Elasticsearch Essentials

Abstract

BigData analytics, complex search queries and real-time event monitoring are only few use cases for using Elasticsearch, a distributed search engine.
In this course, you will learn what is Elasticsearch and how does it work.
You will be able to create Elasticsearch cluster, manage it, model your data properly, load it into the cluster and then run search and aggregation queries on it.

Target Audience

Developers, Team leaders, Software architects, Data engineers, Data scientists

Prerequisites

  • Basic knowledge of HTTP (GET, POST, JSON format)
  • Basic Programming Concepts (control flows, conditionals, scripting

Content

Intro to Elasticsearch:

  • Intro to text indexing
  • Lucene indexes
  • Elasticsearch cluster components
  • Elasticsearch installation
  • Basic Elasticsearch queries

Queries and Data modeling:

  • Elasticsearch client libraries
  • Loading data into Elasticsearch
    • Handling mappings (dates, type formats)
  • Bulk API
  • Data modeling
    • Languages
    • Analyzers and Tokenizers
    • Parent-Child relationships
    • Nested objects
  • Search queries
    • Query DSL
    • Terms
    • Free text search
    • Highlighting
    • Fuzzy
    • Scoring and boosting
    • Scroll API
  • Aggregations
    • Terms
    • Timeline
  • Special queries

Scale and Performance:

  • Elasticsearch performance monitoring
  • Designing for scale

Cluster Management:

  • Security
  • Logging
  • Reindexing
  • Schema management
  • Upgrades
  • Backup and restore

Duration

3 days

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