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Apache ORC (Optimized Row Columnar) is a free and open-source column-oriented data storage format. [3] It is similar to the other columnar-storage file formats available in the Hadoop ecosystem such as RCFile and Parquet. It is used by most of the data processing frameworks Apache Spark, Apache Hive, Apache Flink, and Apache Hadoop.
RCFile became the de facto standard data storage structure in Hadoop software environment supported by the Apache HCatalog project (formerly known as Howl [10]) that is the table and storage management service for Hadoop. [11] RCFile is supported by the open source Elephant Bird library used in Twitter for daily data analytics. [12]
Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.
Apache Parquet and Apache ORC are popular examples of on-disk columnar data formats. Arrow is designed as a complement to these formats for processing data in-memory. [11] The hardware resource engineering trade-offs for in-memory processing vary from those associated with on-disk storage. [12]
Across Unix-like operating systems many different configuration-file formats exist, with each application or service potentially having a unique format, but there is a strong tradition of them being in human-editable plain text, and a simple key–value pair format is common.
The first four file formats supported in Hive were plain text, [13] sequence file, optimized row columnar (ORC) format [14] [15] and RCFile. [ 16 ] [ 17 ] Apache Parquet can be read via plugin in versions later than 0.10 and natively starting at 0.13.
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Examples of column-oriented formats include Apache ORC, [3] Apache Parquet, [4] Apache Arrow, [5] formats used by BigQuery, Amazon Redshift and Snowflake. Predominant examples of row-oriented formats include CSV, formats used in most relational databases , the in-memory format of Apache Spark , and Apache Avro .