Parquet

Parquet is a columnar storage format for computer data. It is an open source file format used for the storage of large datasets. It was originally created by engineers at Twitter and is now hosted as an Apache Software Foundation project.

Parquet is popular in the field of big data and is used by various tools for data exchange. It is especially beneficial when data is being transferred between two different flexible databases, such as Hive and Impala. Parquet also supports features such as compression, splitting, block-level encryption, and data discovery.

Parquet is an efficient file format for large-scale data analysis. It enables applications to use multiple cores concurrently and provides efficient storage and processing of homogeneous data. Additionally, many open-source tools, such as Apache Spark, Hadoop, Impala and Kudu, support the use of Parquet for data analysis.

Parquet also enables data scientists to perform analytics on data stored in distributed systems. This is made possible through its support for functional programming models, such as map-reduce and reduce-only. This makes it an ideal file format for large-scale data analysis.

Parquet is also becoming popular in the machine learning and artificial intelligence fields. It allows algorithms to use multiple cores efficiently, making large-scale machine learning inferences faster.

In conclusion, Parquet is a powerful and versatile file format that is becoming increasingly popular in many areas of computing. It is an open-source file format that enables efficient storage and processing of large datasets, as well as enabling efficient distributed data analysis. It is the file format of choice for many big data and machine learning applications.