Elasticsearch for Developers

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Elasticsearch for Developers


–  Are you looking for ways to gather insights from the data and logs your system emits?
–  Would you like to join companies like Twitter and LinkedIn in providing your own tailor made search that
.   will enable your users to drill-down and auto-complete features?
–  How about creating shiny dashboards to visualize your system and the behavior of the data you gather?

In this intensive 2-day workshop on the leading open-source product Elasticsearch and it’s related technology stack you will learn both the basics of full-text search and information retrieval and how to unleash the power of the inverted index, using the powerful ELK stack: Elasticsearch, Logstash and Kibana.

Through hands-on exercises, lectures and by discussing real-world challenges, you will learn how to achieve a better user experience by incorporating your own search engine in your products. You will also learn how to use the ELK stack to monitor your data real-time, to create live dashboards and to visualize your data.

Course Objectives

The goal of this course is to provide an experienced developer with all the tools to succeed with integrating Elasticsearch into any type of project. You will learn:

  • How to use Elasticsearch for full-text search purposes, and query it for other usecases as well
  • Define and maintain Elasticsearch indexes, and index your data into them
  • Perform aggregation queries to drill-down into time-series data and other types of data
  • Understand where Elasticsearch shines and how to use it correctly

Developers with 3 years of experience or more. Platform doesn’t matter as most of the course is hands on using the REST API using dedicated tools (Sense chrome plugin or via Kibana).

Course Topics

Module 1 – Starting with some basics

  • Basics of Full text search and Information Retrieval
  • Introduction to Lucene and Elasticsearch
  • Using Elasticsearch from your favorite programming language
  • Use cases and continuous syncing with an external data source

Module 2 – Querying and full-text search

  • Various query types
  • Hands-on experience with indexing and searching texts
  • Understanding how scoring is applied
  • The analysis chain

Module 3 – The aggregations framework, Logstash, Beats and Kibana

  • Drilling down information
  • Real-time data analysis and reporting
  • The Aggregations Framework: Metric, Bucket and Pipeline aggregations
  • The ELK stack – Logstash and Kibana
  • Beats

Module 4 – Advanced features

  • Geo-spatial search and aggregations
  • Using scripts in queries and aggregations
  • Anomaly detection
  • Results highlighting
  • Record linkage via MoreLikeThis
  • Suggesters
  • The Percolator
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