Apache PigWhat is Pig?
Pig is a dataflow programming environment for processing very large files. Pig's language is called Pig Latin. A Pig Latin program consists of a directed acyclic graph where each node represents an operation that transforms data. Operations are of two flavors: (1) relational-algebra style operations such as join, filter, project; (2) functional-programming style operators such as map, reduce.
Pig is a tool in the Databases category of a tech stack.
Pig Pros & Cons
Pros of Pig
- ✓Finer-grained control on parallelization
- ✓Join optimizations for highly skewed data
- ✓Open-source
- ✓Proven at Petabyte scale
Cons of Pig
No cons listed yet.
Pig Alternatives & Comparisons
What are some alternatives to Pig?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
