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Elasticsearch Fundamentals: Indexing and Querying Data
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Introduction to Elasticsearch
Elasticsearch
What Is Elastic Stack?
Getting started on Elasticsearch
Architecture of ElasticsearchInteracting with ElasticsearchCRUD OperationsMappingKeyword vs. Text Data TypeScripting and Runtime FieldsQuiz: Getting Started with Elasticsearch
Text Analysis
What Is Text Analysis?Analyzers in ElasticsearchCustom AnalyzersCustom Analyzers: Character filtersCustom Analyzer: TokenizersCustom Analyzers: Token FiltersBuilt-In AnalyzersChallenges: AnalyzersSolutions: AnalyzersQuiz: Text Analysis
Search on ElasticSearch
Introduction to Search Request
Full-Text Queries: Match Query
Full-Text Queries: Match Query Parameters
Full-Text Query: Exploring More Queries
Term-Level Queries: Term Query
Term-Level Queries: Range Query
Term-Level Queries: Exploring More Queries
Fuzzy Search
Compound Queries: Boolean Query
Challenge: Search on Elasticsearch
Solution: Search on Elasticsearch
Quiz: Search on Elasticsearch
Aggregation
Introduction to AggregationBucket AggregationMetric aggregationCombining Bucket and Metrics AggregationPipeline AggregationsNested Bucket AggregationsChallenge: AggregationsSolution: AggregationQuiz: Aggregation
Conclusion
Wrap Up and Next Steps

Project

Integrate Elasticsearch in the Ruby on Rails Application

Full-Text Query: Exploring More Queries

Explore more full-text queries and learn how to utilize them.

We'll cover the following
  • Overview
  • Match phrase query
  • Match phrase prefix query
  • Multi-match query
  • Token matching in match phrase query
  • Example
    • Creating data
    • Queries
      • Retrieving books that contain the phrase "classic novel" in their description
      • Retrieving books that contain the completion of the phrase "classic novel fi" in their description field
      • Retrieving products with the term "novel" present in either their title or description fields
  • Kibana widget

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