Apache Pig

Apache Pig is an open-source platform for processing and analyzing large datasets in distributed environments. It provides Pig Latin, a high-level dataflow language for defining transformations, and an execution layer that converts those programs into parallel processing jobs.

Developers and data engineers use Pig Latin to load data, define schemas, filter records, transform fields, group and aggregate data, join datasets, sort results, split flows, and write output. A Pig program expresses these operations as a sequence of named data relations, which the platform can analyze and optimize before execution.

Pig was designed to simplify data processing workloads that would otherwise require lower-level MapReduce development. It supports custom user-defined functions for specialized processing and is extensible for organization-specific transformations. Apache Pig 0.18.0 supports Hadoop 2 and 3, Tez, Hive 3, Spark 3, HBase 2, and Python 3.

Apache Pig is useful for batch-oriented data transformation, preparation, and analysis on Hadoop-compatible infrastructure. It is not a visual ETL platform, data warehouse, or workflow orchestration tool; users define dataflows in Pig Latin and run them through supported distributed execution engines. Apache Pig is distributed under the Apache License 2.0.