Apache Hive is the data warehouse of Apache Hadoop. Find out everything you need to know about it: definition, use cases, how it works, advantages…
The open-source Hadoop framework is ideal for storing and processing massive amounts of data. For data retrieval, however, this platform is unnecessarily complex, time-consuming and expensive. Fortunately, the Apache Foundation offers another solution to this problem: Apache Hive.
Apache Hive: what is it and what is it for?
Apache Hive is a Data Warehouse software initially created by Facebook. It allows perform SQL-like queries quickly and easily to efficiently extract data from Apache Hadoop. Unlike Hadoop, Hive allows you to perform SQL queries without the need to write in Java.
Today, Apache Hive’s SQL-like interface has become the most popular solution for querying and analyzing Hadoop data. It is a cost-effective solution that can be scaled via the Cloud. As a result many companies such as Netflix and Amazon use and help improve Hive.
Apache Hive: how does it work?
Simply put, Apache Hive translates programs written in HiveQL language (SQL-like) into one or more Java MapReduce, Tez or Spark tasks (three execution engines that can be run on Hadoop YARN). Hive then organizes the data into tables for the Hadoop Distributed File System (HDFS) file and runs the tasks on a cluster to produce a response.
Thes Apache Hive arrays are similar to those of a relational database.and the data units are organized from the broadest to the most granular unit. The databases are made up of tables composed of partitions, which can be further broken down into buckets. The data is accessible via HiveQL. Within each database, the data is numbered and each table corresponds to an HDFS directory.
Within the architecture of Apache Hive, multiple interfaces are available: web interface, CLI, external clients… The Apache Hive Thrift server allows remote clients to submit commands and requests to Apache Hive using a variety of programming languages. The central directory of Apache Hive is a metastore containing all information.
The engine allowing the operation of Hive is the pilot. It consists of a compiler, an optimizer to determine the best execution plan, and an executor.
I mean, come on, security is provided by Hadoop. It therefore relies on Kerberos for mutual authentication between client and server. Permissions for newly created files in Apache Hive are dictated by HDFS, which allows authorization by user, group or other.
Apache Hive: what are the advantages?
Apache Hive is a ideal solution for had-hoc queries and data analysis. It therefore provides insights that give a competitive advantage and facilitate reaction to market demand.
Some of the main advantages of Hive include ease of use related to its “SQL-like” language. In addition, this software speeds up the initial insertion of data since the data does not need to be read and numbered on a disk in the internal database format. This is because Apache Hive reads the schema without checking the array type or schema definition, whereas a traditional database must check the data each time it is inserted.
Knowing that the data is stored in the HDFSit is possible to store hundreds of petabytes of data on Apache Hive. In fact, this solution is much more scalable than a traditional database. Because it is a cloud service,Hive allows users to quickly launch virtual servers as workloads fluctuate.
Security is in place, with the ability to replicate critical workloads for disaster restoration. Finally, the work capacity is unparalleled since it is possible to perform up to 100,000 queries per hour.