HBase architecture consists mainly of four components
HMaster
HRegionserver
HRegions
Zookeeper
HDFS
In this tutorial- you will learn,
HBase Architecture and its Important Components HMaster H Region Server HRegions ZooKeeper HDFS HBase Data Model HBase Use Cases Storage Mechanism in HBase HBase Read and Write Data Explained HBASE vs. HDFS
The following are important roles performed by HMaster in HBase.
Plays a vital role in terms of performance and maintaining nodes in the cluster.
HMaster provides admin performance and distributes services to different region servers.
HMaster assigns regions to region servers.
HMaster has the features like controlling load balancing and failover to handle the load over nodes present in the cluster.
When a client wants to change any schema and to change any Metadata operations, HMaster takes responsibility for these operations.
Some of the methods exposed by HMaster Interface are primarily Metadata oriented methods.
Table (createTable, removeTable, enable, disable)
ColumnFamily (add Column, modify Column)
Region (move, assign)
The client communicates in a bi-directional way with both HMaster and ZooKeeper. For read and write operations, it directly contacts with HRegion servers. HMaster assigns regions to region servers and in turn, check the health status of region servers. In entire architecture, we have multiple region servers. Hlog present in region servers which are going to store all the log files.
HBase Region Servers
When HBase Region Server receives writes and read requests from the client, it assigns the request to a specific region, where the actual column family resides. However, the client can directly contact with HRegion servers, there is no need of HMaster mandatory permission to the client regarding communication with HRegion servers. The client requires HMaster help when operations related to metadata and schema changes are required. HRegionServer is the Region Server implementation. It is responsible for serving and managing regions or data that is present in a distributed cluster. The region servers run on Data Nodes present in the Hadoop cluster. HMaster can get into contact with multiple HRegion servers and performs the following functions.
Hosting and managing regions
Splitting regions automatically
Handling read and writes requests
Communicating with the client directly
HBase Regions
HRegions are the basic building elements of HBase cluster that consists of the distribution of tables and are comprised of Column families. It contains multiple stores, one for each column family. It consists of mainly two components, which are Memstore and Hfile.
ZooKeeper
HBase Zookeeper is a centralized monitoring server which maintains configuration information and provides distributed synchronization. Distributed synchronization is to access the distributed applications running across the cluster with the responsibility of providing coordination services between nodes. If the client wants to communicate with regions, the server’s client has to approach ZooKeeper first. It is an open source project, and it provides so many important services. Services provided by ZooKeeper
Maintains Configuration information
Provides distributed synchronization
Client Communication establishment with region servers
Provides ephemeral nodes for which represent different region servers
Master servers usability of ephemeral nodes for discovering available servers in the cluster
To track server failure and network partitions
Master and HBase slave nodes ( region servers) registered themselves with ZooKeeper. The client needs access to ZK(zookeeper) quorum configuration to connect with master and region servers. During a failure of nodes that present in HBase cluster, ZKquoram will trigger error messages, and it starts to repair the failed nodes.
HDFS
HDFS is a Hadoop distributed File System, as the name implies it provides a distributed environment for the storage and it is a file system designed in a way to run on commodity hardware. It stores each file in multiple blocks and to maintain fault tolerance, the blocks are replicated across a Hadoop cluster. HDFS provides a high degree of fault –tolerance and runs on cheap commodity hardware. By adding nodes to the cluster and performing processing & storing by using the cheap commodity hardware, it will give the client better results as compared to the existing one. In here, the data stored in each block replicates into 3 nodes any in a case when any node goes down there will be no loss of data, it will have a proper backup recovery mechanism. HDFS get in contact with the HBase components and stores a large amount of data in a distributed manner. HBase Data Model consists of following elements,
Set of tables
Each table with column families and rows
Each table must have an element defined as Primary Key.
Row key acts as a Primary key in HBase.
Any access to HBase tables uses this Primary Key
Each column present in HBase denotes attribute corresponding to object
Whenever there is a need to write heavy applications. Performing online log analytics and to generate compliance reports.
Storage Mechanism in HBase
HBase is a column-oriented database and data is stored in tables. The tables are sorted by RowId. As shown below, HBase has RowId, which is the collection of several column families that are present in the table. The column families that are present in the schema are key-value pairs. If we observe in detail each column family having multiple numbers of columns. The column values stored into disk memory. Each cell of the table has its own Metadata like timestamp and other information.
Coming to HBase the following are the key terms representing table schema
Table: Collection of rows present.
Row: Collection of column families.
Column Family: Collection of columns.
Column: Collection of key-value pairs.
Namespace: Logical grouping of tables.
Cell: A {row, column, version} tuple exactly specifies a cell definition in HBase.
Column-oriented vs Row-oriented storages
Column and Row-oriented storages differ in their storage mechanism. As we all know traditional relational models store data in terms of row-based format like in terms of rows of data. Column-oriented storages store data tables in terms of columns and column families. The following Table gives some key differences between these two storages
Step 1) Client wants to write data and in turn first communicates with Regions server and then regions Step 2) Regions contacting memstore for storing associated with the column family Step 3) First data stores into Memstore, where the data is sorted and after that, it flushes into HFile. The main reason for using Memstore is to store data in a Distributed file system based on Row Key. Memstore will be placed in Region server main memory while HFiles are written into HDFS. Step 4) Client wants to read data from Regions Step 5) In turn Client can have direct access to Mem store, and it can request for data. Step 6) Client approaches HFiles to get the data. The data are fetched and retrieved by the Client. Memstore holds in-memory modifications to the store. The hierarchy of objects in HBase Regions is as shown from top to bottom in below table. Some typical IT industrial applications use HBase operations along with Hadoop. Applications include stock exchange data, online banking data operations, and processing Hbase is best-suited solution method.
Summary
HBase architecture components: HMaster, HRegion Server, HRegions, ZooKeeper, HDFS HMaster in HBase is the implementation of a Master server in HBase architecture. When HBase Region Server receives writes and read requests from the client, it assigns the request to a specific region, where the actual column family resides HRegions are the basic building elements of HBase cluster that consists of the distribution of tables and are comprised of Column families. HBase Zookeeper is a centralized monitoring server which maintains configuration information and provides distributed synchronization. HDFS provides a high degree of fault–tolerance and runs on cheap commodity hardware. HBase Data Model is a set of components that consists of Tables, Rows, Column families, Cells, Columns, and Versions. Column and Row-oriented storages differ in their storage mechanism.
