What Is Hive

Hive is a data warehousing infrastructure based on Hadoop. Hadoop provides massive scale out and fault tolerance capabilities for data storage and processing (using the map-reduce programming paradigm) on commodity hardware.

Hive is designed to enable easy data summarization, ad-hoc querying and analysis of large volumes of data. It provides a simple query language called Hive QL, which is based on SQL and which enables users familiar with SQL to do ad-hoc querying, summarization and data analysis easily. At the same time, Hive QL also allows traditional map/reduce programmers to be able to plug in their custom mappers and reducers to do more sophisticated analysis that may not be supported by the built-in capabilities of the language.

What Hive Is NOT

Hadoop is a batch processing system and Hadoop jobs tend to have high latency and incur substantial overheads in job submission and scheduling. As a result - latency for Hive queries is generally very high (minutes) even when data sets involved are very small (say a few hundred megabytes). As a result it cannot be compared with systems such as Oracle where analyses are conducted on a significantly smaller amount of data but the analyses proceed much more iteratively with the response times between iterations being less than a few minutes. Hive aims to provide acceptable (but not optimal) latency for interactive data browsing, queries over small data sets or test queries.

Hive is not designed for online transaction processing and does not offer real-time queries and row level updates. It is best used for batch jobs over large sets of immutable data (like web logs). 不支持在线事务处理,不支持实时查询,不支持行数据更新。最好的用途是:批量处理大数据集的不可改变的数据,比如网络日志。

In the following sections we provide a tutorial on the capabilities of the system. We start by describing the concepts of data types, tables and partitions (which are very similar to what you would find in a traditional relational DBMS) and then illustrate the capabilities of the QL language with the help of some examples.

[Hive-Tutorial] What Is Hive的更多相关文章

  1. Hive Tutorial(上)(Hive 入门指导)

    用户指导 Hive 指导 Hive指导 概念 Hive是什么 Hive不是什么 获得和开始 数据单元 类型系统 内置操作符和方法 语言性能 用法和例子(在<下>里面) 概念 Hive是什么 ...

  2. [Hive - Tutorial] Type System 数据类型

    数据类型Type System Hive supports primitive and complex data types, as described below. See Hive Data Ty ...

  3. Hive Tutorial 阅读记录

    Hive Tutorial 目录 Hive Tutorial 1.Concepts 1.1.What Is Hive 1.2.What Hive Is NOT 1.3.Getting Started ...

  4. Spark入门实战系列--5.Hive(上)--Hive介绍及部署

    [注]该系列文章以及使用到安装包/测试数据 可以在<倾情大奉送--Spark入门实战系列>获取 .Hive介绍 1.1 Hive介绍 月开源的一个数据仓库框架,提供了类似于SQL语法的HQ ...

  5. hive学习3(hive基本操作)

    hive基本操作 hive的数据类型 1)基本数据类型 TINYINT,SMALLINT,INT,BIGINT FLOAT/DOUBLE BOOLEAN STRING 2)复合类型 ARRAY:一组有 ...

  6. [Hive - LanguageManual] Statistics in Hive

    Statistics in Hive Statistics in Hive Motivation Scope Table and Partition Statistics Column Statist ...

  7. Hive over HBase和Hive over HDFS性能比较分析

    http://superlxw1234.iteye.com/blog/2008274 环境配置: hadoop-2.0.0-cdh4.3.0 (4 nodes, 24G mem/node) hbase ...

  8. Hive学习之一 《Hive的介绍和安装》

    一.什么是Hive Hive是建立在 Hadoop 上的数据仓库基础构架.它提供了一系列的工具,可以用来进行数据提取转化加载(ETL),这是一种可以存储.查询和分析存储在 Hadoop 中的大规模数据 ...

  9. Hive综合HBase——经Hive阅读/书写 HBase桌子

    社论: 本文将Hive与HBase整合在一起,使Hive能够读取HBase中的数据,让Hadoop生态系统中最为经常使用的两大框架互相结合.相得益彰. watermark/2/text/aHR0cDo ...

  10. hive优化之——控制hive任务中的map数和reduce数

    一.    控制hive任务中的map数: 1.    通常情况下,作业会通过input的目录产生一个或者多个map任务.主要的决定因素有: input的文件总个数,input的文件大小,集群设置的文 ...

随机推荐

  1. Quartz的任务的临时启动和暂停和恢复

    Quartz的任务的临时启动和暂停和恢复 在项目中需要手动启停某些服务,那么需要有一个控制这些任务的类.由于任务是有Quartz控制的,我们只需要通过Quartz的相关的API实现相关的功能即可. p ...

  2. jquery学习以及下载链接

    jquery学习链接 http://www.w3school.com.cn/jquery/jquery_intro.asp jquery 脚本库下载链接 http://jquery.com/downl ...

  3. Android开发之权限列表

    权限定义 功能 android.permission.ACCESS_CHECKIN_PROPERTIES 允许读写访问"properties"表在checkin数据库中,改值可以修 ...

  4. TCP/IP 与OSI结构图

    OSI参考模型各层的作用 物理层:在物理媒体上传输原始的数据比特流. 数据链路层:将数据分成一个个数据帧,以数据帧为单位传输.有应有答,遇错重发. 网络层:将数据分成一定长度的分组,将分组穿过通信子网 ...

  5. ruby安装插件报错

    有时候我们需要安装ruby插件的时候,会报如下错误:  ERROR: Could not find a valid gem 'rdiscount' (>= 0), here is why: Un ...

  6. 【Todo】抽象渗漏法则 & 找到理想员工 & 软件开发成功 12 法则 & Joel on Software

    Joel应该是个软件专家,这是他文章汇总的中文版本: http://local.joelonsoftware.com/wiki/Chinese_%28Simplified%29 其中有几篇值得好好看看 ...

  7. ACM - ICPC World Finals 2013 D Factors

    原题下载:http://icpc.baylor.edu/download/worldfinals/problems/icpc2013.pdf 题目翻译: 问题描述 一个最基本的算数法则就是大于1的整数 ...

  8. MVVM设计模式《网摘》

    MVVM模式能够帮你把你程序的业务与展现逻辑从用户界面干净地分离开.保持程序逻辑与界面分离能够帮助解决很多开发以及设计问题,能够使你的程序能更容易的测试,维护与升级.它也能很大程度的增加代码重用性,并 ...

  9. SQL全文搜索

    ( select dd.*,t.RANK from crm_CustomerAnalyzeDetails dd ) as t on dd.ID = t.[key] ) union all ( sele ...

  10. bzoj3272 3638

    好题,这道题可以用线段树来快速模拟费用流寻找最长增广路 这样修改怎么做也很显然了 type node=record s,lx,rx,mx,lp,rp,pb,pe:longint; end; ..*,. ...