This Elasticsearch Training intends to provide a solid foundation in search and information retrieval. It starts with fundamental concepts and follows with internals, best-practices and key features. Each topic is followed by a hands-on lab. At the end of the training, attendee will have deep understanding of how Elastic search works, will be able to reliably analyze data and will be ready to build search applications.

  • Architects
  • DBAs
  • Developers

Basic knowledge of database concepts and development environments

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16 Hours

Software Engineering

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Certificate: No

Price: contact us for more details

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Course Outline

Introduction to Elasticsearch

      • The Story of Elasticsearch
      • The Components of Elasticsearch
      • Documents
      • Indexes
      • Indexing Data
      • Searching Data
      • The Bulk API

 

The Search API

      • Introduction to the Search API
      • URI Searches
      • Request Body Searches
      • The match Query
      • The match phrase Query
      • The range Query
      • The Bool Query
      • Source Filtering

 

Text Analysis

      • What is Analysis?
      • Building an Inverted Index
      • Analyzers
      • Custom Analyzers
      • Character Filters
      • Tokenizers
      • Token Filters
      • Defining Analyzers
      • Synonyms
      • How to Choose an Analyzer
      • Segments

 

Mappings

      • What is a Mapping?
      • Dynamic Mappings
      • Defining Explicit Mappings
      • Adding Fields
      • Dive Deeper into Mappings
      • Specifying Analyzers
      • Dynamic Templates
      • Index Templates

 

More Search Features

      • Filters
      • Term Filters
      • The match_phrase_prefix Query
      • The multi_match_Query
      • Fuzziness
      • Highlighting
      • More Like This

The Distributed Model

      • Starting a Node
      • Creating an Index
      • Starting a Second Node
      • Shards: Distribution of an Index
      • Distributing Documents
      • Replication
      • Split Brain
      • Other Node Types
      • Development vs. Production Mode

Working with Search Results

      • The Anatomy of a Search
      • Relevance
      • Boosting Relevance
      • DFS Query-then-fetch
      • Sorting Results
      • Doc Values and Fielddata
      • Pagination
      • Scroll Searches
      • Choosing a Search Type

 

Aggregations

      • What are Aggregations?
      • Types of Aggregations
      • Buckets and Metrics
      • Common Metrics Aggregations
      • The range Aggregation
      • The date range Aggregation
      • The terms Aggregation
      • Nesting Buckets

 

 More Aggregations

      • Global Aggregation
      • The missing Aggregation
      • Histograms
      • Date Histograms
      • Percentiles
      • Top Hits
      • Significant Terms
      • Sorting Buckets

 

Handling Relationships

        • The Need for Data Modeling
        • Denormalization
        • The Need for Nested Types
        • Nested Types
        • Querying a Nested Type
        • Sorting on a Nested Type
        • The Nested Aggregation
        • Parent/Child Types
        • The has child Query

The has_parent Query