Parquet is a type of file format commonly used for storing large, structured datasets. It is based on the columnar storage layout and is characterized by its compression and efficient storage capabilities. The open-source parquet format is most commonly used for processing data in the Hadoop distributed computing system.
The parquet format is a highly efficient binary file format commonly used for data warehouse, data mart, and data lake applications. It is optimized for analytical workloads and provides a way of storing columnar data set that is easy to query and analyze. It is an open-source format developed and maintained by the Apache Software Foundation. Parquet files are compressed and are optimized for columnar data sets.
Since parquet is an open source format, it can be used by many popular frameworks and tools such as Apache Spark, Apache Drill, Apache Hive, Apache Impala, Presto, Flink, Kudu, and MapReduce. Parquet files are also supported by many analytics software, such as Tableau, Qlik, and Power BI.
Parquet provides high-efficiency storage capabilities, reduces file size, and can store data with different types for each column. It allows for easy analysis of large datasets and is optimized for reading, so querying is faster than other storage formats such as CSV and JSON.
The parquet format provides improved query and analysis performance, greater scalability and efficient storage. It is an efficient way to store large, complex data sets and is widely used in data warehouses and big data applications.
