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The term Hadoop is often used for both base modules and sub-modules and also the ecosystem, [12] or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Apache Impala, Apache Flume, Apache Sqoop, Apache Oozie ...
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.
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.
Apache Kudu is a free and open source column-oriented data store of the Apache Hadoop ecosystem. It is compatible with most of the data processing frameworks in the Hadoop environment. It provides completeness to Hadoop's storage layer to enable fast analytics on fast data.
The open-source project to build Apache Parquet began as a joint effort between Twitter [3] and Cloudera. [4] Parquet was designed as an improvement on the Trevni columnar storage format created by Doug Cutting, the creator of Hadoop. The first version, Apache Parquet 1.0, was released in July 2013. Since April 27, 2015, Apache Parquet has been ...
Its primary use is in Apache Hadoop, where it can provide both a serialization format for persistent data, and a wire format for communication between Hadoop nodes, and from client programs to the Hadoop services. Avro uses a schema to structure the data that is being encoded.
HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java.It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System) or Alluxio, providing Bigtable-like capabilities for Hadoop.
Sahara is a component to easily and rapidly provision Hadoop clusters. Users will specify several parameters like the Hadoop version number, the cluster topology type, node flavor details (defining disk space, CPU and RAM settings), and others. After a user provides all of the parameters, Sahara deploys the cluster in a few minutes.