You can store the loaded data in the file system using the store operator. This blog explains how to store data in Apache Pig using the Store operator.
Syntax
Given below is the syntax of the Store statement.
STORE Relation_name INTO ‘ required_directory_path ‘ [USING function];
Example
Assume we have a file student_data.txt in HDFS with the following content.
001,Rajiv,Reddy,9848022337,Hyderabad
002,siddarth,Battacharya,9848022338,Kolkata
003,Rajesh,Khanna,9848022339,Delhi
004,Preethi,Agarwal,9848022330,Pune
005,Trupthi,Mohanthy,9848022336,Bhuwaneshwar
006,Archana,Mishra,9848022335,Chennai.
And we have read it into a relation student using the LOAD operator as shown below.
grunt> student = LOAD ‘hdfs://localhost:9000/pig_data/student_data.txt’
USING PigStorage(‘,’)
as ( id:int, firstname:chararray, lastname:chararray, phone:chararray,
city:chararray );
Now, let us store the relation in the HDFS directory “/pig_Output/” as shown below.
grunt> STORE student INTO ‘ hdfs://localhost:9000/pig_Output/ ‘ USING PigStorage (‘,’);
Output
After executing the store statement, you will get the following output. A directory is created with the specified name and the data will be stored in it.
2015-10-05 13:05:05,429 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.
MapReduceLau ncher – 100% complete
2015-10-05 13:05:05,429 [main] INFO org.apache.pig.tools.pigstats.mapreduce.SimplePigStats –
Script Statistics:

HadoopVersion PigVersion UserId StartedAt FinishedAt Features
2.6.0 0.15.0 Hadoop 2015-10-0 13:03:03 2015-10-05 13:05:05 UNKNOWN
Success!
Job Stats (time in seconds):
JobId Maps Reduces MaxMapTime MinMapTime AvgMapTime MedianMapTime
job_14459_06 1 0 n/a n/a n/a n/a
MaxReduceTime MinReduceTime AvgReduceTime MedianReducetime Alias Feature
0 0 0 0 student MAP_ONLY
OutPut folder
hdfs://localhost:9000/pig_Output/

Input(s): Successfully read 0 records from: “hdfs://localhost:9000/pig_data/student_data.txt”
Output(s): Successfully stored 0 records in: “hdfs://localhost:9000/pig_Output”
Counters:
Total records written : 0
Total bytes written : 0
Spillable Memory Manager spill count : 0
Total bags proactively spilled: 0
Total records proactively spilled: 0

Job DAG: job_1443519499159_0006

2015-10-05 13:06:06,192 [main] INFO org.apache.pig.backend.hadoop.executionengine
.mapReduceLayer.MapReduceLau ncher – Success!

Verification

You can verify the stored data as shown below.
Step 1
First of all, list out the files in the directory named pig_output using the ls command as shown below.
hdfs dfs -ls ‘hdfs://localhost:9000/pig_Output/’
Found 2 items
rw-r–r- 1 Hadoop supergroup 0 2015-10-05 13:03 hdfs://localhost:9000/pig_Output/_SUCCESS
rw-r–r- 1 Hadoop supergroup 224 2015-10-05 13:03 hdfs://localhost:9000/pig_Output/part-m-00000
You can observe that two files were created after executing the store statement.
Step 2
Using cat command, list the contents of the file named part-m-00000 as shown below.
$ hdfs dfs -cat ‘hdfs://localhost:9000/pig_Output/part-m-00000’
1,Rajiv,Reddy,9848022337,Hyderabad
2,siddarth,Battacharya,9848022338,Kolkata
3,Rajesh,Khanna,9848022339,Delhi
4,Preethi,Agarwal,9848022330,Pune
5,Trupthi,Mohanthy,9848022336,Bhuwaneshwar
6,Archana,Mishra,9848022335,Chennai

So, this brings us to the end of blog. This Tecklearn ‘How to Store data in Apache Pig using Store Operator’ helps you with commonly asked questions if you are looking out for a job in Apache Pig and Big Data Domain.
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