Chapters (36)
- 0:00General introduction
- 3:34Introduction
- 5:56Elasticsearch installation process
- 9:02Create an index
- 15:00Index documents
- 22:13Field data types
- 36:55Delete documents
- 39:45Get documents
- 42:35Count documents
- 46:05The exists API
- 49:26The update API
- 57:21The bulk API
- 1:04:40The search API - Part 1
- 1:10:26The search API - Part 2
- 1:21:40The search API - Part 3
- 1:28:54Dense vectors
- 1:33:34Embeddings
- 1:42:11kNN search
- 1:52:01Deep pagination
- 2:08:35Ingest pipelines
- 2:23:32Ingest processors
- 2:31:51Filters in depth
- 2:43:02SQL search API
- 2:51:54Time series data stream
- 3:08:57Analyzers
- 3:24:08The synonyms API
- 3:33:12Common options
- 3:43:25Change the heap size
- 3:48:16Final project - Part 0
- 3:50:11Final project - Part 1
- 4:08:10Final project - Part 2
- 4:23:53Final project - Part 3
- 4:35:14Final project - Part 4
- 4:48:00Final project - Part 5
- 4:56:26Final project - The end
- 4:58:20Conclusion
Show the creator's full description
Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.
✏️ Course developed by @3CodeCampers
⭐️ Links ⭐️
Here is the link to the GitHub repository to get slides, notebooks and the source code for the final project: https://github.com/ImadSaddik/ElasticSearch_Python_Tutorial
Link to the 3CodeCamp YouTube channel: https://www.youtube.com/@3CodeCampers
Link to the official documentation: https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
Link to the starter project: https://www.elastic.co/search-labs/tutorials/search-tutorial/starter-project
Link to the original APOD website: https://apod.nasa.gov/apod/archivepix.html
Link to my universe hub: https://myuniversehub.com/
⭐️ Contents ⭐️
(0:00:00) General introduction
(0:03:34) Introduction
(0:05:56) Elasticsearch installation process
(0:09:02) Create an index
(0:15:00) Index documents
(0:22:13) Field data types
(0:36:55) Delete documents
(0:39:45) Get documents
(0:42:35) Count documents
(0:46:05) The exists API
(0:49:26) The update API
(0:57:21) The bulk API
(1:04:40) The search API - Part 1
(1:10:26) The search API - Part 2
(1:21:40) The search API - Part 3
(1:28:54) Dense vectors
(1:33:34) Embeddings
(1:42:11) kNN search
(1:52:01) Deep pagination
(2:08:35) Ingest pipelines
(2:23:32) Ingest processors
(2:31:51) Filters in depth
(2:43:02) SQL search API
(2:51:54) Time series data stream
(3:08:57) Analyzers
(3:24:08) The synonyms API
(3:33:12) Common options
(3:43:25) Change the heap size
(3:48:16) Final project - Part 0
(3:50:11) Final project - Part 1
(4:08:10) Final project - Part 2
(4:23:53) Final project - Part 3
(4:35:14) Final project - Part 4
(4:48:00) Final project - Part 5
(4:56:26) Final project - The end
(4:58:20) Conclusion
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