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Learning Elasticsearch by Abhishek Andhavarapu Pdf
Store, search, and analyze your data with ease using Elasticsearch 5.x About This Book Get to grips with the basics of Elasticsearch concepts and its APIs, and use them to create efficient applications Create large-scale Elasticsearch clusters and perform analytics using aggregation This comprehensive guide will get you up and running with Elasticsearch 5.x in no time Who This Book Is For If you want to build efficient search and analytics applications using Elasticsearch, this book is for you. It will also benefit developers who have worked with Lucene or Solr before and now want to work with Elasticsearch. No previous knowledge of Elasticsearch is expected. What You Will Learn See how to set up and configure Elasticsearch and Kibana Know how to ingest structured and unstructured data using Elasticsearch Understand how a search engine works and the concepts of relevance and scoring Find out how to query Elasticsearch with a high degree of performance and scalability Improve the user experience by using autocomplete, geolocation queries, and much more See how to slice and dice your data using Elasticsearch aggregations. Grasp how to use Kibana to explore and visualize your data Know how to host on Elastic Cloud and how to use the latest X-Pack features such as Graph and Alerting In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments. Style and approach This comprehensive guide will get you started with Elasticsearch 5.x, so you build a solid understanding of the basics. Every topic is explained in depth and is supplemented with practical examples to enhance your understanding.
Learning Elasticsearch 7.x by Anurag Srivastava Pdf
A step-by-step guide that will teach you how to use Elasticsearch in your application effectively KEY FEATURES ● Get familiar with the core concepts of Elasticsearch. ● Understand how the search engine works and how Elasticsearch is different from other similar tools. ● Learn to install Elasticsearch on different operating systems. ● Get familiar with the components of Elastic Stack such as Kibana, Logstash, and Beats, etc. ● Learn how to import data from different sources such as RDBMS, and files, etc DESCRIPTION In the modern Information Technology age, we are flooded with loads of data so we should know how to handle those data and transform them to fetch meaningful information. This book is here to help you manage the data using Elasticsearch. The book starts by covering the fundamentals of Elasticsearch and the concept behind it. After the introduction, you will learn how to install Elasticsearch on different platforms. You will then get to know about Index Management where you will learn to create, update, and delete Elasticsearch indices. Then you will understand how the Query DSL works and how to write some complex search queries using the Query DSL. After completing these basic features, you will move to some advanced topics. Under advanced topics, you will learn to handle Geodata which can be used to plot the data on a map. The book then focuses on Data Analysis using Aggregation. You will then learn how to tune Elasticsearch performance. The book ends with a chapter on Elasticsearch administration. What you will learn ● Learn how to create and manage a cluster ● Work with different components of Elastic Stack ● Review the list of top Information Security certifications. ● Get to know more about Elasticsearch Index Management. ● Understand how to improve the performance by tuning Elasticsearch WHO THIS BOOK IS FOR This book is for developers, architects, DBA, DevOps, and other readers who want to learn Elasticsearch efficiently and want to apply that in their application whether it is a new one or an existing one. It is also beneficial to those who want to play with their data using Elasticsearch. Basic computer programming is a prerequisite. TABLE OF CONTENTS 1 Getting started with Elasticsearch 2 Installation Elasticsearch 3 Working with Elastic Stack 4 Preparing your data 5 Importing Data into Elasticsearch 6 Managing Your Index 7 Apply Search on Your Data 8 Handling Geo with Elasticsearch 9 Aggregating Your Data 10 Improving the Performance 11 Administer Elasticsearch
Elasticsearch: The Definitive Guide by Clinton Gormley,Zachary Tong Pdf
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
Mastering Elasticsearch by Saravanan Kuppusamy Pdf
Welcome to Mastering Elasticsearch: A Comprehensive Guide. If you're reading this book, it's because you've recognized Elasticsearch's immense potential and are eager to utilize its power for your projects and organization. This guide is designed for data engineers, developers, architects, and anyone seeking to navigate the intricacies of Elasticsearch, empowering you to extract valuable insights from data efficiently. Mastering Elasticsearch serves as your definitive guide to unlocking the full potential of this powerful search engine, known for its versatility in managing modern data. Whether you're a developer, data engineer, or system architect, this book provides the skills to leverage Elasticsearch’s capabilities, giving you a critical edge in search and data analytics. Why Elasticsearch? In today's digital landscape, the sheer volume of data generated every second is staggering. We face the challenge of searching, analyzing, and making sense of this data to deliver actionable insights. Elasticsearch, a cornerstone of the ELK (Elasticsearch, Logstash, Kibana) stack, has emerged as a leading search and analytics engine, renowned for its speed, scalability, and flexibility. It powers systems from full-text search to complex, real-time analytics, handling massive datasets and providing mission-critical support to global organizations. This book takes you on a journey through the vast capabilities of Elasticsearch, from foundational concepts to advanced implementations. Whether you're setting up your first cluster or looking to fine-tune existing deployments, this guide will offer insights tailored to your needs. Foundational Understanding: We'll begin with a robust introduction to Elasticsearch's architecture, terminology, and basic operations. You'll understand how Elasticsearch indexes, searches, and maps data to provide rapid search results. Cluster Architecture: Gain a thorough understanding of Elasticsearch’s distributed architecture, from nodes and shards to clusters, and how these elements work together for horizontal scaling. Indexing Techniques: Learn about creating, managing, and optimizing indices, the cornerstone of Elasticsearch data storage, for efficient search operations. Intermediate Techniques: Building on this foundation, we'll delve into more advanced features such as aggregations, data visualization, and effective index management. We'll discuss geo queries, nested data structures, and how to optimize queries to handle complex data types. Advanced Topics: In the final section, you'll encounter specialized topics like performance tuning, scaling Elasticsearch clusters, and developing custom plugins. We'll explore practical strategies for enhancing security, setting up monitoring, and employing machine learning features to identify patterns and trends in your data. Advanced Querying and Aggregation: Query DSL: Master Elasticsearch’s Query Domain-Specific Language, enabling you to construct sophisticated queries that handle nuanced search requirements with precision. Aggregations: Dive deep into aggregation frameworks that provide powerful tools for real-time analytics, including complex aggregations like nested, scripted, and pipeline. Data Ingestion and Integration: Ingestion Pipelines: Explore ways to seamlessly ingest and transform data with Elasticsearch’s ingest nodes and processors. External Integrations: Implement data ingestion strategies using Logstash, Beats, and other ETL solutions to connect with various data sources. Indexing Strategy: Optimize indexing through sharding, replication, and customized mapping. Caching and Memory: Leverage caching mechanisms and JVM tuning to reduce latency and boost throughput. Security Practices: Implement robust security through authentication, authorization, and encryption to safeguard sensitive data. Monitoring and Troubleshooting: Use Kibana and other tools for real-time monitoring and diagnostics, ensuring high availability and minimizing downtime. Case Studies: Examine case studies that showcase Elasticsearch’s versatility, from e-commerce search solutions to log analytics and beyond. This book aims to cater to both newcomers and seasoned Elasticsearch users. If you're starting out, we'll guide you through initial setup and offer step-by-step instructions to implement core features. Experienced users will find fresh insights, best practices, and advanced techniques to elevate their Elasticsearch knowledge. The book is structured to offer a comprehensive understanding of Elasticsearch while maintaining accessibility. Each chapter provides practical examples, code snippets, and exercises that reinforce key concepts. By working through the examples, you'll gain the confidence to tackle real-world Elasticsearch projects, whether for search, analytics, or application logging. I wrote this guide with the intention of creating a one-stop resource for all things Elasticsearch. With constant evolution in the software and big data landscape, it's essential to stay updated with the latest practices and developments. This guide aims to cover both tried-and-tested fundamentals and emerging trends to ensure you're well-prepared for the challenges ahead. Finally, thank you for choosing this book. I'm thrilled to share my knowledge and insights with you as you begin your journey toward Mastering the Elasticsearch. Let's work together to fully unlock this incredible technology, enabling us to build faster, smarter, and more efficient applications. By the end of Mastering Elasticsearch, you'll have the expertise needed to design, implement, and manage scalable and secure search applications. You'll gain both theoretical understanding and practical insights, enabling you to tailor Elasticsearch to your organization's unique data management needs.
Learning Elastic Stack 7.0 by Pranav Shukla,Sharath Kumar M N Pdf
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.
Master the intricacies of Elasticsearch 7.0 and use it to create flexible and scalable search solutions Key FeaturesMaster the latest distributed search and analytics capabilities of Elasticsearch 7.0Perform searching, indexing, and aggregation of your data at scaleDiscover tips and techniques for speeding up your search query performanceBook Description Building enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks. You'll get started by learning to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of query results and enhancing the customer experience. You'll then get up to speed with performing analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision-makers with better insights. The book will later guide you through using Logstash with examples to collect, parse, and enrich logs before indexing them in Elasticsearch. By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch. What you will learnPre-process documents before indexing in ingest pipelinesLearn how to model your data in the real worldGet to grips with using Elasticsearch for exploratory data analysisUnderstand how to build analytics and RESTful servicesUse Kibana, Logstash, and Beats for dashboard applicationsGet up to speed with Spark and Elasticsearch for real-time analyticsExplore the basics of Spring Data Elasticsearch, and understand how to index, search, and query in a Spring applicationWho this book is for This book is for Elasticsearch developers and data engineers who want to take their basic knowledge of Elasticsearch to the next level and use it to build enterprise-grade distributed search applications. Prior experience of working with Elasticsearch will be useful to get the most out of this book.
Mastering Elasticsearch - Second Edition by Rafał Kuć,Marek Rogoziński Pdf
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.
Learning Advanced Python by Studying Open Source Projects by Rongpeng Li Pdf
This book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and, most importantly, passion. Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python. Throughout this book, readers will learn how to write Python code that is efficient, readable and maintainable, covering key topics such as data structures, algorithms, object-oriented programming and more. The author’s passion for Python shines through in this book, making it an enjoyable and inspiring read for both beginners and experienced programmers.
Machine Learning with the Elastic Stack by Rich Collier,Camilla Montonen,Bahaaldine Azarmi Pdf
Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your data Key FeaturesIntegrate machine learning with distributed search and analyticsPreprocess and analyze large volumes of search data effortlesslyOperationalize machine learning in a scalable, production-worthy wayBook 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 learnFind out how to enable the ML commercial feature in the Elastic StackUnderstand how Elastic machine learning is used to detect different types of anomalies and make predictionsApply effective anomaly detection to IT operations, security analytics, and other use casesUtilize the results of Elastic ML in custom views, dashboards, and proactive alertingTrain and deploy supervised machine learning models for real-time inferenceDiscover various tips and tricks to get the most out of Elastic machine learningWho 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.
Machine Learning with the Elastic Stack - Second Edition by Rich Collier,Camilla Montonen,Bahaaldine Azarmi Pdf
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.
Learning Elastic Stack 6.0 by Pranav Shukla,Sharath Kumar M N Pdf
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.
Machine Learning with the Elastic Stack by Rich Collier,Bahaaldine Azarmi Pdf
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.
Elasticsearch in Action, Second Edition by Madhusudhan Konda Pdf
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
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
Elasticsearch in Action, Second Edition by Madhusudhan Konda Pdf
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. 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