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This PR adds all the guides from [Visual Guides](https://bytebytego.com/guides/) section on bytebytego to the repository with proper links. - [x] Markdown files for guides and categories are placed inside `data/guides` and `data/categories` - [x] Guide links in readme are auto-generated using `scripts/readme.ts`. Everytime you run the script `npm run update-readme`, it reads the categories and guides from the above mentioned folders, generate production links for guides and categories and populate the table of content in the readme. This ensures that any future guides and categories will automatically get added to the readme. - [x] Sorting inside the readme matches the actual category and guides sorting on production
34 lines
1.1 KiB
Markdown
34 lines
1.1 KiB
Markdown
---
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title: "How to Learn Elasticsearch"
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description: "Learn about Elasticsearch features, use cases, and core data structures."
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image: "https://assets.bytebytego.com/diagrams/0182-elastic-search.jpeg"
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createdAt: "2024-03-08"
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draft: false
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categories:
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- caching-performance
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tags:
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- Elasticsearch
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- Search
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---
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Based on the Lucene library, Elasticsearch provides search capabilities. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. The diagram above shows the outline.
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## Features of ElasticSearch:
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* Real-time full-text search
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* Analytics engine
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* Distributed Lucene
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## ElasticSearch use cases:
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* Product search on an eCommerce website
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* Log analysis
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* Auto completer, spell checker
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* Business intelligence analysis
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* Full-text search on Wikipedia
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* Full-text search on StackOverflow
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The core of ElasticSearch lies in the data structure and indexing. It is important to understand how ES builds the **term dictionary** using **LSM Tree** (Log-Strucutured Merge Tree).
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