What are the uses of Apache Pig
What are the uses of Apache Pig
Apache Pig is a high-level platform for creating programs which run on Apache Hadoop. The language for this platform is called Pig Latin. Pig can execute its Hadoop jobs in MapReduce, Apache Tez, or Apache Spark. Pig Latin is the language used for this platform, and it can be extended using user-defined functions (UDFs) that the users can write in Java, Python, JavaScript, Ruby, or Groovy.
Pig enables the data workers to write the complex data transformations without knowing Java. Pig’s simple SQL-like scripting language is called Pig Latin, and it appeals to developers already familiar with scripting languages and SQL.
Apache Pig platform is utilized to analyze the large datasets which consists of high level language for expressing data analysis programs along with the infrastructure for assessing these programs. The Pig programs are highly parallelized due to the virtue of which they can handle large data sets.
Initially Pig was developed by Yahoo! for its data scientists for those who were using Hadoop. It was incepted to focus on analysis of large datasets, than on writing mapper and reduce functions. This made the users to focus on what they want to do rather than bothering with how its done.
Pig language has the facility to write commands in other languages like Java, Python etc. The Big applications which can be built on Pig Latin can be custom built for the different companies to serve the different tasks related to the data management. Pig systemizes all the data and relates it in a manner that when required, filtering and searching data is checked efficiently and quickly.
Apache Pig can process any kind of data, such as structured, semi-structured or unstructured data, coming from various sources. It handles all kinds of data. 10 lines of pig code is approximately equal to 200 lines of MapReduce code and it can handle inconsistent schema in case of the unstructured data.
Pig extracts the data, performs operations on it and dumps the data in the required format in HDFS i.e. ETL. It automatically optimizes the tasks before execution, i.e. automatic optimization and allows the programmers and developers to concentrate upon the whole operation irrespective of creating mapper and reducer functions separately.
Apache Pig is used for analyzing and performing tasks like ad-hoc processing. It is used, Where there is a need to process huge data sets like Web logs, streaming online data, etc.
Pig is used the need of Data processing for search platforms such as Yahoo uses Pig for 40% of their jobs including news feeds and search engine.
Pig can be used Where we need to process time sensitive data loads and the data needs to be extracted and analyzed quickly. E.g. machine learning algorithms require time sensitive data loads, and the twitter needs to quickly extract data of customer activities and analyze the data to find patterns in customer behaviors, and make recommendations immediately like trending tweets.
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