Learn how to configure your Hadoop cluster to run optimal MapReduce jobs Overview Optimize your M... more Learn how to configure your Hadoop cluster to run optimal MapReduce jobs 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.
DataMiningCloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting... more DataMiningCloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting parallel data mining algorithms and distributed data mining on a Cloud environment. Service Oriented Architecture (SOA) approach is used to implement all the data mining applications independent services, each capable of carrying out a set of predefined tasks. DMCloud architecture relies on the Cloud IaaS OpenNebula Infrastructure extended with a specific workflows-based SLA broker, and other open technology and standards. It provides tools and services facilitating the user development, deployment and transparent utilization of data mining applications in a cloud environment.
Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high ... more Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high performance NoSQL .NET based applications with step-by-step practical examples Master advanced RavenDB indexes and queries Create objects in .NET and map them to RavenDB In Detail RavenDB is a second generation document database written in .NET, offering a flexible data model designed to address requirements coming from real-world systems. It is different from the other document databases around, as with RavenDB you can get up and running in a few minutes, and that includes grasping all the basics. It allows you to build high-performance, low-latency applications with ease and efficiency. RavenDB 2.x Beginners Guide introduces RavenDB concepts and teaches you everything, right from installing RavenDB, to creating documents, and querying indexes. This book will help you take advantage of powerful, document-oriented NoSQL databases and build a solid foundation on which you can create your ...
Cloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting parallel ... more Cloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting parallel data mining algorithms and distributed data mining on a Cloud environment. Service Oriented Architecture (SOA) approach is used to implement all the data mining applications independent services, each capable of carrying out a set of predefined tasks. DMCloud architecture relies on the Cloud IaaS OpenNebula Infrastructure extended with a specific workflows-based SLA broker, and other open technology and standards. It provides tools and services facilitating the user development, deployment and transparent utilization of data mining applications in a cloud environment.
Learn how to configure your Hadoop cluster to run optimal MapReduce jobs Overview Optimize your M... more Learn how to configure your Hadoop cluster to run optimal MapReduce jobs 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 detai...
Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high ... more Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high performance NoSQL .NET based applications with step-by-step practical examples Master advanced RavenDB indexes and queries Create objects in .NET and map them to RavenDB In Detail RavenDB is a second generation document database written in .NET, offering a flexible data model designed to address requirements coming from real-world systems. It is different from the other document databases around, as with RavenDB you can get up and running in a few minutes, and that includes grasping all the basics. It allows you to build high-performance, low-latency applications with ease and efficiency. RavenDB 2.x Beginners Guide introduces RavenDB concepts and teaches you everything, right from installing RavenDB, to creating documents, and querying indexes. This book will help you take advantage of powerful, document-oriented NoSQL databases and build a solid foundation on which you can create your .NET applications. This book presents RavenDB, the .NET document-oriented NoSQL database, through a series of clear and practical exercises that will help you to take advantage of this database server. The book starts off with an introduction to RavenDB and its Management Studio. You will then move ahead and learn how to quickly and efficiently build high performance, NoSQL document-oriented .NET applications using the .NET client API or the HTTP REST API. Next, Dynamic and static indexes that use map/reduce to process datasets are covered. You will then see how to create and query these indexes, with the help of detailed examples. You will also learn how to deploy your RavenDB server in a production environment and how to optimize and secure it. With numerous practical examples, RavenDB 2.x Beginners Guide teaches you everything you need to know for building high performance .NET document-oriented NoSQL databases. What you will learn from this book Get RavenDB up and running on your local machine or server, and discover the RavenDB Management Studio Interact with RavenDB using the .NET Client API and REST HTTP API Map .NET objects to RavenDB documents Create and query dynamic indexes, and single-map and multi-map static indexes Implement map/reduce to process large datasets Learn and implement paging, exact matching, and full-text search queries Host RavenDB within IIS and run it as a Windows service or in embedded mode Secure RavenDB using a replication bundle and optimize it with sharding Approach Written in a friendly, example-driven Beginners Guide format, there are plenty of step-by-step instructions and examples that are designed to help you get started with RavenDB. Who this book is written for If you are a .NET developer, new to document-oriented databases, and you wish to learn how to build applications using NoSQL databases, then this book is for you. Experience with relational database systems will be helpful, but not necessary.
Learn how to configure your Hadoop cluster to run optimal MapReduce jobs Overview Optimize your M... more Learn how to configure your Hadoop cluster to run optimal MapReduce jobs 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.
DataMiningCloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting... more DataMiningCloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting parallel data mining algorithms and distributed data mining on a Cloud environment. Service Oriented Architecture (SOA) approach is used to implement all the data mining applications independent services, each capable of carrying out a set of predefined tasks. DMCloud architecture relies on the Cloud IaaS OpenNebula Infrastructure extended with a specific workflows-based SLA broker, and other open technology and standards. It provides tools and services facilitating the user development, deployment and transparent utilization of data mining applications in a cloud environment.
Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high ... more Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high performance NoSQL .NET based applications with step-by-step practical examples Master advanced RavenDB indexes and queries Create objects in .NET and map them to RavenDB In Detail RavenDB is a second generation document database written in .NET, offering a flexible data model designed to address requirements coming from real-world systems. It is different from the other document databases around, as with RavenDB you can get up and running in a few minutes, and that includes grasping all the basics. It allows you to build high-performance, low-latency applications with ease and efficiency. RavenDB 2.x Beginners Guide introduces RavenDB concepts and teaches you everything, right from installing RavenDB, to creating documents, and querying indexes. This book will help you take advantage of powerful, document-oriented NoSQL databases and build a solid foundation on which you can create your ...
Cloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting parallel ... more Cloud is a framework that extends the current Weka Grid-enabler Toolkits for supporting parallel data mining algorithms and distributed data mining on a Cloud environment. Service Oriented Architecture (SOA) approach is used to implement all the data mining applications independent services, each capable of carrying out a set of predefined tasks. DMCloud architecture relies on the Cloud IaaS OpenNebula Infrastructure extended with a specific workflows-based SLA broker, and other open technology and standards. It provides tools and services facilitating the user development, deployment and transparent utilization of data mining applications in a cloud environment.
Learn how to configure your Hadoop cluster to run optimal MapReduce jobs Overview Optimize your M... more Learn how to configure your Hadoop cluster to run optimal MapReduce jobs 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 detai...
Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high ... more Build high performance NoSQL .NET-based applications quickly and efficiently Overview Build high performance NoSQL .NET based applications with step-by-step practical examples Master advanced RavenDB indexes and queries Create objects in .NET and map them to RavenDB In Detail RavenDB is a second generation document database written in .NET, offering a flexible data model designed to address requirements coming from real-world systems. It is different from the other document databases around, as with RavenDB you can get up and running in a few minutes, and that includes grasping all the basics. It allows you to build high-performance, low-latency applications with ease and efficiency. RavenDB 2.x Beginners Guide introduces RavenDB concepts and teaches you everything, right from installing RavenDB, to creating documents, and querying indexes. This book will help you take advantage of powerful, document-oriented NoSQL databases and build a solid foundation on which you can create your .NET applications. This book presents RavenDB, the .NET document-oriented NoSQL database, through a series of clear and practical exercises that will help you to take advantage of this database server. The book starts off with an introduction to RavenDB and its Management Studio. You will then move ahead and learn how to quickly and efficiently build high performance, NoSQL document-oriented .NET applications using the .NET client API or the HTTP REST API. Next, Dynamic and static indexes that use map/reduce to process datasets are covered. You will then see how to create and query these indexes, with the help of detailed examples. You will also learn how to deploy your RavenDB server in a production environment and how to optimize and secure it. With numerous practical examples, RavenDB 2.x Beginners Guide teaches you everything you need to know for building high performance .NET document-oriented NoSQL databases. What you will learn from this book Get RavenDB up and running on your local machine or server, and discover the RavenDB Management Studio Interact with RavenDB using the .NET Client API and REST HTTP API Map .NET objects to RavenDB documents Create and query dynamic indexes, and single-map and multi-map static indexes Implement map/reduce to process large datasets Learn and implement paging, exact matching, and full-text search queries Host RavenDB within IIS and run it as a Windows service or in embedded mode Secure RavenDB using a replication bundle and optimize it with sharding Approach Written in a friendly, example-driven Beginners Guide format, there are plenty of step-by-step instructions and examples that are designed to help you get started with RavenDB. Who this book is written for If you are a .NET developer, new to document-oriented databases, and you wish to learn how to build applications using NoSQL databases, then this book is for you. Experience with relational database systems will be helpful, but not necessary.
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