Hadoop Cloudera Architecture

Cloudera vs MapR vs Hortonworks.

Hadoop cloudera architecture. Cloudera Inc was founded as a collective effort of big data geniuses from Google, Oracle, Yahoo and Facebook in the year 08 Cloudera was the first one to develop and distribute Apache Hadoop based software and is still the largest organization with the largest user base with many customers to their belt In addition to the core of the distribution based upon Apache Hadoop, Cloudera has provided more proprietary tools such as the Cloudera Management suite to automate the installation. Although Hadoop is a free, opensource platform, Cloudera adds substantial value by providing strong security, policydriven data governance, formal system management, product support and lots of important system integrations to bring all data sources together under its umbrella. HDFS Architecture Apache HDFS or Hadoop Distributed File System is a blockstructured file system where each file is divided into blocks of a predetermined size These blocks are stored across a cluster of one or several machines Apache Hadoop HDFS Architecture follows a Master/Slave Architecture, where a cluster comprises of a single NameNode (Master node) and all the other nodes are DataNodes (Slave nodes).

Understanding YARN architecture YARN allows you to use various data processing engines for batch, interactive, and realtime stream processing of data stored in HDFS or cloud storage like S3 and ADLS You can use different processing frameworks for different usecases, for example, you can run Hive for SQL applications, Spark for inmemory applications, and Storm for streaming applications, all on the same Hadoop cluster. It is a Hadoop 2x Highlevel Architecture We will discuss indetailed Lowlevel Architecture in coming sections Hadoop Common Module is a Hadoop Base API (A Jar file) for all Hadoop Components All other components works on top of this module HDFS stands for Hadoop Distributed File System It is also know as HDFS V2 as it is part of Hadoop 2x with some enhanced features It is used as a Distributed Storage System in Hadoop Architecture. After having fun building, deploying, managing and using Hadoop clusters, Ian joined Cloudera as a Solutions Architect in 14 His day job now involves integrating Hadoop into enterprises and making stuff work in the real world.

This course is designed for data architects, data integration architects, managers, Clevel executives, decision makers, technical infrastructure team, and Hadoop administrators or developers who want to understand the fundamentals of Big Data and the Hadoop ecosystem No previous Hadoop or programming knowledge is required. The modular architecture of Hadoop makes it very flexible in adding new functionalities that tend to answer more diverse Big Data tasks Vendors who have implemented over Hadoop’s openended framework, tweaked its code to enhance the existing functionalities. And Cloudera, the leader in enterprise analytic data management powered by Apache™ Hadoop®, this reference architecture supplies a blueprint for augmenting legacy warehouses to increase capacity and optimize performance It enables organizations to better capitalize on the business value of big data.

Apache Hadoop The Apache™ Hadoop® project develops opensource software for reliable, scalable, distributed computing The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware It has many similarities with existing distributed file systems However, the differences from other distributed file systems are significant HDFS is highly faulttolerant and is designed to be deployed on lowcost hardware. Apache Flume Apache Hadoop Apache HBase Apache Kafka Apache Spark Evaluating which streaming architectural pattern is the best match to your use case is a precondition for a successful production deployment The Apache Hadoop ecosystem has become a preferred platform for enterprises seeking to process and understand largescale data in real time Technologies like Apache Kafka, Apache Flume, Apache Spark, Apache Storm, and Apache Samza are increasingly pushing the envelope on what is possible.

The Data Cloud — Powered By Hadoop One key aspect of the Cloudera Data Platform (CDP), which is just beginning to be understood, is how much of a recombinantevolution it represents, from an architectural standpoint, visàvis Hadoop in its first decade I’ve been having a blast showing CDP to customers over the past few months and the response has been nothing short of phenomenal. Cloudera is market leader in hadoop community as Redhat has been in Linux Community (As other answer indicated) Cloudera is an umbrella product which deal with big data systems Having Apache Hadoop at core, Cloudera has created an architecture w. Hadoop is an Apache opensource framework that store and process Big Data in a distributed environment across the cluster using simple programming models Hadoop provides parallel computation on top of distributed storage To learn more about Hadoop in detail from Certified Experts you can refer to this Hadoop tutorial blog.

Apache Flume Apache Hadoop Apache HBase Apache Kafka Apache Spark Evaluating which streaming architectural pattern is the best match to your use case is a precondition for a successful production deployment The Apache Hadoop ecosystem has become a preferred platform for enterprises seeking to process and understand largescale data in real time Technologies like Apache Kafka, Apache Flume, Apache Spark, Apache Storm, and Apache Samza are increasingly pushing the envelope on what is possible. Hadoop Common These Java libraries are used to start Hadoop and are used by other Hadoop modules Hadoop Architecture The Hadoop architecture is a package of the file system, MapReduce engine and the HDFS (Hadoop Distributed File System) The MapReduce engine can be MapReduce/MR1 or YARN/MR2. The default factor for single node Hadoop cluster is one In multinode Hadoop clusters, the daemons run on separate host or machine A multinode Hadoop cluster has masterslave architecture In this NameNode daemon run on the master machine.

Cloudera is market leader in hadoop community as Redhat has been in Linux Community (As other answer indicated) Cloudera is an umbrella product which deal with big data systems Having Apache Hadoop at core, Cloudera has created an architecture w. MLens is an accelerator toolkit from Knowledge Lens which enables automated workload migration from Hadoop (Cloudera/Hortonworks/MapR distributions) to Databricks Unlike other tools in the market, MLens enables transparent accessibility of migrated assets so developers can review and make necessary amendments MLens10. Cloudera University's Big Data Architecture Workshop (BDAW) is a 3day learning event that addresses advanced big data architecture topics BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem.

This fourday administrator training course provides participants with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster using Cloudera Manager From installation and configuration through load balancing and tuning, this training course is the best preparation for the realworld challenges faced. Hadoop is an ecosystem of open source components that fundamentally changes the way enterprises store, process, and analyze data Unlike traditional systems, Hadoop enables multiple types of analytic workloads to run on the same data, at the same time, at massive scale on industrystandard hardware CDH, Cloudera's open source platform, is the most popular distribution of Hadoop and related projects in the world (with support available via a Cloudera Enterprise subscription). In a single node Hadoop cluster, all the processes run on one JVM instance The user need not make any configuration setting The Hadoop user only needs to set JAVA_HOME variable The default factor for single node Hadoop cluster is one In multinode Hadoop clusters, the daemons run on separate host or machine A multinode Hadoop cluster has masterslave architecture.

Also for each diagram below, red represents EDW optimization data architecture and black represents existing data architecture Use Case 1 Active Archiving In this use case aged data is offloaded to Hadoop instead of being stored on the EDW or on archival storage like tape. Lenovo Big Data Reference Architecture for Cloudera Distribution for Hadoop Provides a thoroughly tested and integrated solution that combines the benefits of leadingedge technologies with mature, enterpriseready features. Cloudera Hadoop impala architecture is very different compared to other database engine on HDFS like Hive The Impala server is a distributed, massively parallel processing (MPP) database engine The architecture is similar to the other distributed databases like Netezza, Greenplum etc Hadoop impala consists of different daemon processes that run on specific hosts within your CDH cluster.

The Hadoop architecture allows parallel processing of data using several components Hadoop HDFS to store data across slave machines Hadoop YARN for resource management in the Hadoop cluster Hadoop MapReduce to process data in a distributed fashion Zookeeper to ensure synchronization across a. This release of the reference architecture is for deploying Cloudera’s Distribution of Apache Hadoop (CDH) 511 on Red Hat OSP 11 This reference architecture articulates a specific design pattern which is recommended to be administratordriven as opposed to enduser selfservice based. The Cloudera Hadoop Reference Configuration is based on Cisco UCS Common Platform Architecture (CPA) for Big Data, a highly scalable architecture designed to meet a variety of scaleout application demands with seamless data integration and management integration capabilities built using the following components.

Hadoop is an open source framework overseen by Apache Software Foundation which is written in Java for storing and processing of huge datasets with the cluster of commodity hardware There are mainly two problems with the big data First one is to store such a huge amount of data and the second one is to process that stored data. Cloudera Hadoop Distribution provides a scalable, flexible, integrated platform that makes it easy to manage rapidly increasing volumes and varieties of data in your enterprise In this blog on Cloudera Hadoop Distribution, we will be covering the following topics Introduction to Hadoop;. The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware It has many similarities with existing distributed file systems However, the differences from other distributed file systems are significant HDFS is highly faulttolerant and is designed to be deployed on lowcost hardware.

Cloudera University's Big Data Architecture Workshop (BDAW) is a 3day learning event that addresses advanced big data architecture topics BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. Unlike data warehouses, Hadoop is in a better position to deal with disruption Its key strengths are open source, and decoupled architecture Open source means the pace of innovation can be. Shared storage platform in the data center, as well as for Hadoop administrators and architects who will be data center architects or engineers and/or collaborate with specialists in that space This document describes Dell EMC and Cloudera recommendations on the following topics 1 Storage array considerations 2 Data network considerations 3.

Lenovo Big Data Reference Architecture for Cloudera Distribution for Hadoop Provides a thoroughly tested and integrated solution that combines the benefits of leadingedge technologies with mature, enterpriseready features. Also for each diagram below, red represents EDW optimization data architecture and black represents existing data architecture Use Case 1 Active Archiving In this use case aged data is offloaded to Hadoop instead of being stored on the EDW or on archival storage like tape. Cloudera Search Training Cloudera University’s threeday Search training course is for developers and data engineers who want to index data in Hadoop for more powerful realtime queries Participants will learn to get more value from their data by integrating Cloudera Search with external applications.

Hadoop is an Apache opensource framework that store and process Big Data in a distributed environment across the cluster using simple programming models Hadoop provides parallel computation on top of distributed storage To learn more about Hadoop in detail from Certified Experts you can refer to this Hadoop tutorial blog. Concur’s Modern Hadoop Architecture Complete data access (structured and unstructured) 1 Improvements New Data Pig Process 1 1 Store HDFS 18 18© Cloudera, Inc. After having fun building, deploying, managing and using Hadoop clusters, Ian joined Cloudera as a Solutions Architect in 14 His day job now involves integrating Hadoop into enterprises and making stuff work in the real world.

Hadoop’s costeffective scalability allows for more analytic exploration of data that previously was too costly to store or troublesome to format Integration of Cloudera and SAS technologies makes big data analytics approachable and supports innovative applications. CDH delivers everything you need for enterprise use right out of the box By integrating Hadoop with more than a dozen other critical open source projects, Cloudera has created a functionally advanced system that helps you perform endtoend Big Data workflows. Cloudera is a company that specializes in mega data collections built around the Apache Hadoop platform to create what it calls “enterprise data hubs” Such hubs enable customers to create informationdriven organizations, where Cloudera provides a platform for enterpriseready data management.

The Cloudera foundation is built upon the Apache Hadoop framework and employs the largest group of committers under one roof Cloudera enables organizations to capture, store, analyze and act on any data at massive speed and scale in a single data solution using Hadoop platforms Cloudera is being agnostic to hardware and our solutions can be optimized for both the Cloud and onpremises environments. HDFS Key Features HDFS is a faulttolerant and selfhealing distributed filesystem designed to turn a cluster of industrystandard servers into a massively scalable pool of storage Developed specifically for largescale data processing workloads where scalability, flexibility, and throughput are critical, HDFS accepts data in any format regardless of schema, optimizes for highbandwidth streaming, and scales to proven deployments of 100PB and beyond. • Dell Ready Bundle for Cloudera Hadoop Architecture Guide and best practices • Optimized server configurations • Optimized network infrastructure • Cloudera Enterprise Solution Use Case Summary The Dell Ready Bundle for Cloudera Hadoop is designed to address the use cases described in Table 1 Big Data Solution Use Cases on page 16.

The Cloudera Hadoop Reference Configuration is based on Cisco UCS Common Platform Architecture (CPA) for Big Data, a highly scalable architecture designed to meet a variety of scaleout application demands with seamless data integration and management integration capabilities built using the following components. HDFS Architecture Apache HDFS or Hadoop Distributed File System is a blockstructured file system where each file is divided into blocks of a predetermined size These blocks are stored across a cluster of one or several machines Apache Hadoop HDFS Architecture follows a Master/Slave Architecture, where a cluster comprises of a single NameNode (Master node) and all the other nodes are DataNodes (Slave nodes). Cloudera Hadoop impala architecture is very different compared to other database engine on HDFS like Hive The Impala server is a distributed, massively parallel processing (MPP) database engine The architecture is similar to the other distributed databases like Netezza, Greenplum etc Hadoop impala consists of different daemon processes that run on specific hosts within your CDH cluster.