Ibm Data Engine For Hadoop And Spark


Ibm Data Engine For Hadoop And Spark
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Ibm Data Engine For Hadoop And Spark


Ibm Data Engine For Hadoop And Spark
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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2016-08-24

Ibm Data Engine For Hadoop And Spark written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-24 with Computers categories.


This IBM® Redbooks® publication provides topics to help the technical community take advantage of the resilience, scalability, and performance of the IBM Power SystemsTM platform to implement or integrate an IBM Data Engine for Hadoop and Spark solution for analytics solutions to access, manage, and analyze data sets to improve business outcomes. This book documents topics to demonstrate and take advantage of the analytics strengths of the IBM POWER8® platform, the IBM analytics software portfolio, and selected third-party tools to help solve customer's data analytic workload requirements. This book describes how to plan, prepare, install, integrate, manage, and show how to use the IBM Data Engine for Hadoop and Spark solution to run analytic workloads on IBM POWER8. In addition, this publication delivers documentation to complement available IBM analytics solutions to help your data analytic needs. This publication strengthens the position of IBM analytics and big data solutions with a well-defined and documented deployment model within an IBM POWER8 virtualized environment so that customers have a planned foundation for security, scaling, capacity, resilience, and optimization for analytics workloads. This book is targeted at technical professionals (analytics consultants, technical support staff, IT Architects, and IT Specialists) that are responsible for delivering analytics solutions and support on IBM Power Systems.



Ibm Data Engine For Hadoop And Spark


Ibm Data Engine For Hadoop And Spark
DOWNLOAD eBooks

Author : Dino Quintero
language : en
Publisher:
Release Date : 2016

Ibm Data Engine For Hadoop And Spark written by Dino Quintero and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Data mining categories.


This IBM® Redbooks® publication provides topics to help the technical community take advantage of the resilience, scalability, and performance of the IBM Power SystemsTM platform to implement or integrate an IBM Data Engine for Hadoop and Spark solution for analytics solutions to access, manage, and analyze data sets to improve business outcomes. This book documents topics to demonstrate and take advantage of the analytics strengths of the IBM POWER8® platform, the IBM analytics software portfolio, and selected third-party tools to help solve customer's data analytic workload requirements. This book describes how to plan, prepare, install, integrate, manage, and show how to use the IBM Data Engine for Hadoop and Spark solution to run analytic workloads on IBM POWER8. In addition, this publication delivers documentation to complement available IBM analytics solutions to help your data analytic needs. This publication strengthens the position of IBM analytics and big data solutions with a well-defined and documented deployment model within an IBM POWER8 virtualized environment so that customers have a planned foundation for security, scaling, capacity, resilience, and optimization for analytics workloads. This book is targeted at technical professionals (analytics consultants, technical support staff, IT Architects, and IT Specialists) that are responsible for delivering analytics solutions and support on IBM Power Systems.



Enterprise Data Warehouse Optimization With Hadoop On Ibm Power Systems Servers


Enterprise Data Warehouse Optimization With Hadoop On Ibm Power Systems Servers
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2018-01-31

Enterprise Data Warehouse Optimization With Hadoop On Ibm Power Systems Servers written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Computers categories.


Data warehouses were developed for many good reasons, such as providing quick query and reporting for business operations, and business performance. However, over the years, due to the explosion of applications and data volume, many existing data warehouses have become difficult to manage. Extract, Transform, and Load (ETL) processes are taking longer, missing their allocated batch windows. In addition, data types that are required for business analysis have expanded from structured data to unstructured data. The Apache open source Hadoop platform provides a great alternative for solving these problems. IBM® has committed to open source since the early years of open Linux. IBM and Hortonworks together are committed to Apache open source software more than any other company. IBM Power SystemsTM servers are built with open technologies and are designed for mission-critical data applications. Power Systems servers use technology from the OpenPOWER Foundation, an open technology infrastructure that uses the IBM POWER® architecture to help meet the evolving needs of big data applications. The combination of Power Systems with Hortonworks Data Platform (HDP) provides users with a highly efficient platform that provides leadership performance for big data workloads such as Hadoop and Spark. This IBM RedpaperTM publication provides details about Enterprise Data Warehouse (EDW) optimization with Hadoop on Power Systems. Many people know Power Systems from the IBM AIX® platform, but might not be familiar with IBM PowerLinuxTM, so part of this paper provides a Power Systems overview. A quick introduction to Hadoop is provided for those not familiar with the topic. Details of HDP on Power Reference architecture are included that will help both software architects and infrastructure architects understand the design. In the optimization chapter, we describe various topics: traditional EDW offload, sizing guidelines, performance tuning, IBM Elastic StorageTM Server (ESS) for data-intensive workload, IBM Big SQL as the common structured query language (SQL) engine for Hadoop platform, and tools that are available on Power Systems that are related to EDW optimization. We also dedicate some pages to the analytics components (IBM Data Science Experience (IBM DSX) and IBM SpectrumTM Conductor for Spark workload) for the Hadoop infrastructure.



Apache Spark Implementation On Ibm Z Os


Apache Spark Implementation On Ibm Z Os
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Author : Lydia Parziale
language : en
Publisher: IBM Redbooks
Release Date : 2016-08-13

Apache Spark Implementation On Ibm Z Os written by Lydia Parziale and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-13 with Computers categories.


The term big data refers to extremely large sets of data that are analyzed to reveal insights, such as patterns, trends, and associations. The algorithms that analyze this data to provide these insights must extract value from a wide range of data sources, including business data and live, streaming, social media data. However, the real value of these insights comes from their timeliness. Rapid delivery of insights enables anyone (not only data scientists) to make effective decisions, applying deep intelligence to every enterprise application. Apache Spark is an integrated analytics framework and runtime to accelerate and simplify algorithm development, depoyment, and realization of business insight from analytics. Apache Spark on IBM® z/OS® puts the open source engine, augmented with unique differentiated features, built specifically for data science, where big data resides. This IBM Redbooks® publication describes the installation and configuration of IBM z/OS Platform for Apache Spark for field teams and clients. Additionally, it includes examples of business analytics scenarios.



Bridging Relational And Nosql Databases


Bridging Relational And Nosql Databases
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Author : Gaspar, Drazena
language : en
Publisher: IGI Global
Release Date : 2017-11-30

Bridging Relational And Nosql Databases written by Gaspar, Drazena and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Computers categories.


Relational databases have been predominant for many years and are used throughout various industries. The current system faces challenges related to size and variety of data thus the NoSQL databases emerged. By joining these two database models, there is room for crucial developments in the field of computer science. Bridging Relational and NoSQL Databases is an innovative source of academic content on the convergence process between databases and describes key features of the next database generation. Featuring coverage on a wide variety of topics and perspectives such as BASE approach, CAP theorem, and hybrid and native solutions, this publication is ideally designed for professionals and researchers interested in the features and collaboration of relational and NoSQL databases.



Ibm Power Systems L And Lc Server Positioning Guide


Ibm Power Systems L And Lc Server Positioning Guide
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2017-02-16

Ibm Power Systems L And Lc Server Positioning Guide written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-16 with Computers categories.


This IBM® RedpaperTM publication is written to assist you in locating the optimal server/workload fit within the IBM Power SystemsTM L and IBM OpenPOWER LC product lines. IBM has announced several scale-out servers, and as a partner in the OpenPOWER organization, unique design characteristics that are engineered into the LC line have broadened the suite of available workloads beyond typical client OS hosting. This paper looks at the benefits of the Power Systems L servers and OpenPOWER LC servers, and how they are different, providing unique benefits for Enterprise workloads and use cases.



Apache Spark For The Enterprise Setting The Business Free


Apache Spark For The Enterprise Setting The Business Free
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Author : Oliver Draese
language : en
Publisher: IBM Redbooks
Release Date : 2016-02-09

Apache Spark For The Enterprise Setting The Business Free written by Oliver Draese and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-09 with Computers categories.


Analytics is increasingly an integral part of day-to-day operations at today's leading businesses, and transformation is also occurring through huge growth in mobile and digital channels. Enterprise organizations are attempting to leverage analytics in new ways and transition existing analytics capabilities to respond with more flexibility while making the most efficient use of highly valuable data science skills. The recent growth and adoption of Apache Spark as an analytics framework and platform is very timely and helps meet these challenging demands. The Apache Spark environment on IBM z/OS® and Linux on IBM z SystemsTM platforms allows this analytics framework to run on the same enterprise platform as the originating sources of data and transactions that feed it. If most of the data that will be used for Apache Spark analytics, or the most sensitive or quickly changing data is originating on z/OS, then an Apache Spark z/OS based environment will be the optimal choice for performance, security, and governance. This IBM® RedpaperTM publication explores the enterprise analytics market, use of Apache Spark on IBM z SystemsTM platforms, integration between Apache Spark and other enterprise data sources, and case studies and examples of what can be achieved with Apache Spark in enterprise environments. It is of interest to data scientists, data engineers, enterprise architects, or anybody looking to better understand how to combine an analytics framework and platform on enterprise systems.



Ibm Software Defined Infrastructure For Big Data Analytics Workloads


Ibm Software Defined Infrastructure For Big Data Analytics Workloads
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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2015-06-29

Ibm Software Defined Infrastructure For Big Data Analytics Workloads written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-29 with Computers categories.


This IBM® Redbooks® publication documents how IBM Platform Computing, with its IBM Platform Symphony® MapReduce framework, IBM Spectrum Scale (based Upon IBM GPFSTM), IBM Platform LSF®, the Advanced Service Controller for Platform Symphony are work together as an infrastructure to manage not just Hadoop-related offerings, but many popular industry offeringsm such as Apach Spark, Storm, MongoDB, Cassandra, and so on. It describes the different ways to run Hadoop in a big data environment, and demonstrates how IBM Platform Computing solutions, such as Platform Symphony and Platform LSF with its MapReduce Accelerator, can help performance and agility to run Hadoop on distributed workload managers offered by IBM. This information is for technical professionals (consultants, technical support staff, IT architects, and IT specialists) who are responsible for delivering cost-effective cloud services and big data solutions on IBM Power SystemsTM to help uncover insights among client's data so they can optimize product development and business results.



Cloudera Data Platform Private Cloud Base With Ibm Spectrum Scale


Cloudera Data Platform Private Cloud Base With Ibm Spectrum Scale
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Author : Wei Gong
language : en
Publisher: IBM Redbooks
Release Date : 2021-08-27

Cloudera Data Platform Private Cloud Base With Ibm Spectrum Scale written by Wei Gong and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-27 with Computers categories.


This IBM® Redpaper publication provides guidance on building an enterprise-grade data lake by using IBM Spectrum® Scale and Cloudera Data Platform (CDP) Private Cloud Base for performing in-place Cloudera Hadoop or Cloudera Spark-based analytics. It also covers the benefits of the integrated solution and gives guidance about the types of deployment models and considerations during the implementation of these models. August 2021 update added CES protocol support in Hadoop environment



Harness The Power Of Big Data The Ibm Big Data Platform


Harness The Power Of Big Data The Ibm Big Data Platform
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Author : Paul Zikopoulos
language : en
Publisher: McGraw Hill Professional
Release Date : 2012-11-08

Harness The Power Of Big Data The Ibm Big Data Platform written by Paul Zikopoulos and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-08 with Computers categories.


Boost your Big Data IQ! Gain insight into how to govern and consume IBM’s unique in-motion and at-rest Big Data analytic capabilities Big Data represents a new era of computing—an inflection point of opportunity where data in any format may be explored and utilized for breakthrough insights—whether that data is in-place, in-motion, or at-rest. IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is infusing open source Big Data technologies with IBM innovation that manifest in a platform capable of "changing the game." The four defining characteristics of Big Data—volume, variety, velocity, and veracity—are discussed. You’ll understand how IBM is fully committed to Hadoop and integrating it into the enterprise. Hear about how organizations are taking inventories of their existing Big Data assets, with search capabilities that help organizations discover what they could already know, and extend their reach into new data territories for unprecedented model accuracy and discovery. In this book you will also learn not just about the technologies that make up the IBM Big Data platform, but when to leverage its purpose-built engines for analytics on data in-motion and data at-rest. And you’ll gain an understanding of how and when to govern Big Data, and how IBM’s industry-leading InfoSphere integration and governance portfolio helps you understand, govern, and effectively utilize Big Data. Industry use cases are also included in this practical guide.