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- Advanced Elasticsearch 7.0. A practical guide to designing, indexing, and querying advanced distributed search engines
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Advanced Elasticsearch 7.0. A practical guide to designing, indexing, and querying advanced distributed search engines
Ebook
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.
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.
- 1. Overview of Elasticsearch 7
- 2. Index APIs
- 3. Document APIs
- 4. Mapping APIs
- 5. Anatomy of an Analyzer
- 6. Search APIs
- 7. Modeling Your Data in the Real World
- 8. Aggregations Frameworks
- 9. Preprocessing Documents in Ingest Pipelines
- 10. Using ElasticSearch for Exploratory Data Analysis
- 11. Elasticsearch from Java Programming
- 12. Elasticsearch from Python Programming
- 13. Using Kibana, Logstash and Beats
- 14. Working with Elasticsearch SQL
- 15. Working with Elasticsearch Analysis Plugins
- 16. Machine Learning with Elasticsearch
- 17. Spark and Elasticsearch for Real-Time Analytics
- 18. Building Analytics RESTful Services
- Title: Advanced Elasticsearch 7.0. A practical guide to designing, indexing, and querying advanced distributed search engines
- Author: Wai Tak Wong
- Original title: Advanced Elasticsearch 7.0. A practical guide to designing, indexing, and querying advanced distributed search engines
- ISBN: 9781789956566, 9781789956566
- Date of issue: 2019-08-23
- Format: Ebook
- Item ID: e_2ax6
- Publisher: Packt Publishing