ElasticSearch Cookbook - Second Edition

ElasticSearch Cookbook - Second Edition
Author: Alberto Paro
Publisher: Packt Publishing Ltd
Total Pages: 472
Release: 2015-01-28
Genre: Computers
ISBN: 1783554843

If you are a developer who implements ElasticSearch in your web applications and want to sharpen your understanding of the core elements and applications, this is the book for you. It is assumed that you’ve got working knowledge of JSON and, if you want to extend ElasticSearch, of Java and related technologies.

ElasticSearch Cookbook

ElasticSearch Cookbook
Author: Alberto Paro
Publisher: Packt Publishing Ltd
Total Pages: 671
Release: 2013-12-24
Genre: Computers
ISBN: 1782166637

Written in an engaging, easy-to-follow style, the recipes will help you to extend the capabilities of ElasticSearch to manage your data effectively. If you are a developer who implements ElasticSearch in your web applications, manage data, or have decided to start using ElasticSearch, this book is ideal for you. This book assumes that you’ve got working knowledge of JSON and Java

Mastering Elasticsearch - Second Edition

Mastering Elasticsearch - Second Edition
Author: Rafał Kuć
Publisher: Packt Publishing Ltd
Total Pages: 434
Release: 2015-02-27
Genre: Computers
ISBN: 1783553804

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.

Elasticsearch in Action, Second Edition

Elasticsearch in Action, Second Edition
Author: Madhusudhan Konda
Publisher: Simon and Schuster
Total Pages: 590
Release: 2023-10-31
Genre: Computers
ISBN: 1617299855

Build powerful, production-ready search applications using the incredible features of Elasticsearch. In Elasticsearch in Action, Second Edition you will discover: Architecture, concepts, and fundamentals of Elasticsearch Installing, configuring, and running Elasticsearch and Kibana Creating an index with custom settings Data types, mapping fundamentals, and templates Fundamentals of text analysis and working with text analyzers Indexing, deleting, and updating documents Indexing data in bulk, and reindexing and aliasing operations Learning search concepts, relevancy scores, and similarity algorithms Elasticsearch in Action, Second Edition teaches you to build scalable search applications using Elasticsearch. This completely new edition explores Elasticsearch fundamentals from the ground up. You’ll deep dive into design principles, search architectures, and Elasticsearch’s essential APIs. Every chapter is clearly illustrated with diagrams and hands-on examples. You’ll even explore real-world use cases for full text search, data visualizations, and machine learning. Plus, its comprehensive nature means you’ll keep coming back to the book as a handy reference! Foreword by Shay Banon. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Create fully professional-grade search engines with Elasticsearch and Kibana! Rewritten for the latest version of Elasticsearch, this practical book explores Elasticsearch’s high-level architecture, reveals infrastructure patterns, and walks through the search and analytics capabilities of numerous Elasticsearch APIs. About the book Elasticsearch in Action, Second Edition teaches you how to add modern search features to websites and applications using Elasticsearch 8. In it, you’ll quickly progress from the basics of installation and configuring clusters, to indexing documents, advanced aggregations, and putting your servers into production. You’ll especially appreciate the mix of technical detail with techniques for designing great search experiences. What's inside Understanding search architecture Full text and term-level search queries Analytics and aggregations High-level visualizations in Kibana Configure, scale, and tune clusters About the reader For application developers comfortable with scripting and command-line applications. About the author Madhusudhan Konda is a full-stack lead engineer, architect, mentor, and conference speaker. He delivers live online training on Elasticsearch and the Elastic Stack. Table of Contents 1 Overview 2 Getting started 3 Architecture 4 Mapping 5 Working with documents 6 Indexing operations 7 Text analysis 8 Introducing search 9 Term-level search 10 Full-text searches 11 Compound queries 12 Advanced search 13 Aggregations 14 Administration 15 Performance and troubleshooting

Elasticsearch: The Definitive Guide

Elasticsearch: The Definitive Guide
Author: Clinton Gormley
Publisher: "O'Reilly Media, Inc."
Total Pages: 659
Release: 2015-01-23
Genre: Computers
ISBN: 1449358500

Whether you need full-text search or real-time analytics of structured data—or both—the Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships. If you’re a newcomer to both search and distributed systems, you’ll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you’ll follow a problem-based approach to learn why, when, and how to use Elasticsearch features. Understand how Elasticsearch interprets data in your documents Index and query your data to take advantage of search concepts such as relevance and word proximity Handle human language through the effective use of analyzers and queries Summarize and group data to show overall trends, with aggregations and analytics Use geo-points and geo-shapes—Elasticsearch’s approaches to geolocation Model your data to take advantage of Elasticsearch’s horizontal scalability Learn how to configure and monitor your cluster in production

Elasticsearch in Action

Elasticsearch in Action
Author: Roy Russo
Publisher: Simon and Schuster
Total Pages: 702
Release: 2015-11-17
Genre: Computers
ISBN: 1638353190

Summary Elasticsearch in Action teaches you how to build scalable search applications using Elasticsearch. You'll ramp up fast, with an informative overview and an engaging introductory example. Within the first few chapters, you'll pick up the core concepts you need to implement basic searches and efficient indexing. With the fundamentals well in hand, you'll go on to gain an organized view of how to optimize your design. Perfect for developers and administrators building and managing search-oriented applications. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Modern search seems like magic—you type a few words and the search engine appears to know what you want. With the Elasticsearch real-time search and analytics engine, you can give your users this magical experience without having to do complex low-level programming or understand advanced data science algorithms. You just install it, tweak it, and get on with your work. About the Book Elasticsearch in Action teaches you how to write applications that deliver professional quality search. As you read, you'll learn to add basic search features to any application, enhance search results with predictive analysis and relevancy ranking, and use saved data from prior searches to give users a custom experience. This practical book focuses on Elasticsearch's REST API via HTTP. Code snippets are written mostly in bash using cURL, so they're easily translatable to other languages. What's Inside What is a great search application? Building scalable search solutions Using Elasticsearch with any language Configuration and tuning About the Reader For developers and administrators building and managing search-oriented applications. About the Authors Radu Gheorghe is a search consultant and software engineer. Matthew Lee Hinman develops highly available, cloud-based systems. Roy Russo is a specialist in predictive analytics. Table of Contents PART 1 CORE ELASTICSEARCH FUNCTIONALITY Introducing Elasticsearch Diving into the functionality Indexing, updating, and deleting data Searching your data Analyzing your data Searching with relevancy Exploring your data with aggregations Relations among documents PART 2 ADVANCED ELASTICSEARCH FUNCTIONALITY Scaling out Improving performance Administering your cluster

Learning Elastic Stack 7.0

Learning Elastic Stack 7.0
Author: Pranav Shukla
Publisher: Packt Publishing Ltd
Total Pages: 461
Release: 2019-05-31
Genre: Computers
ISBN: 1789958539

A beginner's guide to storing, managing, and analyzing data with the updated features of Elastic 7.0 Key FeaturesGain access to new features and updates introduced in Elastic Stack 7.0Grasp the fundamentals of Elastic Stack including Elasticsearch, Logstash, and KibanaExplore useful tips for using Elastic Cloud and deploying Elastic Stack in production environmentsBook Description The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. This book will give you a fundamental understanding of what the stack is all about, and help you use it efficiently to build powerful real-time data processing applications. The first few sections of the book will help you understand how to set up the stack by installing tools, and exploring their basic configurations. You’ll then get up to speed with using Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for data visualization. As you work through the book, you will discover the technique of creating custom plugins using Kibana and Beats. This is followed by coverage of the Elastic X-Pack, a useful extension for effective security and monitoring. You’ll also find helpful tips on how to use Elastic Cloud and deploy Elastic Stack in production environments. By the end of this book, you’ll be well versed with the fundamental Elastic Stack functionalities and the role of each component in the stack to solve different data processing problems. What you will learnInstall and configure an Elasticsearch architectureSolve the full-text search problem with ElasticsearchDiscover powerful analytics capabilities through aggregations using ElasticsearchBuild a data pipeline to transfer data from a variety of sources into Elasticsearch for analysisCreate interactive dashboards for effective storytelling with your data using KibanaLearn how to secure, monitor and use Elastic Stack’s alerting and reporting capabilitiesTake applications to an on-premise or cloud-based production environment with Elastic StackWho this book is for This book is for entry-level data professionals, software engineers, e-commerce developers, and full-stack developers who want to learn about Elastic Stack and how the real-time processing and search engine works for business analytics and enterprise search applications. Previous experience with Elastic Stack is not required, however knowledge of data warehousing and database concepts will be helpful.

Machine Learning with the Elastic Stack

Machine Learning with the Elastic Stack
Author: Rich Collier
Publisher: Packt Publishing Ltd
Total Pages: 299
Release: 2019-01-31
Genre: Computers
ISBN: 1788471776

Leverage Elastic Stack’s machine learning features to gain valuable insight from your data Key FeaturesCombine machine learning with the analytic capabilities of Elastic StackAnalyze large volumes of search data and gain actionable insight from themUse external analytical tools with your Elastic Stack to improve its performanceBook Description Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure. By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly. What you will learnInstall the Elastic Stack to use machine learning featuresUnderstand how Elastic machine learning is used to detect a variety of anomaly typesApply effective anomaly detection to IT operations and security analyticsLeverage the output of Elastic machine learning in custom views, dashboards, and proactive alertingCombine your created jobs to correlate anomalies of different layers of infrastructureLearn various tips and tricks to get the most out of Elastic machine learningWho this book is for If you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.

Relevant Search

Relevant Search
Author: John Berryman
Publisher: Simon and Schuster
Total Pages: 517
Release: 2016-06-19
Genre: Computers
ISBN: 1638353611

Summary Relevant Search demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Users are accustomed to and expect instant, relevant search results. To achieve this, you must master the search engine. Yet for many developers, relevance ranking is mysterious or confusing. About the Book Relevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime. What's Inside Techniques for debugging relevance? Applying search engine features to real problems? Using the user interface to guide searchers? A systematic approach to relevance? A business culture focused on improving search About the Reader For developers trying to build smarter search with Elasticsearch or Solr. About the Authors Doug Turnbull is lead relevance consultant at OpenSource Connections, where he frequently speaks and blogs. John Berryman is a data engineer at Eventbrite, where he specializes in recommendations and search. Foreword author, Trey Grainger, is a director of engineering at CareerBuilder and author of Solr in Action. Table of Contents The search relevance problem Search under the hood Debugging your first relevance problem Taming tokens Basic multifield search Term-centric search Shaping the relevance function Providing relevance feedback Designing a relevance-focused search application The relevance-centered enterprise Semantic and personalized search

Machine Learning with the Elastic Stack - Second Edition

Machine Learning with the Elastic Stack - Second Edition
Author: Rich Collier
Publisher:
Total Pages: 450
Release: 2021-05-28
Genre:
ISBN: 9781801070034

Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your data Key Features: Integrate machine learning with distributed search and analytics Preprocess and analyze large volumes of search data effortlessly Operationalize machine learning in a scalable, production-worthy way Book Description: Elastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively. With the addition of machine learning, a key commercial feature, the Elastic Stack makes this process even more efficient. This updated second edition of Machine Learning with the Elastic Stack provides a comprehensive overview of Elastic Stack's machine learning features for both time series data analysis as well as for classification, regression, and outlier detection. The book starts by explaining machine learning concepts in an intuitive way. You'll then perform time series analysis on different types of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you'll deploy machine learning within Elastic Stack for logging, security, and metrics. Finally, you'll discover how data frame analysis opens up a whole new set of use cases that machine learning can help you with. By the end of this Elastic Stack book, you'll have hands-on machine learning and Elastic Stack experience, along with the knowledge you need to incorporate machine learning in your distributed search and data analysis platform. What You Will Learn: Find out how to enable the ML commercial feature in the Elastic Stack Understand how Elastic machine learning is used to detect different types of anomalies and make predictions Apply effective anomaly detection to IT operations, security analytics, and other use cases Utilize the results of Elastic ML in custom views, dashboards, and proactive alerting Train and deploy supervised machine learning models for real-time inference Discover various tips and tricks to get the most out of Elastic machine learning Who this book is for: If you're a data professional looking to gain insights into Elasticsearch data without having to rely on a machine learning specialist or custom development, then this Elastic Stack machine learning book is for you. You'll also find this book useful if you want to integrate machine learning with your observability, security, and analytics applications. Working knowledge of the Elastic Stack is needed to get the most out of this book.