You can run Apache Pig in two modes, namely, Local Mode and HDFS mode.
Local Mode
In this mode, all the files are installed and run from your local host and local file system. There is no need of Hadoop or HDFS. This mode is generally used for testing purpose.
MapReduce Mode
MapReduce mode is where we load or process the data that exists in the Hadoop File System (HDFS) using Apache Pig. In this mode, whenever we execute the Pig Latin statements to process the data, a MapReduce job is invoked in the back-end to perform a particular operation on the data that exists in the HDFS.

Apache Pig Execution Mechanisms

Apache Pig scripts can be executed in three ways, namely, interactive mode, batch mode, and embedded mode.
• Interactive Mode (Grunt shell) − You can run Apache Pig in interactive mode using the Grunt shell. In this shell, you can enter the Pig Latin statements and get the output (using Dump operator).
• Batch Mode (Script) − You can run Apache Pig in Batch mode by writing the Pig Latin script in a single file with .pig extension.
• Embedded Mode (UDF) − Apache Pig provides the provision of defining our own functions (User Defined Functions) in programming languages such as Java, and using them in our script.

Invoking the Grunt Shell

You can invoke the Grunt shell in a desired mode (local/MapReduce) using the −x option as shown below.

Local mode

MapReduce mode

Command −

$ ./pig –x local

Command −

$ ./pig -x mapreduce

Output −

Either of these commands gives you the Grunt shell prompt as shown below.
grunt>
You can exit the Grunt shell using ‘ctrl + d’.
After invoking the Grunt shell, you can execute a Pig script by directly entering the Pig Latin statements in it.
grunt> customers = LOAD ‘customers.txt’ USING PigStorage(‘,’);

Executing Apache Pig in Batch Mode

You can write an entire Pig Latin script in a file and execute it using the –x command. Let us suppose we have a Pig script in a file named sample_script.pig as shown below.
Sample_script.pig
student = LOAD ‘hdfs://localhost:9000/pig_data/student.txt’ USING
PigStorage(‘,’) as (id:int,name:chararray,city:chararray);

Dump student;
Now, you can execute the script in the above file as shown below.

Local mode	MapReduce mode
$ pig -x local Sample_script.pig	$ pig -x mapreduce Sample_script.pig

So, this brings us to the end of blog. This Tecklearn ‘How to Execute Apache Pig’ 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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Hadoop Fundamentals
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• Data Storage: HDFS
• Distributed Data Processing: YARN, MapReduce, and Spark
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• Data Integration: Sqoop
• Other Hadoop Data Tools
• Exercise Scenarios Explanation
Introduction to Pig
• What Is Pig?
• Pig’s Features
• Pig Use Cases
• Interacting with Pig
Basic Data Analysis with Pig
• Pig Latin Syntax
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• Logging
• Using Hadoop’s Web UI
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• Performance Overview
• Understanding the Execution Plan
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Introduction to Hive and Impala
• What Is Hive?
• What Is Impala?
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• Comparing Hive to Traditional Databases
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Querying with Hive and Impala
• Databases and Tables
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• Differences Between Hive and Impala Query Syntax
• Using Hue to Execute Queries
• Using the Impala Shell
Data Management
• Data Storage
• Creating Databases and Tables
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• Altering Databases and Tables
• Simplifying Queries with Views
• Storing Query Results
Data Storage and Performance
• Partitioning Tables
• Choosing a File Format
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Relational Data Analysis with Hive and Impala
• Joining Datasets
• Common Built-In Functions
• Aggregation and Windowing
Working with Impala
• How Impala Executes Queries
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Analyzing Text and Complex Data with Hive
• Complex Values in Hive
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