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Elasticsearch

Learn how Elasticsearch stores JSON documents across a cluster, how mappings and field types decide what you can search, and how to write the everyday queries that find, filter, sort and page through results — all on one small bookshop index.

Ready to learn5 sections · 22 lessons
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Course curriculum

Introduction to Elasticsearch4 lessons

Learn the JSON-over-HTTP language every request uses, how a search engine differs from a relational database, where Elasticsearch sits in the ELK stack, and how to run a node and reach it from Kibana's Console.

  1. JSON and REST — How You Talk to Elasticsearch10 min
  2. Search Engines vs Relational Databases12 min
  3. The ELK Stack and What Elasticsearch Is Used For10 min
  4. Running Elasticsearch: Docker, Elastic Cloud and the Kibana Console12 min
Cluster Anatomy and Mappings5 lessons

Meet clusters, nodes, indices, documents and IDs; see what master, data and coordinating nodes do; split indices into shards and replicas; then learn how dynamic and explicit mappings decide each field's type — and how a mapping can explode.

  1. Cluster, Node, Index, Document, ID10 min
  2. Node Roles: Master, Data and Coordinating12 min
  3. Shards, Replicas and the Split-Brain Problem15 min
  4. Dynamic Mapping — Elasticsearch Guesses the Schema12 min
  5. Explicit Mapping and the Mapping Explosion15 min
Data Types4 lessons

Decide between text and keyword, pick numeric, boolean and date types that sort and compare correctly, map geo points for distance searches, and choose between object, nested and flattened for structured data.

  1. Text vs Keyword — The Most Important Choice12 min
  2. Numbers, Booleans and Dates12 min
  3. Geo Points — Searching by Place12 min
  4. Object, Nested and Flattened15 min
Documents and Leaf Queries5 lessons

Create and delete indices, index, read, update and delete documents one at a time and in bulk, meet the query languages and the leaf-versus-compound idea, then write match, term, range, exists, ids, prefix and wildcard queries.

  1. Create, Read, Update and Delete — Indices and Documents12 min
  2. Many Documents at Once: Bulk, By-Query and Reindex15 min
  3. Query DSL and the Other Query Languages12 min
  4. Match vs Term — Analysed or Exact12 min
  5. Range, Exists, IDs, Prefix and Wildcard15 min
Controlling Search Results4 lessons

Combine leaf queries with bool's must, should, filter and must_not, understand query versus filter context, then page and sort results and trim and highlight what comes back.

  1. bool: must and should12 min
  2. bool: filter and must_not — Query vs Filter Context12 min
  3. Pagination and Sorting12 min
  4. Source Filtering and Highlighting12 min