Pig Tutoriallearning manual
Published on 2023-04-20 00:10:05 · 中文 · بالعربية · Español · हिंदीName · 日本語 · Русский язык · 中文繁體
Apache Pig Tutorial
The Pig tutorial provides basic and advanced concepts of Pig. Our Pig tutorial is designed for beginners and professionals.
Pig is an advanced data flow platform used to execute Hadoop's Map Reduce program. It was developed by Yahoo. The language of Pig is Pig Latin.
Our Pig tutorial includes Apache Pig and its usage, Pig installation, Pig runtime mode, Pig Latin concept, Pig data types, Pig examples, all topics related to Pig user-defined functions, etc
What is Apache Pig
Apache Pig is an advanced data flow platform used to execute Hadoop's MapReduce program. The language used by Pig is Pig Latin.
The Pig script is internally converted into a Map Reduce job and executed on the data stored in HDFS. In addition, Pig can also perform its work in Apache Tez or Apache Spark.
Pig can process any type of data, namely structured, semi structured, or unstructured, and store the corresponding results in Hadoop data files in the system. Each task that can be achieved using PIG can also be implemented using the Java used in MapReduce.
Features of Apache Pig
Let's take a look at the various uses of Pig technology.
1) Easy to program
Writing complex Java programs for map reduce is quite difficult for non programmers. Pig makes this process simple. In Pig, the query is internally converted to MapReduce.
2) Optimization opportunities
The encoding of tasks allows the system to automatically optimize their execution, allowing users to focus on semantics rather than efficiency.
3) Scalability
User defined functions have been written in which users can write logic to execute
4) Flexible
It can easily handle structured and unstructured data.
5) Built-in operators
It contains various types of operators, such as sorting, filtering, and concatenation.
The difference between Apache MapReduce and PIG
| Apache MapReduce | Apache PIG |
| It is a low-level data processing tool | It is an advanced data flow tool |
| Here, complex programs need to be developed using Java or Python | No need to develop complex programs |
| It is difficult to perform data operations in MapReduce | It provides built-in operators to perform data operations such as union, sorting, and sorting |
| It does not allow nested data types | It provides nested data types such as tuples, packages, and maps |