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Loading and storing data with Pig
Pig is a high-level scripting language that allows you to process large amounts of data on Hadoop. In this blog post, we will learn how to load and store data with Pig.
Loading data with Pig
To load data with Pig, you need to use the LOAD operator. The LOAD operator takes a file path and an optional schema as arguments. For example:
data = LOAD 'input.txt' AS (name:chararray, age:int);
This statement loads the data from input.txt and assigns it to a relation called data. The schema specifies that each record has two fields: name and age.
You can also load data from other sources, such as HDFS, Hive tables, or databases. For example:
data = LOAD 'hdfs://localhost:9000/user/pig/input.txt' USING PigStorage(',') AS (name:chararray, age:int);
This statement loads the data from HDFS using PigStorage as the loader function. The loader function determines how the data is read and parsed. PigStorage takes a delimiter as an argument and splits each line by that delimiter.
Storing data with Pig
To store data with Pig, you need to use the STORE operator. The STORE operator takes a relation and a file path as arguments. For example:
STORE data INTO 'output.txt';
This statement stores the relation data into output.txt using the default storage function.
You can also store data into other formats or destinations, such as CSV files, JSON files, or Hive tables. For example:
STORE data INTO 'output.csv' USING PigStorage(',');
This statement stores the relation data into output.csv using PigStorage as the storage function.
Conclusion
Pig is a powerful tool for processing large amounts of data on Hadoop. You can use Pig to load and store data from various sources and formats using simple operators and functions.
FAQs
Q: What is the difference between Pig Latin and SQL?
A: Pig Latin is a scripting language that allows you to write complex transformations on Hadoop without writing Java code. SQL is a query language that allows you to perform analytical operations on structured or semi-structured data.
Q: How can I run Pig scripts?
A: You can run Pig scripts in two modes: local mode and mapreduce mode. Local mode runs on your local machine without using Hadoop. Mapreduce mode runs on a Hadoop cluster using MapReduce framework.
Q: What are some common functions in Pig?
A: Some common functions in Pig are:
- FILTER: filters out records that do not satisfy a condition.
- GROUP: groups records by one or more fields.
- JOIN: joins two or more relations by matching values of common fields.
- FOREACH: applies an expression or a nested block to each record.
- ORDER BY: sorts records by one or more fields.
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