Requirement
Assume that you want to load file (which have a pipe(|) separated values) in pig and store the output delimited by a comma (‘,’).
Solution
Follow the below steps:
Step 1: Sample file
Create a sample file named as sample_1.txt file.
If you have any sample data with you, then put the content in that file with a delimiter pipe (‘|’). If you have created a file in windows, then transfer it to your Linux machine via WinSCP.
You can get the file from here sample_1
I have a local directory as /root/bigdataprogrammers/input_files, so I have placed a sample_1.txt file in that directory.
You can see the content of that file using below command in the shell:
cat /root/bigdataprogrammers/input_files/sample_1.txt
It will show the file content:-
Step 2: Load Data in Pig
Now, I will load the file in pig, because the file is present in local, so here I prefer pig in local mode. In real time pig MapReduce mode works.
Enter a below-mentioned command in putty
pig -x local
It will take you to the grunt shell. Type the below-mentioned command in grunt shell.
MyPSVData = LOAD '/root/bigdataprogrammers/input_files/sample_1.txt' using PigStorage('|') AS (id:chararray,code:chararray);
You can see whether the file is loaded or not using below command:-
dump MyPSVData
It will show the content of relation MyPSVData.
Step 3: Store output data in Pig
You can store this relation(MyPSVData) using STORE command in pig, assume that you want output file in comma delimited format.
Enter below command to store the relation into comma delimited file. It will be stored in a psv_to_comma directory which will be created dynamically, make sure that you do not have the same directory already present in your output directory.
STORE MyPSVData INTO '/root/bigdataprogrammers/output_files/psv_to_comma' using PigStorage(',');
Step 4: Show Output
Come out of grunt shell by pressing ctrl+c
Use below command to see the output:
cat root/bigdataprogrammers/output_files/psv_to_comma/*
keep learning.
Don’t miss the tutorial on Top Big data courses on Udemy you should Buy