ElasticSearch in action
summary
A runnable demo indexes a company blog via an Atom‑feed script, shows explicit mappings (including English/Dutch/raw fields) to fix mistaken types, and walks the analyzer/tokenizer outputs so full‑text queries and exact filters behave as expected. Examples include a geo point 5 km radius query over Belgian towns, aggregations that return authors and counts (Roy 415 posts, Anonymous 184, Kristoff 23), cluster behavior with default five shards and replicas, advice to run three nodes with discovery settings, and ELK/Beats/Kibana Sense examples plus a GitHub of runnable queries.
AI-written summary · about
chapters (13)
- 0:00Introduction
- 1:27What is Elasticsearch
- 2:50Core concepts and setup
- 6:24Mapping and analyzers
- 11:01Basic search queries
- 13:49Filters vs queries
- 17:44Geo spatial data
- 19:55Relevance and boosting
- 21:41Multi-index searches
- 23:28Aggregations explained
- 26:20Managing Elasticsearch
- 33:45ELK stack overview
- 35:34Integration and resources
related talks
35mElasticsearch - Beyond Full-text Search
47mMake sense of your (big) data using Elasticsearch
01h 04mDiving into Elasticsearch with .NET
41mBetter Data Exploration and Visualisation with Elasticsearch and Kibana
16mWhy we built ElasticSearch
54mAdvanced (elastic)search for your legacy application
31mUsing Elasticsearch with Rails Apps
37mBeyond the basics with Elasticsearch