Watch Learning Elasticsearch 5.0

Name: Learning Elasticsearch 5.0
Released: 2017-01-23
Cast: Ethan Anthony

2017
1 Season

Learning Elasticsearch 5.0 is a valuable resource for anyone looking to enhance their understanding of Elasticsearch, an open-source search engine that enables users to search and analyze massive amounts of data. The show is hosted and presented by Ethan Anthony, a renowned expert and instructor in Elasticsearch, and is published by Packt Publishing, a reputable educational platform for software developers.

Ethan Anthony breaks down Elasticsearch 5.0 into digestible parts, with each part building upon the last. The show offers a comprehensive overview of Elasticsearch 5.0, starting with the basics, and gradually delving into more advanced topics. Ethan Anthony's clear and concise explanations make the show accessible to both beginners and experienced Elasticsearch users.

The show is packed with demonstrations that illustrate the practical applications of Elasticsearch 5.0. Ethan Anthony provides real-world examples that show how Elasticsearch can be used to solve problems, enhance search functions, and improve data analysis in various industries. This makes the show invaluable to anyone looking to gain a practical understanding of how Elasticsearch can be implemented in their work.

The show is well-structured, with each episode covering a specific topic. Ethan Anthony begins with an introduction to the show, Elasticsearch, and its uses. He goes on to explain how to install Elasticsearch, set it up, and configure it. The series then progresses to more advanced topics, such as working with indices, querying data, and analyzing data in Elasticsearch.

Throughout the show, Ethan Anthony emphasizes best practices and gives tips on how to optimize Elasticsearch for specific use cases. He demonstrates how to leverage Elasticsearch's strengths to build powerful, scalable, and efficient systems for search and data analysis.

One of the unique features of Learning Elasticsearch 5.0 is the focus on Elasticsearch plugins. Ethan Anthony dedicates some episodes to specific Elasticsearch plugins that can extend its functionality. He explains how to install and use these plugins and their applications in various use cases.

The show is designed to be interactive, with plenty of opportunities for viewers to follow along and implement what they learn. Ethan Anthony provides code snippets and examples that viewers can copy and use to practice. This ensures that viewers can develop a hands-on understanding of Elasticsearch 5.0.

Learning Elasticsearch 5.0 is suitable for a wide range of audiences, including developers, system administrators, data analysts, and search professionals. The show offers a foundation for anyone looking to get started with Elasticsearch, as well as providing valuable insights for experienced users.

In summary, Learning Elasticsearch 5.0 from Packt Publishing starring Ethan Anthony is an exceptional resource for anyone looking to enhance their understanding and skills in Elasticsearch. The show covers a wide range of topics, from the basics to advanced features, and is delivered in a clear and concise manner. The emphasis on real-world applications and best practices makes the show invaluable to anyone looking to implement Elasticsearch in their work.

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Seasons

35. Choosing between ElasticSearch and Apache Solr

January 23, 2017

ElasticSearch isn't the only high-octane text search engine in existence. Understanding a competing technology helps to identify where ElasticSearch stands.

34. Getting into Synonyms

January 23, 2017

User generated queries for text search can be filled with colloquialism, abbreviations etc. Synonyms in ElasticSearch aim to help minimize this challenge.

33. Geo Searching

January 23, 2017

The ability to query Geo data highly ranks in modern use cases. ElasticSearch simplifies the process of geo searching.

31. Running Log Analysis

January 23, 2017

It's not enough to know the steps to the log analysis process. Practical experience is also necessary for true understanding.

30. Preparing for Log Analysis

January 23, 2017

Log analysis is a multi-step process that requires attention to detail. Clear understanding of the process is essential.

29. Beats

January 23, 2017

The complexity of moving data from external systems to ElasticSearch presents many challenges. Beats was created to simplify the process of moving data into ElasticSearch.

28. X-Pack

January 23, 2017

Prior to ElasticSearch 5.0, security, monitoring, alerting, reporting, graph and so on. were all separate components. Version 5.0 combined these to form X-Pack.

27. Logstash

January 23, 2017

Log analysis is an involved process that moves unstructured log data into the ElasticSearch cluster. Logstash was created for this very reason.

26. Kibana

January 23, 2017

Data aggregation is the first of many steps in the analysis process. Kibana facilitates data visualization and acts as a cluster management interface.

24. Myths about ElasticSearch

January 23, 2017

Not understanding the intended use of a technology can lead to bad implementations or even worse. It is imperative to understand what ElasticSearch is not designed for.

22. Aggregation Based Analytics

January 23, 2017

Generating analytics can be a challenging task. Built-in aggregation based analytics in ElasticSearch take the pain out of analytics.

21. Exist Query

January 23, 2017

At times you will need to know when a given field exists. This is when you should turn to exist queries.

20. Range Query

January 23, 2017

Sometimes you will want to search a range of values. Range queries are the solution to this challenge.

19. Term Queries and Boosting

January 23, 2017

Understanding the type of queries required to gain optimal results is necessary in ElasticSearch. Knowledge of term queries and boosting helps to optimize query results.

18. Understanding DSL

January 23, 2017

Moving beyond the basics in DSL can be challenging. Going beyond the basic to take a deeper look into DSL helps.

15. Using REST API to Search

January 23, 2017

Using REST API requires knowledge of how to run desired queries. Hands-on experience makes this possible.

14. Introduction to REST API

January 23, 2017

Interfacing with technology from external systems can be challenging and often requires a high degree of expertise. The REST API in ElasticSearch solves this problem.

13. Using Bulk API

January 23, 2017

Since adding documents is among the most commonly performed tasks in ElasticSearch, there needs to be a way to add multiple documents simultaneously. The bulk API solves this problem.

12. Adding and Deleting Documents

January 23, 2017

Document addition and deletion in ElasticSearch controls the flow of data. The ability to add and delete documents in ElasticSearch is necessary.

11. Adding and Deleting an Index

January 23, 2017

Index and Mapping set the stage for data search and analysis. Knowledge of how each work is important for effective ElasticSearch usage.

10. Setting Shards and Replicas

January 23, 2017

Distributed technology is extremely challenging to understand. Understanding how to set shards and replicas in ElasticSearch is therefore a necessary first step.

9. What Is a Cluster?

January 23, 2017

The concept of a cluster can be broad and sometimes confusing. Understanding an ElasticSearch cluster is an important step in the learning process.

8. Documents in ElasticSearch

January 23, 2017

Documents hold data in ElasticSearch. Understanding the workings of documents put one on the path to better understanding ElasticSearch.

7. What Is an Index?

January 23, 2017

The indices are easily the cornerstone of ElasticSearch. As such, understanding indices and how they work is key.

5. What's New in Version 5.0?

January 23, 2017

Version 5.0 of ElasticSearch has some key changes. Highlighting these changes help developers to get a better understanding of what's new.

4. Goal of ElasticSearch

January 23, 2017

Before diving into any new technology, it is all too important to understand what the subject technology was designed for and the best use cases. Peering into the objectives of ElasticSearch solves this.

3. Installing ElasticSearch

January 23, 2017

Setting up a new technology is often a challenging affair. By walking through the simple process of installing ElasticSearch, developers can quickly move along the learning process.

2. What Is ElasticSearch?

January 23, 2017

Gaining a holistic view of a new technology is the first necessary step to learning how it works. ElasticSearch is introduced with accompanying use cases.