Over 130 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with ElasticSearch
About This Book
- Deploy and manage simple ElasticSearch nodes as well as complex cluster topologies
- Write native plugins to extend the functionalities of ElasticSearch to boost your business
- Packed with clear, step-by-step recipes to walk you through the capabilities of ElasticSearch
Who This Book Is For
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.
What You Will Learn
- Make ElasticSearch work for you by choosing the best cloud topology and powering it with plugins
- Develop tailored mapping to take full control of index steps
- Build complex queries through managing indices and documents
- Optimize search results through executing analytics aggregations
- Manage rivers (SQL, NoSQL, and web-based) to synchronize and populate cross-source data
- Develop web interfaces to execute key tasks
- Monitor the performance of the cluster and nodes
In Detail
This book will guide you through the complete ElasticSearch ecosystem. From choosing the correct transport layer and communicating with the server to creating and customizing internal actions, you will develop an in-depth knowledge of the implementation of the ElasticSearch architecture.
After creating complex queries and analytics, mapping, aggregation, and scripting, you will master the integration of ElasticSearch's functionality in user-facing applications and take your knowledge one-step further by building custom plugins, developing tailored mapping, executing powerful analytics, and integrating with Python and Java applications.
Alberto Paro
Alberto Paro is an engineer, project manager, and software developer. He currently works as a CTO at Big Data Technologies and as a freelance consultant on software engineering for Big Data 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 8 years old, and to date, has collected a lot of experience using different operating systems, applications, and programming. In 2000, he graduated in computer science engineering at 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 currently works 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, and ElasticSearch. 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-MongoDB-engine). 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 Elasticsearch Server, Second Edition, and the video course, Building a Search Server with ElasticSearch, all of which are published by Packt Publishing.
