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Advanced Elasticsearch 7.0

Advanced Elasticsearch 7.0

By : Wong
3.5 (4)
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Advanced Elasticsearch 7.0

Advanced Elasticsearch 7.0

3.5 (4)
By: Wong

Overview of this book

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.
Table of Contents (25 chapters)
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1
Section 1: Fundamentals and Core APIs
8
Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
13
Section 3: Programming with the Elasticsearch Client
16
Section 4: Elastic Stack
20
Section 5: Advanced Features

Refreshing mapping changes for static mapping

In Chapter 3, Document APIs, we introduced the Update by Query API for documents and also for static mappings. If static mapping is used, any fields not specified in the mappings will not be indexed and searchable; however, they are stored in _source. If we need to search for a non-mapping field later, we only need to update the static mappings to make the indexed documents take effect of the changes. No document reindexing step is required. Assume that the original mappings for our sample documents do not have the exchange field, that the document has been indexed, and that we now want it to be searchable:

  1. First, we need to update the mapping, as shown in the following screenshot:
  1. The next step is to issue an Update by Query request to take the static mapping changes into effect, as shown in the following screenshot:

In the...

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