Indexing Data in Elasticsearch from Pluralsight

This course explains the index distribution architecture of Elasticsearch, cluster configuration, shards and replicas, similarity models, advanced search, and mixed-language documents, all of which improve the performance of search queries.

Getting Elasticsearch up and running is very simple, but tuning it to have low latency and high performance for search queries requires a deep understanding of the index distribution architecture. In this course, Indexing Data in Elasticsearch, you will understand the structure of distributed indices and advanced search constructs such as similarity models, segment merging, suggesters, fuzzy searches and working with mixed-language documents. First, you will study why shard overallocation is a good thing and how you can configure your cluster to avoid the split-brain scenario. Then, you will see how indices can be configured to use different similarity models and how to use force merging of segments to improve the performance of large indices. Next, you will explore how to cache prudently and use advanced search features. Finally, you will learn to deal with different languages in the same document with the ICU plugin. At the end of this course, you will have a deep understanding of how indexing works in Elasticsearch and be comfortable with advanced query constructs.

What's inside

Syllabus

Course Overview

Introducing the Index Distribution Architecture

Executing Low-level Index Control

Improving the User Search Experience

Dealing with Human Languages

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches configuration, administration, and design of Elasticsearch clusters

Instructors Janani Ravi have experience with Elasticsearch

Covers advanced concepts such as shard overallocation, query caching, and mixed-language documents

Develops skills in indexing, searching, and managing large-scale Elasticsearch clusters for high performance

Emphasizes performance optimization and tuning techniques for Elasticsearch deployments

Requires a basic understanding of Elasticsearch and some experience with data modeling and querying

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Indexing Data in Elasticsearch with these activities:

Review Course Materials

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Review the course materials before each class to prepare for the upcoming topics and discussions.

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Read assigned readings and watch videos
Take notes and highlight key concepts
Review lecture slides and handouts

Review ElasticSearch Concepts

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Review core ElasticSearch concepts before class to ensure you have a strong foundation in the fundamentals.

Browse courses on Elasticsearch

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Review ElasticSearch documentation and tutorials
Complete ElasticSearch online courses or workshops

Practice Creating ElasticSearch Indices

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Creating indices is a fundamental skill in ElasticSearch. Practice this skill to improve your understanding and proficiency.

Browse courses on Elasticsearch

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Create indices with different settings and configurations
Practice indexing documents into different indices
Query and retrieve documents from indices

Five other activities

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Form a Study Group

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Forming a study group will provide you with a support system, enhance your understanding through discussions, and help you stay accountable.

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Find a group of classmates with similar interests
Set regular meeting times and locations
Discuss course materials, work on assignments together, and prepare for exams

Follow ElasticSearch Best Practices

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ElasticSearch has a wealth of best practices to optimize performance and reliability. Learn and apply these best practices to enhance your ElasticSearch implementation.

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Read ElasticSearch documentation on best practices
Follow ElasticSearch community forums and discussions
Attend ElasticSearch webinars and meetups

Create an ElasticSearch Cluster

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Deploying an ElasticSearch cluster is a valuable hands-on experience that will deepen your understanding of ElasticSearch architecture and operations.

Browse courses on Elasticsearch

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Install ElasticSearch on multiple servers
Configure and manage the ElasticSearch cluster
Monitor and troubleshoot the cluster

Attend ElasticSearch Workshops

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ElasticSearch workshops provide hands-on training and expert insights that can significantly enhance your ElasticSearch skills.

Browse courses on Elasticsearch

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Find and register for ElasticSearch workshops
Attend the workshops and actively participate
Apply the knowledge and skills gained in your ElasticSearch projects

Participate in ElasticSearch Competitions

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ElasticSearch competitions provide a challenging and rewarding way to test your skills and learn from others in the ElasticSearch community.

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Find and register for ElasticSearch competitions
Develop solutions using ElasticSearch
Submit your solutions and compete with others

Career center

Learners who complete Indexing Data in Elasticsearch will develop knowledge and skills that may be useful to these careers:

Search Engineer

A Search Engineer builds and maintains search engines. The skillset required for this role overlaps with Indexing Data in Elasticsearch, which teaches the advanced concepts of indexing and search.

See salaries and explore the career path for Search Engineer

Data Engineer

A Data Engineer designs and builds data management systems for storage, security, and accessibility. Indexing Data in Elasticsearch can support this work by providing skills in distributed index design, shard and replica configurations, and more.

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Database Architect

A Database Architect designs and manages database systems to meet the needs of an organization. Database Architects must have a deep understanding of data indexing and retrieval, which makes Indexing Data in Elasticsearch an excellent course for gaining these skills.

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Solutions Architect

A Solutions Architect designs and implements technical solutions for businesses to meet their business needs. The topics covered in Indexing Data in Elasticsearch, such as search optimization and data retrieval, are highly relevant to this role.

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IT Architect

An IT Architect designs and implements technology solutions for businesses. Indexing Data in Elasticsearch teaches concepts and tools used in IT architecture tasks, such as search engine optimization and data retrieval.

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Technical Architect

A Technical Architect designs and implements technology solutions for businesses. Extensive knowledge of data retrieval and indexing is essential for Technical Architects, making Indexing Data in Elasticsearch highly relevant.

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Enterprise Architect

An Enterprise Architect designs and implements technology solutions to meet the business needs of a large organization. The knowledge gained in Indexing Data in Elasticsearch can be useful for an Enterprise Architect, as it teaches skills for efficient data indexing and retrieval.

See salaries and explore the career path for Enterprise Architect

Data Scientist

A Data Scientist analyzes large datasets to extract insights and patterns. The knowledge gained in Indexing Data in Elasticsearch can be useful for a Data Scientist, as it teaches skills for efficient data indexing and retrieval.

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Business Analyst

A Business Analyst gathers and interprets data to identify opportunities for improvement within a business. The knowledge gained in Indexing Data in Elasticsearch can be useful for a Business Analyst, as it teaches skills for efficient data indexing and retrieval.

See salaries and explore the career path for Business Analyst

Data Analyst

A Data Analyst collects, analyzes, and interprets data to provide insights for decision-making. The knowledge gained in Indexing Data in Elasticsearch can be useful for a Data Analyst, as it teaches skills for efficient data indexing and retrieval.

See salaries and explore the career path for Data Analyst

Database Administrator

A Database Administrator is a computer professional who handles the design, implementation, and maintenance of database management systems. The knowledge gained in Indexing Data in Elasticsearch can be useful for a Database Administrator, as it teaches skills for efficient data indexing and retrieval.

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DevOps Engineer

A DevOps Engineer builds and maintains the infrastructure and tools that software development teams use to build and deploy software. The knowledge gained in Indexing Data in Elasticsearch can be useful for a DevOps Engineer, as it teaches skills for data storage and retrieval that are essential for software development.

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Systems Analyst

A Systems Analyst analyzes, designs, and implements information systems. The knowledge gained in Indexing Data in Elasticsearch can be useful for a Systems Analyst, as it teaches skills for efficient data indexing and retrieval.

See salaries and explore the career path for Systems Analyst

Information Architect

An Information Architect designs and organizes information within an application or website. This course, Indexing Data in Elasticsearch, may be helpful in developing your knowledge of the indexing distribution architecture, similarity models, and more, which can provide practical assistance in an information architecture role.

See salaries and explore the career path for Information Architect

Software Developer

A Software Developer builds and designs software programs and applications. This course, Indexing Data in Elasticsearch, may be useful in cultivating your skills, as it provides deep knowledge and expertise in the indexing architecture of Elasticsearch, which can be practical in a software development context.

See salaries and explore the career path for Software Developer

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Indexing Data in Elasticsearch.

Elasticsearch: The Definitive Guide

Save

Provides a comprehensive guide to Elasticsearch, covering topics such as index distribution architecture, cluster configuration, shards and replicas, similarity models, and advanced search. It valuable resource for anyone who wants to learn more about Elasticsearch and how to use it effectively.

Elasticsearch: The Definitive Guide: A Distributed...

Paperback

Elasticsearch: The Definitive Guide: A Distributed...

Kindle Edition

Elasticsearch in Action

Save

Provides a practical guide to Elasticsearch, with a focus on real-world use cases. It covers topics such as data ingestion, indexing, searching, and analytics. It valuable resource for anyone who wants to learn how to use Elasticsearch to solve real-world problems.

Elasticsearch in Action

Kindle Edition

Developing Blockchain Solutions in the Cloud

Save

Comprehensive guide to using Elasticsearch in real-world scenarios. It valuable resource for anyone who wants to learn how to use Elasticsearch effectively.

Developing Blockchain Solutions in the Cloud:...

Kindle Edition

Elasticsearch in Action

Save

Practical guide to Elasticsearch, with a focus on real-world examples. It good choice for anyone who wants to learn how to use Elasticsearch effectively.

Elasticsearch in Action

Paperback

Check price

Elasticsearch in Action

Kindle Edition

Check price

Lucene in Action

Save

Provides a comprehensive guide to Apache Lucene, the open-source search engine library that is used by Elasticsearch. It valuable resource for anyone who wants to learn more about the internals of Elasticsearch and how to use it effectively.

Lucene in Action, Second Edition: Covers Apache...

Paperback

Lucene in Action

Kindle Edition