[{"createTime":1735734952000,"id":1,"img":"hwy_ms_500_252.jpeg","link":"https://activity.huaweicloud.com/cps.html?fromacct=261f35b6-af54-4511-a2ca-910fa15905d1&utm_source=V1g3MDY4NTY=&utm_medium=cps&utm_campaign=201905","name":"华为云秒杀","status":9,"txt":"华为云38元秒杀","type":1,"updateTime":1735747411000,"userId":3},{"createTime":1736173885000,"id":2,"img":"txy_480_300.png","link":"https://cloud.tencent.com/act/cps/redirect?redirect=1077&cps_key=edb15096bfff75effaaa8c8bb66138bd&from=console","name":"腾讯云秒杀","status":9,"txt":"腾讯云限量秒杀","type":1,"updateTime":1736173885000,"userId":3},{"createTime":1736177492000,"id":3,"img":"aly_251_140.png","link":"https://www.aliyun.com/minisite/goods?userCode=pwp8kmv3","memo":"","name":"阿里云","status":9,"txt":"阿里云2折起","type":1,"updateTime":1736177492000,"userId":3},{"createTime":1735660800000,"id":4,"img":"vultr_560_300.png","link":"https://www.vultr.com/?ref=9603742-8H","name":"Vultr","status":9,"txt":"Vultr送$100","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":5,"img":"jdy_663_320.jpg","link":"https://3.cn/2ay1-e5t","name":"京东云","status":9,"txt":"京东云特惠专区","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":6,"img":"new_ads.png","link":"https://www.iodraw.com/ads","name":"发布广告","status":9,"txt":"发布广告","type":1,"updateTime":1735660800000,"userId":3},{"createTime":1735660800000,"id":7,"img":"yun_910_50.png","link":"https://activity.huaweicloud.com/discount_area_v5/index.html?fromacct=261f35b6-af54-4511-a2ca-910fa15905d1&utm_source=aXhpYW95YW5nOA===&utm_medium=cps&utm_campaign=201905","name":"底部","status":9,"txt":"高性能云服务器2折起","type":2,"updateTime":1735660800000,"userId":3}]
1. 架构的介绍
mpp架构是将许多数据库通过网络连接起来,相当于将一个个垂直系统横向连接,形成一个统一对外的服务的分布式数据库系统。每个节点
由一个单机数据库系统独立管理和操作该物理机上的的所有资源(CPU,内存等),节点内系统的各组件间相互调用无需通过主节点。
Hadoop架构是将不同的资源管理与功能进行分层抽象设计,每层形成一类组件,实现一定的解耦,包括存储资源管理等,在每层内进行跨节点
的资源统一管理或功能并行执行,层与层之间通过接口调用,相互透明,节点内不同层的组件间的相互调用需要由“控制节点”掌握或通过“控制节点”协调,即控制节点了解每个节点不同层组件间的互动过程。
2 各自的优势
2.1 水平扩展性
Hadoop架构的水平扩展性更高。Hadoop架构能够扩展到10K台机器,Mpp架构最高只能扩展到几百台。
2.2 容错
Hadoop的容错性更高,其存储与计算都是分离开来,同时存在副本。而在MPP架构下,某个节点异常之后,整个计算过程就被阻塞住。
2.3 事务支持
MPP架构对事物支持得更好,MPP架构下各个节点是单机数据库,能够很好的支持事务,只需master节点增加全局事务的逻辑,即可做到很好的事务支持。Hadoop架构下的事务支持能力很弱。
2.4 数据结构
Hadoop架构可适用于非结构化,半结构化,结构化数据(Hbase),MPP架构只适用于结构化数据。
总的来说,Hadoop架构在数据量比较低的情况下,运行速度远不及MPP架构,但数据量一旦超过某个量级,Hadoop架构的在吞吐量方面更有优势。有些大数据数据仓库产品也采用混合的架构,以融合两者的优点。
例如Impala,Presto都是基于HDFS的MPP分析引擎,仅利用HDFS实现分区的容错性,放弃MapReduce计算模型,在面向OLAP场景时可实现更好的性能,降低延迟
。