys are grouped together and the values for similar keys are added up to find the occurrences for a particular word. Hadoop WordCount Example- Reducer Phase Execution After the shuffle phase is executed from the WordCount example code, the output will look like this - (an,1) Hadoop WordCount Example- Shuffle Phase ExecutionĪfter the map phase execution is completed successfully, shuffle phase is executed automatically wherein the key-value pairs generated in the map phase are taken as input and then sorted in alphabetical order. ![]() Key-Value pairs from Hadoop Map Phase Execution- (an,1) In this case, the entire sentence will be split into 5 tokens (one for each word) with a value 1 as shown below – The mapper phase in the WordCount example will split the string into individual tokens i.e. The key is the word from the input file and value is ‘1’.įor instance if you consider the sentence “An elephant is an animal”. The text from the input text file is tokenized into words to form a key value pair with all the words present in the input text file. Hadoop WordCount Example- Mapper Phase Execution Hadoop WordCount operation occurs in 3 stages – Word Count - Hadoop Map Reduce Example – How it works? Eclipse must be installed as the MapReduce WordCount example will be run from eclipse IDE.Single node hadoop cluster must be configured and running.Hadoop Installation must be completed successfully.Pre-requisites to follow this Hadoop WordCount Example Tutorial This tutorial will help hadoop developers learn how to implement WordCount example code in MapReduce to count the number of occurrences of a given word in the input file. Hadoop MapReduce WordCount example is a standard example where hadoop developers begin their hands-on programming with. This hadoop tutorial aims to give hadoop developers a great start in the world of hadoop mapreduce programming by giving them a hands-on experience in developing their first hadoop based WordCount application. What will you learn from this Hadoop MapReduce Tutorial? ![]()
0 Comments
Leave a Reply. |