Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Optimizing Hadoop for MapReduce

Buy

This book is the perfect introduction to sophisticated concepts in MapReduce and will ensure you have the knowledge to optimize job performance. This is not an academic treatise; it's an example-driven tutorial for the real world.

Overview

  • Optimize your MapReduce job performance
  • Identify your Hadoop cluster's weaknesses
  • Tune your MapReduce configuration

In Detail

MapReduce is the distribution system that the Hadoop MapReduce engine uses to distribute work around a cluster by working parallel on smaller data sets. It is useful in a wide range of applications, including distributed pattern-based searching, distributed sorting, web link-graph reversal, term-vector per host, web access log stats, inverted index construction, document clustering, machine learning, and statistical machine translation.

This book introduces you to advanced MapReduce concepts and teaches you everything from identifying the factors that affect MapReduce job performance to tuning the MapReduce configuration. Based on real-world experience, this book will help you to fully utilize your cluster's node resources to run MapReduce jobs optimally.

This book details the Hadoop MapReduce job performance optimization process. Through a number of clear and practical steps, it will help you to fully utilize your cluster's node resources.

Starting with how MapReduce works and the factors that affect MapReduce performance, you will be given an overview of Hadoop metrics and several performance monitoring tools. Further on, you will explore performance counters that help you identify resource bottlenecks, check cluster health, and size your Hadoop cluster. You will also learn about optimizing map and reduce tasks by using Combiners and compression.

The book ends with best practices and recommendations on how to use your Hadoop cluster optimally.

What you will learn from this book

  • Learn about the factors that affect MapReduce performance
  • Utilize the Hadoop MapReduce performance counters to identify resource bottlenecks
  • Size your Hadoop cluster's nodes
  • Set the number of mappers and reducers correctly
  • Optimize mapper and reducer task throughput and code size using compression and Combiners
  • Understand the various tuning properties and best practices to optimize clusters

Approach

This book is an example-based tutorial that deals with optimizing MapReduce job performance.

Who this book is written for

If you are a Hadoop administrator, developer, MapReduce user, or beginner, this book is the best choice available if you wish to optimize your clusters and applications. Having prior knowledge of creating MapReduce applications is not necessary, but will help you better understand the concepts and snippets of MapReduce class template code.

(HTML tags aren't allowed.)

Fuzzy Quantifiers: A Computational Theory (Studies in Fuzziness and Soft Computing)
Fuzzy Quantifiers: A Computational Theory (Studies in Fuzziness and Soft Computing)
From a linguistic perspective, it is quantification which makes all the difference between “having no dollars” and “having a lot of dollars”. And it is the meaning of the quantifier “most” which eventually decides if “Most Americans voted Kerry” or “Most Americans voted Bush” (as it...
Java All-In-One Desk Reference For Dummies (Computers)
Java All-In-One Desk Reference For Dummies (Computers)
9 books in 1—your key to success with Java!

Your one-stop guide to taming Java® and boosting your developer skills

Want to start programming with Java? This handy resource packs all the Java essentials you need into one easy-to-use guide. It's been fully updated for Java 6, covering...

Computing Qualitatively Correct Approximations of Balance Laws: Exponential-Fit, Well-Balanced and Asymptotic-Preserving (SEMA SIMAI Springer Series)
Computing Qualitatively Correct Approximations of Balance Laws: Exponential-Fit, Well-Balanced and Asymptotic-Preserving (SEMA SIMAI Springer Series)

The book gives an overview of recent numerical techniques for the integration of partial differential equations, especially hyperbolic systems of balance laws in one space dimension (Part I) and weakly nonlinear kinetic equations (Part II). Several of its salient features are:

  • Surveys both analytical and numerical aspects...

Creating a Data-Driven Organization
Creating a Data-Driven Organization

What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture. This practical book shows you how true data-drivenness involves processes that require genuine buy-in across your company, from analysts...

Juniper MX Series
Juniper MX Series

Discover why routers in the Juniper MX Series, with their advanced feature sets and record breaking scale, are so popular among enterprises and network service providers. This authoritative book shows you step-by-step how to implement high-density, high-speed Layer 2 and Layer 3 Ethernet services, using Router Engine DDoS Protection,...

Sas 9.1 Language Reference Concepts
Sas 9.1 Language Reference Concepts
This title comprehensively documents essential concepts for SAS features, the DATA step, and SAS files, including general BASE SAS concepts, BASE SAS DATA, BASE SAS file concepts, and much more.

Base SAS software enables you to bring all your data into a single system. This title comprehensively documents essential concepts for SAS
...
©2019 LearnIT (support@pdfchm.net) - Privacy Policy