Super Search with OpenSearch and Python
summary
OpenSearch is an Elasticsearch fork that the demo uses with the Python client to index ~220k recipe documents and run concrete queries against a live cluster. The recording shows match vs match_phrase with slope=1 to preserve or relax word order, demonstrates fuzziness=auto to tolerate typos like desert vs dessert, and wires results into OpenSearch Dashboards for counts and word clouds. Code calls the REST search endpoint and the demo queries actually return the shown results.
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chapters (16)
- 0:00SuperSearch with OpenSearch intro
- 1:10What is OpenSearch
- 3:21Why OpenSearch
- 4:02OpenSearch superpowers
- 6:13Python demo setup
- 9:01Match query basics
- 11:52Match query operators
- 13:41Match phrase query
- 16:49Slope parameter flexibility
- 18:34Slope parameter visualization
- 20:15Fuzziness parameter
- 21:40Automatic fuzziness
- 23:24OpenSearch Dashboards
- 25:13OpenSearch implementation example
- 26:59OpenSearch at Ivan
- 27:20Resources and closing
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