Help Center/ MapReduce Service/ User Guide (Ankara Region)/ Overview/ Components/ Hive/ Relationship Between Hive and Other Components
Updated on 2024-11-29 GMT+08:00
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Relationship Between Hive and Other Components

Relationship Between Hive and HDFS

Hive is a sub-project of Apache Hadoop, which uses HDFS as the file storage system. It parses and processes structured data with highly reliable underlying storage supported by HDFS. All data files in the Hive database are stored in HDFS, and all data operations on Hive are also performed using HDFS APIs.

Relationship Between Hive and MapReduce

Hive data computing depends on MapReduce. MapReduce is also a sub-project of Apache Hadoop and is a parallel computing framework based on HDFS. During data analysis, Hive parses HQL statements submitted by users into MapReduce tasks and submits the tasks for MapReduce to execute.

Relationship Between Hive and Tez

Tez, an open-source project of Apache, is a distributed computing framework that supports directed acyclic graphs (DAGs). When Hive uses the Tez engine to analyze data, it parses HQL statements submitted by users into Tez tasks and submits the tasks to Tez for execution.

Relationship Between Hive and DBService

MetaStore (metadata service) of Hive processes the structure and attribute information of Hive metadata, such as Hive databases, tables, and partitions. The information needs to be stored in a relational database and is managed and processed by MetaStore. In the product, the metadata of Hive is stored and maintained by the DBService component, and the metadata service is provided by the Metadata component.

Relationship Between Hive and Elasticsearch

Hive uses Elasticsearch as its extended file storage system. Hive integrates the Elasticsearch-Hadoop plug-in of Elasticsearch, creates a foreign table, and stores table data in Elasticsearch so that Hive can read and write Elasticsearch index data.

Parent topic: Hive