Elasticsearch 5.x Cookbook - Third Edition oleh Alberto Paro

Key FeaturesDeploy and manage simple Elasticsearch nodes as well as complex cluster topologiesWrite native plugins to extend the functionalities of Elasticsearch 5.x to boost your businessPacked with clear, step-by-step recipes to walk you through the capabilities of Elasticsearch 5.xBook DescriptionElasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem.Well guide you through comprehensive recipes on whats new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index.You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins.By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch.What you will learnChoose the best Elasticsearch cloud topology to deploy and power it up with external pluginsDevelop tailored mapping to take full control of index stepsBuild complex queries through managing indices and documentsOptimize search results through executing analytics aggregationsMonitor the performance of the cluster and nodesInstall Kibana to monitor cluster and extend Kibana for pluginsIntegrate Elasticsearch in Java, Scala, Python and Big Data applicationsAbout the AuthorAlberto Paro is an engineer, project manager, and software developer. He currently works as freelance trainer/consultant on big data technologies and NoSQL solutions. He loves to study emerging solutions and applications mainly related to big data processing, NoSQL, natural language processing, and neural networks. He began programming in BASIC on a Sinclair Spectrum when he was eight years old, and to date, has collected a lot of experience using different operating systems, applications, and programming languages.In 2000, he graduated in computer science engineering from Politecnico di Milano with a thesis on designing multiuser and multidevice web applications. He assisted professors at the university for about a year. He then came in contact with The Net Planet Company and loved their innovative ideas; he started working on knowledge management solutions and advanced data mining products. In summer 2014, his company was acquired by a big data technologies company, where he worked until the end of 2015 mainly using Scala and Python on state-of-the-art big data software (Spark, Akka, Cassandra, and YARN). In 2013, he started freelancing as a consultant for big data, machine learning, Elasticsearch and other NoSQL products. He has created or helped to develop big data solutions for business intelligence, financial, and banking companies all over the world. A lot of his time is spent teaching how to efficiently use big data solutions (mainly Apache Spark), NoSql datastores (Elasticsearch, HBase, and Accumulo) and related technologies (Scala, Akka, and Playframework). He is often called to present at big data or Scala events. He is an evangelist on Scala and Scala.js (the transcompiler from Scala to JavaScript).In his spare time, when he is not playing with his children, he likes to work on open source projects. When he was in high school, he started contributing to projects related to the GNOME environment (gtkmm). One of his preferred programming languages is Python, and he wrote one of the first NoSQL backends on Django for MongoDB (Django-MongoDBengine). In 2010, he began using Elasticsearch to provide search capabilities to some Django e-commerce sites and developed PyES (a Pythonic client for Elasticsearch), as well as the initial part of the Elasticsearch MongoDB river. He is the author of Elasticsearch Cookbook as well as a technical reviewer of Elasticsearch Server-Second Edition, Learning Scala Web Development, and the video course, Building a Search Server with Elasticsearch, all of which are published by Packt Publishing.Table of ContentsGetting StartedDownloading and SetupManaging MappingsBasic OperationsSearchText and Numeric QueriesRelationships and Geo QueriesAggregationsScriptingManaging Clusters and NodesBackup and RestoreUser InterfacesIngestJava IntegrationScala IntegrationPython IntegrationPlugin DevelopmentBig Data Integration