Learning Couchbase
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Learning Couchbase
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Author : Henry Potsangbam
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-11-23
Learning Couchbase written by Henry Potsangbam and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-23 with Computers categories.
Design documents and implement real world e-commerce applications with Couchbase About This Book Get acquainted with Couchbase architecture and design your document-based data schema Implement full text search using industry standard elastic search plugins Develop critical and high performance applications using this hands-on tutorial guide Who This Book Is For If you are new to the NoSQL document system or have little or no experience in NoSQL development and administration and are planning to deploy Couchbase for your next project, then this book is for you. It would be helpful to have a bit of familiarity with Java. What You Will Learn Get acquainted with the concept of NoSQL databases and configure your Couchbase database cluster Maintain Couchbase effectively using the web-based administrative console with ease Enable partition capabilities by making use of Buckets Analyze important design considerations for maintaining relationship between various documents Use Couchbase SDK Java API to store and retrieve document Write views using map/reduce to retrieve documents efficiently Get familiar with N1QL and how to use it in Java applications Integrate Couchbase with Elasticsearch to implement full text search Configure XDCR for disaster recovery and develop ecommerce application using Couchbase In Detail NoSQL database systems have changed application development in terms of adaptability to dynamics schema and scalability. Compared with the currently available NoSQL database systems, Couchbase is the fastest. Its ease of configuration and powerful features for storing different schema structures, retrieval using map reduce and inbuilt disaster recovery by replicating document across the geographical region, make it one of the most powerful, scalable and comprehensive NoSQL in the market. Couchbase also introduces smart client API for various programming language to integrate the database with the application easily, yet providing very complex features like cluster health awareness. This book achieves its goal by taking up an end-to-end development structure, right from understanding NOSQL document design to implementing full fledged eCommerce application design using Couchbase as a backend. Starting with the architecture of Couchbase to get you up and running, this book quickly takes you through designing a NoSQL document and implementing highly scalable applications using Java API. You will then be introduced to document design and get to know the various ways to administer Couchbase. Followed by this, learn to store documents using bucket. Moving on, you will then learn to store, retrieve and delete documents using smart client base on Java API. You will then retrieve documents using SQL like syntax call N1QL. Next, you will learn how to write map reduce base views. Finally, you will configure XDCR for disaster recovery and implement an eCommerce application using Couchbase. Style and approach The book starts from absolute basics and slowly moves to more advanced topics ensuring at every step that all concepts and terms are understood by the reader to have complete understanding at every stage. Technical and complex terms are explained in clear and simple language, thus making this book a perfect companion for those who have started their journey to NoSQL using Couchbase
Intelligent Systems In Big Data Semantic Web And Machine Learning
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Author : Noreddine Gherabi
language : en
Publisher: Springer Nature
Release Date : 2021-05-28
Intelligent Systems In Big Data Semantic Web And Machine Learning written by Noreddine Gherabi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Computers categories.
This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.
Developing With Couchbase Server
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Author : MC Brown
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-02-01
Developing With Couchbase Server written by MC Brown and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-01 with Computers categories.
Today’s highly interactive websites pose a challenge for traditional SQL databases—the ability to scale rapidly and serve loads of concurrent users. With this concise guide, you’ll learn how to build web applications on top of Couchbase Server 2.0, a NoSQL database that can handle websites and social media where hundreds of thousands of users read and write large volumes of information. Using food recipe information as examples, this book demonstrates how to take advantage of Couchbase’s document-oriented database design, and how to store and query data with various CRUD operations. Discover why Couchbase is better than SQL databases with memcached tiers for managing data from the most interactive portions of your application. Learn about Couchbase Server’s cluster-based architecture and how it differs from SQL databases Choose a client library for Java, .NET, Ruby, Python, PHP, or C, and connect to a cluster Structure data in a variety of formats, from serialized objects, a stream of raw bytes, or as JSON documents Learn core storage and retrieval methods, including document IDs, expiry times, and concurrent updates Create views with map/reduce and learn Couchbase mechanisms for querying and selection
Getting Started With Couchbase Server
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Author : Martin C. Brown
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012
Getting Started With Couchbase Server written by Martin C. Brown and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
Do you know what to do if your web application goes viral and usage suddenly explodes? This concise guide introduces you to Couchbase Server, an extremely fast NoSQL database that automatically distributes data across a cluster of commodity servers or virtual machines. You'll learn hands-on how to build a Couchbase cluster without changing your application, and how to expand your database on the fly without interrupting service. Discover how this open source server can help your application gain scalability and performance. Learn how the server's architecture affects the way you build and deploy your database Store data without defining a data structure--and retrieve it without complex queries or query languages Use a formula to estimate your cluster size requirements Set up individual nodes through a browser, command line, or REST API Enable your application to read and write data with sub-millisecond latency through managed object caching Get a quick guide to building applications that integrate Couchbase's core protocol Identify problems in your cluster with the web console Expand or shrink your cluster, handle failovers, and back up data
Machine Learning Systems
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Author : Jeffrey Smith
language : en
Publisher: Simon and Schuster
Release Date : 2018-05-21
Machine Learning Systems written by Jeffrey Smith and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-21 with Computers categories.
Summary Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. Foreword by Sean Owen, Director of Data Science, Cloudera Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology If you’re building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and good user experience, this is the book for you. It collects principles and practices of machine learning systems that are dramatically easier to run and maintain, and that are reliably better for users. About the Book Machine Learning Systems: Designs that scale teaches you to design and implement production-ready ML systems. You'll learn the principles of reactive design as you build pipelines with Spark, create highly scalable services with Akka, and use powerful machine learning libraries like MLib on massive datasets. The examples use the Scala language, but the same ideas and tools work in Java, as well. What's Inside Working with Spark, MLlib, and Akka Reactive design patterns Monitoring and maintaining a large-scale system Futures, actors, and supervision About the Reader Readers need intermediate skills in Java or Scala. No prior machine learning experience is assumed. About the Author Jeff Smith builds powerful machine learning systems. For the past decade, he has been working on building data science applications, teams, and companies as part of various teams in New York, San Francisco, and Hong Kong. He blogs (https: //medium.com/@jeffksmithjr), tweets (@jeffksmithjr), and speaks (www.jeffsmith.tech/speaking) about various aspects of building real-world machine learning systems. Table of Contents PART 1 - FUNDAMENTALS OF REACTIVE MACHINE LEARNING Learning reactive machine learning Using reactive tools PART 2 - BUILDING A REACTIVE MACHINE LEARNING SYSTEM Collecting data Generating features Learning models Evaluating models Publishing models Responding PART 3 - OPERATING A MACHINE LEARNING SYSTEM Delivering Evolving intelligence
Getting Started With Couchbase Server
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Author : MC Brown
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-06-08
Getting Started With Couchbase Server written by MC Brown and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-08 with Computers categories.
Do you know what to do if your web application goes viral and usage suddenly explodes? This concise guide introduces you to Couchbase Server, an extremely fast NoSQL database that automatically distributes data across a cluster of commodity servers or virtual machines. You’ll learn hands-on how to build a Couchbase cluster without changing your application, and how to expand your database on the fly without interrupting service. Discover how this open source server can help your application gain scalability and performance. Learn how the server’s architecture affects the way you build and deploy your database Store data without defining a data structure—and retrieve it without complex queries or query languages Use a formula to estimate your cluster size requirements Set up individual nodes through a browser, command line, or REST API Enable your application to read and write data with sub-millisecond latency through managed object caching Get a quick guide to building applications that integrate Couchbase’s core protocol Identify problems in your cluster with the web console Expand or shrink your cluster, handle failovers, and back up data
Learning Dapr
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Author : Haishi Bai
language : en
Publisher: O'Reilly Media
Release Date : 2020-08-24
Learning Dapr written by Haishi Bai and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-24 with Computers categories.
Get the authoritative guide to Dapr, the distributed application runtime that works with new and existing programming languages alike. Written by the model’s creators, this introduction shows you how Dapr not only unifies stateless, stateful, and actor programming models but also runs everywhere—in the cloud or on the edge. Authors Haishi Bai and Yaron Schneider, both with Microsoft’s Azure CTO team, explain that, with Dapr, you don’t need to include any SDKs or libraries in your user code. Instead, you automatically get flexible binding, state management, the actor pattern, pub-sub, reliable messaging, and many more features. This book shows developers, architects, CIOs, students, and computing enthusiasts how to get started with Dapr. Learn the new programming model for cloud native applications Write high-performance distributed applications without drilling into technical details Use Dapr with any language or framework to write microservices easily Learn how Dapr provides consistency and portability through open APIs and extensible, community-driven components Explore how Dapr handles state, resource bindings, and pub-sub messaging to enable resilient event-driven architectures that scale Integrate cloud applications with various SaaS offerings, such as machine learning
Learning Elastic Stack 6 0
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Author : Pranav Shukla
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-12-22
Learning Elastic Stack 6 0 written by Pranav Shukla and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-22 with Computers categories.
Deliver end-to-end real-time distributed data processing solutions by leveraging the power of Elastic Stack 6.0 Key Features - Get to grips with the new features introduced in Elastic Stack 6.0 - Get valuable insights from your data by working with the different components of the Elastic stack such as Elasticsearch, Logstash, Kibana, X-Pack, and Beats - Includes handy tips and techniques to build, deploy and manage your Elastic applications efficiently on-premise or on the cloud Book Description The Elastic Stack is a powerful combination of tools for distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. After a quick overview of the newly introduced features in Elastic Stack 6.0, you’ll learn how to set up the stack by installing the tools, and see their basic configurations. Then it shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You’ll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments. On completing this book, you’ll have a solid foundational knowledge of the basic Elastic Stack functionalities. You’ll also have a good understanding of the role of each component in the stack to solve different data processing problems. What you will learn - Familiarize yourself with the different components of the Elastic Stack - Get to know the new functionalities introduced in Elastic Stack 6.0 - Effectively build your data pipeline to get data from terabytes or petabytes of data into Elasticsearch and Logstash for searching and logging - Use Kibana to visualize data and tell data stories in real-time - Secure, monitor, and use the alerting and reporting capabilities of Elastic Stack - Take your Elastic application to an on-premise or cloud-based production environment Who this book is for This book is for data professionals who want to get amazing insights and business metrics from their data sources. If you want to get a fundamental understanding of the Elastic Stack for distributed, real-time processing of data, this book will help you. A fundamental knowledge of JSON would be useful, but is not mandatory. No previous experience with the Elastic Stack is required.
Scalable Big Data Architecture
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Author : Bahaaldine Azarmi
language : en
Publisher: Apress
Release Date : 2015-12-31
Scalable Big Data Architecture written by Bahaaldine Azarmi and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-31 with Computers categories.
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.
Learning Pyspark
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Author : Tomasz Drabas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-02-27
Learning Pyspark written by Tomasz Drabas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-27 with Computers categories.
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0 About This Book Learn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0 Develop and deploy efficient, scalable real-time Spark solutions Take your understanding of using Spark with Python to the next level with this jump start guide Who This Book Is For If you are a Python developer who wants to learn about the Apache Spark 2.0 ecosystem, this book is for you. A firm understanding of Python is expected to get the best out of the book. Familiarity with Spark would be useful, but is not mandatory. What You Will Learn Learn about Apache Spark and the Spark 2.0 architecture Build and interact with Spark DataFrames using Spark SQL Learn how to solve graph and deep learning problems using GraphFrames and TensorFrames respectively Read, transform, and understand data and use it to train machine learning models Build machine learning models with MLlib and ML Learn how to submit your applications programmatically using spark-submit Deploy locally built applications to a cluster In Detail Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications. Style and approach This book takes a very comprehensive, step-by-step approach so you understand how the Spark ecosystem can be used with Python to develop efficient, scalable solutions. Every chapter is standalone and written in a very easy-to-understand manner, with a focus on both the hows and the whys of each concept.