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Xiaobian to share with you how hbase is to store the underlying data, I believe most people do not know how, so share this article for your reference, I hope you have a lot of harvest after reading this article, let's go to understand it together!

hbase relies on "HDFS" to store the underlying data. HBase utilizes Hadoop HDFS as its file storage system to provide high-reliability underlying storage support for HBase;HDFS is highly fault-tolerant and designed to be deployed on low-cost hardware.

HBase - Hadoop Database, is a high-reliability, high-performance, column-oriented, scalable distributed storage system, using HBase technology to build large-scale structured storage clusters on low-cost PC servers.

hbase relies on "HDFS" to store the underlying data.

HBase is an open source implementation of Google Bigtable, similar to Google Bigtable using GFS as its file storage system, HBase uses Hadoop HDFS as its file storage system;Google runs MapReduce to process massive data in Bigtable, HBase also uses Hadoop MapReduce to process massive data in HBase;Google Bigtable uses Chubby as a collaborative service, and HBase uses Zookeeper as its counterpart.

The diagram above depicts the layers in the Hadoop EcoSystem. HBase is located in the structured storage layer, Hadoop HDFS provides high-reliability underlying storage support for HBase, Hadoop MapReduce provides high-performance computing power for HBase, and Zookeeper provides stable services and failover mechanisms for HBase.

HDFS

Hadoop Distributed File System (HDFS) is a Distributed File System designed to run on commodity hardware. It has a lot in common with existing distributed file systems. But at the same time, it is also very different from other distributed file systems. HDFS is a highly fault-tolerant system suitable for deployment on inexpensive machines. HDFS provides high-throughput data access and is ideal for applications on large-scale datasets. HDFS relaxes some POSIX constraints to achieve the purpose of streaming file system data. HDFS was originally developed as an infrastructure for the Apache Nutch search engine project. HDFS is part of the Apache Hadoop Core project.

HDFS is fault-tolerant and designed to be deployed on low-cost hardware. It also provides high throughput for accessing application data, suitable for applications with large data sets. HDFS relaxes POSIX requirements so that streaming access to data in the file system can be achieved.

HDFS uses a Master/Slave structure model, where an HDFS cluster consists of a NameNode and several DataNodes. NameNode acts as the primary server to manage the namespace of the file system and the access operations of clients to files; DataNode in the cluster manages the stored data.

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