Elasticsearch 8 Course with JavaScript Client for Beginners

Install Elasticsearch 8.7.0 and Kibana 8.7.0 on Windows, configure security with credentials and enrollment token, start Elasticsearch before Kibana, and use dev tools to manage data.

Discover how Elasticsearch, a document-oriented search engine built on Lucene, stores, deletes, and retrieves documents with fast search using an inverted index, mappings, and a comparison to relational databases.

Discover how Elasticsearch distributes data across a cluster of nodes, explaining shards and replicas, indexing with inverted indexes, and how segments become immutable while updates use versioning.

Create, retrieve, and delete indexes in Elasticsearch using http put, get, and delete requests. Learn how to manage docs with _doc and _source, and understand mappings and settings.

Explore how the Elasticsearch query context determines document relevance, using match, multi match, and bool queries, along with range, phrase, term, and prefix queries on a sample employees index.

Explore how to use filter context and fuzzy search in Elasticsearch 8, including term and range filters, bool filter, and performance benefits of filtering over scoring.

Explore aggregations in Elasticsearch, including metric aggregations (average, sum, min, max, stats), bucket aggregations (term, range, date range, histogram), pipeline and matrix aggregations, and moving average calculations.

Define custom mappings and settings for the employees index in Elasticsearch, including fields like name, age, salary, is_manager, and hire_date with date formats, plus shards, replicas, and bool must queries.

Learn how dynamic mappings in Elasticsearch automatically create field types from indexed documents, extendable by adding new fields like email, and the importance of explicit mappings for control.

Explore built-in and custom analyzers in Elasticsearch, including whitespace, standard, and English, plus ASCII folding, to see how lowercase and stopwords shape tokenization.

Install node and VS Code on Windows, verify node and npm versions, and set up a ready development environment for the Elasticsearch 8 course with JavaScript client.

Learn how to install the Elasticsearch JavaScript client and securely connect to an Elasticsearch cluster using https with a valid certificate, including setting up a Node.js project and configuring TLS.

Install docker on Windows and run Elasticsearch and Kibana in containers, following steps to set up Docker Desktop, enable WSL, create a network, pull images, and configure the map count.

Connect a Node.js application to Elasticsearch in a Docker container using a JavaScript client, configuring credentials, certificate, and a ping check to verify the connection.

Create an index named blog in Elasticsearch 8 with the JavaScript client, setting one shard and zero replicas, and define mappings for title, content, and date.

Define an array of documents with id, title, content, and date, then index them in the blog index using the Elasticsearch JavaScript client bulk method.

Learn to refresh the index and get a document by id using the Elasticsearch 8 JavaScript client, enabling immediate searchability of newly indexed documents in the blog index.

Build an async search function that queries blog index by matching content with JavaScript Elasticsearch client, and run a method to create the index, index, refresh, and retrieve by ID.

Create an index named books and define mappings for title (text), author (keyword), genre (keyword), and year (integer), then create, refresh, and search documents in the connected Elasticsearch cluster.

Prepare and bulk index book documents into the books index using the client bulk method, defining id, title, author, genre, and year of publishing, with error handling.

Develop an async function to search documents in the books index using the client.search method with a match query on genre, and log the hits to the console.

Learn to create and refresh a books index in Elasticsearch 8 with the JavaScript client, then index documents and perform a genre fiction search.

Learn how to fetch all documents from the books index using the JavaScript client with a match_all query and implement pagination and sorting with from, size, and sort options.

Learn to define geospatial mappings for places and regions, index documents with geo_point and geoshape, and perform a ten kilometres search near the Eiffel Tower using Elasticsearch 8 JavaScript.

Index ten product documents into the products.0002 index with the JavaScript client, then verify results with a match_all query in Kibana as you prepare for aggregations in Elasticsearch.

Discover terms aggregations in Elasticsearch to group documents by a field and count buckets. See the category.keyword example, build the aggregation in code, and verify results in Kibana.

Learn to implement date histogram aggregations in elasticsearch 8 with the javascript client, grouping documents by timestamp into day, week, and month intervals in the products 0002 index.

Explore range aggregations in Elasticsearch 8 with the JavaScript client, defining price ranges 0–100, 100–500, and 500–1000, counting documents and verifying results in Kibana.

Learn how metrics aggregations in Elasticsearch 8 with the JavaScript client compute statistics—average, sum, min, and max—on numeric fields, demonstrated by averaging product ratings.