Open Source For You — December 2017

Admin How To

44 | DECEMBER 2017 | OPEN SOURCE FOR YOU | http://www.OpenSourceForU.com

The importance of Hive in Hadoop

Apache Hive lets you work with Hadoop in a very efficient

manner. It is a complete data warehouse infrastructure that

is built on top of the Hadoop framework. Hive is uniquely

placed to query data, and perform powerful analysis and

data summarisation while working with large volumes of

data. An integral part of Hive is the HiveQL query, which is

an SQL-like interface that is used extensively to query what

is stored in databases.

Hive has the distinct advantage of deploying high-speed data

reads and writes within the data warehouses while managing

large data sets that are distributed across multiple locations, all

thanks to its SQL-like features. It provides a structure to the

data that is already stored in the database. The users are able to

connect with Hive using a command line tool and a JDBC driver.

How to implement Hive

First, download Hive from http://apache.claz.org/hive/

stable/. Next, download apache-hive-1.2.1-bin.tar.

gz 26-Jun-2015 13:34 89M. Extract it manually and

rename the folder as hive.

Figure 1: Hive architecture

HDFS or HBASE Data Storage

Meta Store

Map Reduce

USER INTERFACES WEB UI HIVE COMMAND LINE HD Insight

Hive QL Process Engine

Execution Engine

Figure 2: Hive configuration

Table 1

Unit name Operation

User interface Hive is data warehouse infrastructure

software that can create interactions

between the user and HDFS. The user

interfaces that Hive supports are Hive

Web UI, the Hive command line, and

Hive HD Insight (in Windows Server).

Meta store Hive chooses respective database

servers to store the schema or

metadata of tables, databases and

columns in a table, along with their

data types, and HDFS mapping.

HiveQL pro-

cess engine

HiveQL is similar to SQL for querying

on schema information on the meta

store. It replaces the traditional ap-

proach of the MapReduce program.

Instead of writing the MapReduce

program in Java, we can write a

query for a MapReduce job and

process it.

Execution

engine

The conjunction part of the HiveQL

Process engine and MapReduce is

the Hive Execution engine, which

processes the query and generates

results that are the same as MapRe-

duce results.

HDFS or

HBASE

Hadoop distributed file system or

HBASE comprises the data storage

techniques for storing data into the file

system.

Figure 3: Getting started with Hive