Derek Binkley
Add Location-based Searching to Site with ElasticSearch
#1about 5 minutes
Understanding the fundamentals of the Elasticsearch search engine
Elasticsearch is a read-optimized search engine based on Apache Lucene that operates via REST calls and is part of the ELK stack.
#2about 2 minutes
Setting up a local development environment with Docker
A local Elasticsearch and Kibana environment can be quickly configured and launched using a simple Docker Compose file.
#3about 6 minutes
Defining data structure with indexes and mappings
Data is organized into JSON documents within an index, and its structure is defined by a mapping that specifies data types like text, keyword, and geo_point.
#4about 11 minutes
Performing basic text searches and filters in Kibana
Use `match` queries for ranked text searching and `filter` queries for exact, non-scored matching, which can be combined using a `bool` query.
#5about 3 minutes
Exploring advanced features and efficient data ingestion
Elasticsearch offers fast performance, advanced features like "more like this" searches, and requires bulk inserts for efficient data loading.
#6about 8 minutes
Finding locations within a specific geographic radius
The `geo_distance` filter allows you to find all documents that fall within a specified circular radius from a central latitude and longitude point.
#7about 5 minutes
Sorting search results by proximity to a point
Instead of just filtering, you can use a `geo_distance` sort to order results by their actual distance from a given point, from nearest to farthest.
#8about 2 minutes
Querying for locations inside a custom polygon shape
The `geo_polygon` filter enables searching for documents whose geo-points fall within a custom shape defined by a series of latitude and longitude coordinates.
#9about 2 minutes
Modifying schemas and handling complex object arrays
You can add new properties to an existing mapping, and the `nested` data type should be used to properly index and query arrays of objects.
Related jobs
Jobs that call for the skills explored in this talk.
Matching moments
25:24 MIN
Q&A on indexing, aggregations, and OpenSearch vs Elasticsearch
Search and aggregations made easy with OpenSearch and NodeJS
12:14 MIN
Introducing the core principles of Elasticsearch
Distributed search under the hood
23:08 MIN
Leveraging Redis for geospatial data management
Covid-19 - A crowdsourced map for checking supermarket wait times worldwide
15:33 MIN
Using Elasticsearch as a vector database for search
Harry Potter and the Elastic Semantic Search
00:51 MIN
Understanding the original search architecture at GetYourGuide
Optimizing Discovery: PostgreSQL's Role in Transforming GetYourGuide's Search
26:28 MIN
Audience Q&A on use cases, CMS, and SEO
One Framework To Rule Them All: Faster Websites With Astro
03:15 MIN
An overview of existing full-text search solutions
Writing a full-text search engine in TypeScript
25:32 MIN
Visualizing application performance with an Elastic dashboard
Observability with OpenTelemetry & Elastic
Featured Partners
Related Videos
46:58Distributed search under the hood
Alexander Reelsen
57:52Harry Potter and the Elastic Semantic Search
Iulia Feroli
55:39Creating a routing app with Google Maps API from scratch
Germán Álvarez
34:34Vision for Websites: Training Your Frontend to See
Daniel Madalitso Phiri
39:39Writing a full-text search engine in TypeScript
Michele Riva
36:44ChatGPT vs Google: SEO in the Age of AI Search - Eric Enge
Eric Enge
28:55Search and aggregations made easy with OpenSearch and NodeJS
Olena Kutsenko
57:52Develop AI-powered Applications with OpenAI Embeddings and Azure Search
Rainer Stropek
Related Articles
View all articles
.gif?w=240&auto=compress,format)
From learning to earning
Jobs that call for the skills explored in this talk.
Senior DevOps Engineer - Search & Services - (f/m/x)
AUTO1 Group SE
Berlin, Germany
Intermediate
Senior
ELK
Terraform
Elasticsearch
Search - Search Inference - Senior Site Reliability Engineer
Elastic
€88K
Senior
Linux
Terraform
Kubernetes
Elasticsearch
+2
Elasticsearch - Principal Software Engineer II - Search Internals, Lucene
Referral Board
Apache Solr
Elasticsearch
Continuous Integration
Elasticsearch - Principal Engineer - Core Infrastructure, & JVM Internals
Elastic
Kubernetes
Elasticsearch
Microsoft Access
Software Engineer - Data Infrastructure - OpenSearch/ElasticSearch
Canonical Ltd.
Remote
Linux
Kubernetes
Elasticsearch