druid
实时分析型数据库
Druid | Interactive Analytics at Scale http://druid.io/
Druid is primarily used to store, query, and analyze large event streams. Examples of event streams include user generated data such as clickstreams, application generated data such as performance metrics, and machine generated data such as network flows and server metrics. Druid is optimized for sub-second queries to slice-and-dice, drill down, search, filter, and aggregate this data. Druid is commonly used to power interactive applications where performance, concurrency, and uptime are important.
Druid was initially created to power a scalable, visual, multi-tenant application where users could not only rapidly slice and dice data to create ad-hoc reports, but also interactively explore data to quickly determine the root cause of patterns and anomalies. Druid is designed from the ground up for sub-second queries, which are critical in interactive applications as usability studies have shown that humans get distracted and lose their train of thought if responses take longer than a second.
Design
Druid’s core design combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a unified system for operational analytics. Core design ideas include:
Column-oriented storage
Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys.
Native search indexes
Druid creates inverted indexes for string values for fast search and filter.
Streaming and batch ingest
Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more.
Flexible schemas
Druid gracefully handles evolving schemas and nested data.
Time-optimized partitioning
Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases.
SQL support
In addition to its native JSON based language, Druid speaks SQL over either HTTP or JDBC.
Horizontally scalable
Druid has been used in production to ingest millions of events/sec, retain years of data, and provide sub-second queries.
Easy to operate
Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures.
To learn more, read our Technology page.
Use cases
Druid is proven in production at the world’s leading companies, with the largest installations having more than a thousand servers, ingesting over 10 million events per second, and supporting thousands of concurrent queries per second. Druid is used to:
Analyze performance
Create interactive dashboards with full drill down capabilities. Analyze performance of digital products, track mobile app usage, or monitor site reliability.
Diagnose problems
Find the root cause of issues. Troubleshoot netflow bottlenecks, analyze security threats, or diagnose software crashes.
Find commonalities
Find common attributes among events. Identify shared components in defective products, or determine patterns in top performing products.
Increase efficiency
Improve product engagement. Optimize ad-spend in digital marketing campaigns or increase user engagement in online products.
To learn more, read our Use Cases page.
druid的更多相关文章
- Spring + SpringMVC + Druid + MyBatis 给你一个灵活的后端解决方案
生命不息,折腾不止. 折腾能遇到很多坑,填坑我理解为成长. 两个月前自己倒腾了一套用开源框架构建的 JavaWeb 后端解决方案. Spring + SpringMVC + Druid + JPA(H ...
- Spring + SpringMVC + Druid + JPA(Hibernate impl) 给你一个稳妥的后端解决方案
最近手头的工作不太繁重,自己试着倒腾了一套用开源框架组建的 JavaWeb 后端解决方案. 感觉还不错的样子,但实践和项目实战还是有很大的落差,这里只做抛砖引玉之用. 项目 git 地址:https: ...
- 学记:spring boot使用官网推荐以外的其他数据源druid
虽然spring boot提供了4种数据源的配置,但是如果要使用其他的数据源怎么办?例如,有人就是喜欢druid可以监控的强大功能,有些人项目的需要使用c3p0,那么,我们就没办法了吗?我们就要编程式 ...
- druid连接池获取不到连接的一种情况
数据源一开始配置: jdbc.initialSize=1jdbc.minIdle=1jdbc.maxActive=5 程序运行一段时间后,执行查询抛如下异常: exception=org.mybati ...
- druid配置数据库连接使用密文密码
spring使用druid配置dataSource片段代码 dataSource配置 <!-- 基于Druid数据库链接池的数据源配置 --> <bean id="data ...
- [转]阿里巴巴数据库连接池 druid配置详解
一.背景 java程序很大一部分要操作数据库,为了提高性能操作数据库的时候,又不得不使用数据库连接池.数据库连接池有很多选择,c3p.dhcp.proxool等,druid作为一名后起之秀,凭借其出色 ...
- 技术杂记-改造具有监控功能的数据库连接池阿里Druid,支持simple-jndi,kettle
kettle内置的jndi管理是simple-jndi,功能确实比较简单,我需要监控kettle性能,druid确实是很不错的选择,但没有提供对应的支持,我改进了druid源码,实现了simple-j ...
- sql 连接数不释放 ,Druid异常:wait millis 40000, active 600, maxActive 600
Hibernate + Spring + Druid 数据库mysql 由于配置如下 <bean id="dataSource" class="com.alibab ...
- druid sql黑名单 报异常 sql injection violation, part alway true condition not allow
最近使用druid,发现阿里这个连接池 真的很好用,可以监控到连接池活跃连接数 开辟到多少个连接数 关闭了多少个,对于我在项目中查看错误 问题,很有帮助, 但是最近发现里面 有条sql语句 被拦截了, ...
- 从零开始学 Java - 数据库连接池的选择 Druid
我先说说数据库连接 数据库大家都不陌生,从名字就能看出来它是「存放数据的仓库」,那我们怎么去「仓库」取东西呢?当然需要钥匙啦!这就是我们的数据库用户名.密码了,然后我们就可以打开门去任意的存取东西了. ...
随机推荐
- Kafka 快速起步
Kafka 快速起步 原创 2017-01-05 杜亦舒 性能与架构 性能与架构 性能与架构 微信号 yogoup 功能介绍 网站性能提升与架构设计 主要内容:1. kafka 安装.启动2. 消息的 ...
- Laravel 手动分页实现
Laravel 手动分页实现 基于5.2版本 在开发过程中有这么一种情况,你请求Java api获取信息,由于信息较多,需要分页显示.Laravel官方提供了一个简单的方式paginate($perP ...
- rabbitmq文章源
网易杭研后台技术中心的博客 rabbitmq topic简单demo http://blog.csdn.net/cugb1004101218/article/details/21243927?utm_ ...
- Atitit. 软件开发中的管理哲学--一个伟大的事业必然是过程导向为主 过程导向 vs 结果导向
Atitit. 软件开发中的管理哲学--一个伟大的事业必然是过程导向为主 过程导向 vs 结果导向 1. 一个伟大的事业必然是过程导向为主 1 1.1. 过程的执行情况(有明确的执行手册及标准) ...
- 2.Stacks(堆栈)
一.概述 C++ Stack(堆栈) 是一个容器类的改编,为程序员提供了堆栈的全部功能,也就是说实现了一个先进后出(FILO)的数据结构. 二.常用API empty() 堆栈为空则返回真 pop() ...
- html 基本标签 ---短语
<em> </em> 着重 <strong> </strong> 强调 <dfn> </dfn> 定义 <code> ...
- .net获取客户端IP
using System; using System.Data; using System.Configuration; using System.Web; using System.Web.Secu ...
- TPM--Trusted Platform Module
trouSerS是IBM的一帮牛人搞的TSS软件栈,提供了与TPM交互的API,从而可以让我们方便地编写应用程序. 地址:https://sourceforge.net/projects/trouse ...
- Linux压缩解压缩命令学习笔记
Linux中主要的压缩文件有:*.gz *.tar *.tar.gz *.zip *.bz2 *.tar.bz2 .zip这种古老的压缩格式,在window和Linux中都不需要安装软件可 ...
- C# Dictionary学习
http://www.cnblogs.com/gdjlc/archive/2010/01/22/2086922.html http://wenku.baidu.com/link?url=TOgeedl ...