{"id":25240,"date":"2018-08-14T09:52:31","date_gmt":"2018-08-14T04:22:31","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=25240"},"modified":"2021-08-25T22:32:46","modified_gmt":"2021-08-25T17:02:46","slug":"hadoop-cluster","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/hadoop-cluster\/","title":{"rendered":"What is Hadoop Cluster | Hadoop Cluster Architecture"},"content":{"rendered":"<div class='__iawmlf-post-loop-links' style='display:none;' data-iawmlf-post-links='[{&quot;id&quot;:1824,&quot;href&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=a-DXDkK1i08&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20250817120808\\\/https:\\\/\\\/www.youtube.com\\\/watch?v=a-DXDkK1i08&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2025-12-10 03:27:45&quot;,&quot;http_code&quot;:206},{&quot;date&quot;:&quot;2025-12-13 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10:34:32&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-04 08:46:20&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-07 17:28:54&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-11 08:41:37&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-16 21:13:07&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-22 14:22:39&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-05-30 15:34:15&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-03 11:24:24&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-09 07:25:19&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-12 08:16:13&quot;,&quot;http_code&quot;:200}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-06-12 08:16:13&quot;,&quot;http_code&quot;:200},&quot;process&quot;:&quot;done&quot;}]'><\/div>\n<h2><b>1. Hadoop Cluster<\/b><\/h2>\n<p><span style=\"font-weight: 400\">Today, we will start the Hadoop Cluster Tutorial. In this Tutorial, we will discuss <\/span><a href=\"https:\/\/data-flair.training\/blogs\/hadoop-tutorial-for-beginners\/\"><b>Hadoop<\/b><\/a><span style=\"font-weight: 400\"> Cluster Architecture, diagram. Moreover, we will look at the Hadoop Cluster advantages and Hadoop Nodes configuration.<\/span><br \/>\n<span style=\"font-weight: 400\">In simple terms, Cluster is a set of connected computers which work together as a single system. Similarly, the Hadoop cluster is just a computer cluster which we use for Handling huge volume of data distributedly.<\/span><br \/>\n<span style=\"font-weight: 400\">So, let&#8217;s start the Hadoop Cluster Tutorial.<\/span><\/p>\n<div id=\"attachment_26843\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-26843\" class=\"wp-image-26843 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2.jpg\" alt=\"Hadoop Cluster\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-Tutorial-01-2-1024x536.jpg 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-26843\" class=\"wp-caption-text\">What is Hadoop Cluster | Hadoop Cluster Architecture<\/p><\/div>\n<h2><b>2. Hadoop Cluster Architecture<\/b><\/h2>\n<p><span style=\"font-weight: 400\">Basically, for the purpose of storing as well as analyzing huge amounts of unstructured data in a distributed computing environment, a special type of computational cluster is designed that what we call as Hadoop Clusters.<\/span><br \/>\n<span style=\"font-weight: 400\">Though, whenever we talk about Hadoop Clusters, two main terms come up, they are cluster and node, so on defining them:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">A collection of nodes is\u00a0what we call the cluster.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">A node is a point of intersection\/connection within a network, ie a server<\/span><\/li>\n<\/ul>\n<div id=\"attachment_26839\" style=\"width: 1090px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-26839\" class=\"wp-image-26839 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2.png\" alt=\"Hadoop Cluster Architecture\" width=\"1080\" height=\"1080\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2.png 1080w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2-150x150.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2-300x300.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2-768x768.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2-1024x1024.png 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster2-100x100.png 100w\" sizes=\"auto, (max-width: 1080px) 100vw, 1080px\" \/><\/a><p id=\"caption-attachment-26839\" class=\"wp-caption-text\">Hadoop Cluster Architecture<\/p><\/div>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/install-hadoop-1-x-on-multi-node-cluster\/\"><b>You must read set up for Cluster in Hadoop<\/b><\/a><\/p>\n<p><span style=\"font-weight: 400\">There is nothing shared between the nodes in a Hadoop cluster except for the network which connects them (Hadoop follows shared-nothing architecture). This feature decreases the processing latency so the cluster-wide latency is minimized when there is a need to process queries on huge amounts of data.<\/span><br \/>\n<span style=\"font-weight: 400\">In addition,<\/span> <span style=\"font-weight: 400\">Hadoop clusters have two types of machines, such as Master \u00a0and Slave, where:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Master: HDFS NameNode, YARN ResourceManager.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Slaves: HDFS DataNodes, YARN NodeManagers.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">However, it is recommended to separate the master and slave node, because:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Task\/application workloads on the slave nodes should be isolated from the masters.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Slaves nodes are frequently decommissioned for maintenance.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Moreover, it is possible to scale out a Hadoop cluster. Here, Scaling means to add more nodes. That\u2019s why\u00a0we also call it linearly scalable. Hence, we get a corresponding boost in throughput, for every node we add.<\/span><br \/>\n<a href=\"https:\/\/data-flair.training\/blogs\/hadoop-2-x-vs-hadoop-3-x-comparison\/\"><b>Let&#8217;s have a look at Hadoop 2.x vs Hadoop 3.x<\/b><\/a><\/p>\n<h2><b>3. Datanode and Namenode<\/b><\/h2>\n<div id=\"attachment_26840\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-26840\" class=\"wp-image-26840 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2.png\" alt=\"Hadoop Cluster\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2.png 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2-150x79.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2-300x157.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2-768x402.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/08\/Hadoop-Cluster-2-1024x536.png 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-26840\" class=\"wp-caption-text\">Hadoop Cluster &#8211; Datanode and Namenode<\/p><\/div>\n<p><span style=\"font-weight: 400\">The NameNode is the HDFS master, which manages the file system namespace and regulates access to files by clients and also consults with DataNodes (HDFS slave) while copying data or running MapReduce operations. Whereas DataNode manages storage attached to the nodes that they run on, basically there are a number of DataNodes, that means one DataNode per slave in the cluster. <\/span><br \/>\n<span style=\"font-weight: 400\">In other words, a node which knows where the files are to be found in hdfs are Namenode, and the node which have the data of the files are Datanodes.<\/span><br \/>\n<span style=\"font-weight: 400\">Refer below image to understand its basic image:<\/span><\/p>\n<h2><b>4. Yarn<\/b><\/h2>\n<p><span style=\"font-weight: 400\">Yarn &#8211; Yet Another resource negotiator is the resource management layer of Hadoop. It permits diverse applications like real-time streaming, multiple data processing engines interactive SQL, data science as well as batch processing, to handle data which is stored in hdfs.<\/span><\/p>\n<h3><b>&#8211; What YARN Does<\/b><\/h3>\n<p><span style=\"font-weight: 400\">It is a Hadoop\u2019s prerequisite which offers a central platform that brings security, and data governance tools, as well as resource management over Hadoop clusters.<\/span><br \/>\n<span style=\"font-weight: 400\">Furthermore, it offers a consistent framework for writing data access applications that run in Hadoop, to ISVs as well as developers.<\/span><br \/>\n<span style=\"font-weight: 400\">Also, it enhances a Hadoop compute cluster on the basis of several features, such as Compatibility, Scalability, Cluster Utilization, and Multi-tenancy.<\/span><br \/>\n<a href=\"https:\/\/data-flair.training\/blogs\/hadoop-distributed-cache\/\"><b>Do you know about the Distributed cache in Hadoop<\/b><\/a><\/p>\n<h2><b>5. The Communication Protocols<\/b><\/h2>\n<p><span style=\"font-weight: 400\">For inter-node communication, Hadoop uses tcp ip. Basically, on top of the TCP\/IP protocol, all HDFS communication protocols are layered and on the NameNode machine, a client establishes a connection to a configurable TCP port. Moreover, with the NameNode it talks the ClientProtocol. And, by using the DataNode Protocol, the DataNodes talk to the NameNode. <\/span><br \/>\n<span style=\"font-weight: 400\">In addition, the abstraction Remote Procedure Call (RPC) \u00a0wraps both the DataNode Protocol as well as the Client Protocol. Although, the NameNode never starts any RPCs, by design. Rather than that it only responds to RPC requests which are issued by DataNodes or clients.<\/span><\/p>\n<h2><b>6. Hadoop Nodes Configuration<\/b><\/h2>\n<p><span style=\"font-weight: 400\">However, by two types of important configuration files, Hadoop\u2019s Java configuration is driven:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Read-only default configuration : core-default.xml, hdfs-default.xml, yarn-default.xml and mapred-default.xml.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Site-specific configuration : etc\/hadoop\/core-site.xml, etc\/hadoop\/hdfs-site.xml, etc\/hadoop\/yarn-site.xml and etc\/hadoop\/mapred-site.xml.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Moreover, by setting site-specific values via above files and etc\/hadoop\/hadoop-env.sh and etc\/hadoop\/yarn-env.sh, we can control the Hadoop scripts found in the bin\/ directory of the distribution.<\/span><br \/>\n<span style=\"font-weight: 400\">In addition, we need to configure the environment in which the Hadoop daemons execute and also the configuration parameters for the Hadoop daemons, in order to configure the Hadoop cluster. Where, <\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">HDFS daemons: NameNode, and DataNode.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">YARN daemons: ResourceManager, and NodeManager.<\/span><\/li>\n<\/ul>\n<h2><b>7. Advantages of a Hadoop Cluster<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The cluster helps in increasing the speed of the analysis process.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">It is inexpensive.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">These clusters are failure resilient.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">One more benefit to Hadoop clusters is \u201cscalability\u201d, it means Hadoop offers Scalable and flexible Data Storage. Here Scalability means, we can scale a Hadoop cluster by adding new servers to the cluster if needed.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Hadoop Clusters deal with data from many sources and formats in a very quick, easy manner.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">It is possible to deploy Hadoop using a single-node installation, for evaluation purposes.<\/span><\/li>\n<\/ul>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/limitations-of-hadoop\/\"><b>Let&#8217;s discuss Hadoop Limitations<\/b><\/a><\/p>\n<h2><b>8. Cluster management<\/b><\/h2>\n<p><span style=\"font-weight: 400\">There are several options for Hadoop Cluster management. One of them is Apache Ambari, this is used and promoted by Hortonworks and many more. \u00a0As an advantage, we can manage more than one cluster at the same time by using Ambari. Another tool from various options for Hadoop Cluster management is Cloudera Manager. It is an end-to-end management tool for Apache Hadoop that offers complete control over Hadoop clusters. Moreover, it provides beneficial features to monitor performance as well as the health of the Hadoop cluster. Also, it permits us to deploy and operate a complete Hadoop stack in a very easy manner.<\/span><br \/>\n<span style=\"font-weight: 400\">So, this was all in the Hadoop Clusters. Hope you like our explanation<\/span><\/p>\n<h2><b>9. Conclusion: Hadoop Clusters<\/b><\/h2>\n<p><span style=\"font-weight: 400\">Hence, we have seen the whole about Hadoop Cluster in detail. Moreover, in this Hadoop Cluster tutorial, we discussed Architecture of Cluster in Hadoop, its Components along with Hadoop Nodes Configuration in detail. Also, we discussed Hadoop Cluster Diagram for better understanding with the Hadoop. Still, if you have any doubt, ask in the comment tab. You can also share the experience of reading this blog through comments.<\/span><br \/>\n<b>See also &#8211; <\/b><br \/>\n<a href=\"https:\/\/www.youtube.com\/watch?v=a-DXDkK1i08\"><b>Install Hadoop 2.x in Distributed Mode<\/b><\/a><br \/>\n<a href=\"http:\/\/www.bmcsoftware.in\/\"><b>For reference<\/b><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>1. Hadoop Cluster Today, we will start the Hadoop Cluster Tutorial. In this Tutorial, we will discuss Hadoop Cluster Architecture, diagram. Moreover, we will look at the Hadoop Cluster advantages and Hadoop Nodes configuration.&#46;&#46;&#46;<\/p>\n","protected":false},"author":7,"featured_media":25399,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[22],"tags":[255,309,784,2697,5223,5224,5225,5227,5228,5229,5300,15731],"class_list":["post-25240","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hadoop","tag-adding-nodes-to-hadoop-cluster","tag-advantages-of-a-hadoop-cluster-setup","tag-apache-hadoop-cluster","tag-communicating-between-nodes","tag-hadoop-cluster-architecture","tag-hadoop-cluster-components","tag-hadoop-cluster-diagram","tag-hadoop-cluster-setup","tag-hadoop-cluster-tutorial","tag-hadoop-clusters","tag-hadoop-nodes-configuration","tag-what-is-hadoop-cluster"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What is Hadoop Cluster | Hadoop Cluster Architecture - 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