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WeAreDevelopers LIVE • Nov 30, 2020

Add Location-based Searching to Site with ElasticSearch

Derek Binkley

How do you return localized search results across millions of records in mere milliseconds? Discover how to combine geographic boolean filters with ranked text queries in Elasticsearch.

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#1 about 3 min

Understanding the fundamentals of the Elasticsearch engine

A look at Elasticsearch as a read-optimized, REST-based search engine built on Apache Lucene.

#2 about 2 min

Exploring the core components of the ELK stack

How Beats, Logstash, Kibana, and Elasticsearch work together for managing and visualizing data.

#3 about 2 min

Reviewing deployment and hosting options for Elasticsearch clusters

Different environments for running search clusters including AWS images, Docker containers, and GraphQL annotation integrations.

#4 about 3 min

Bootstrapping the geographic location API using Docker Compose

How to spin up an Elasticsearch and Kibana instance locally using a Docker compose file.

#5 about 2 min

Defining indexes and documents in the Elasticsearch data structure

The hierarchy of indices, document types, and mappings used to structure saved records.

#6 about 5 min

Configuring property mappings and spatial data types for indexing

How to configure schema templates that support integer, text, keyword, and geospatial data points.

#7 about 1 min

Reviewing the geographic feature classes inside the sample dataset

A brief look at the format of location records grouped by feature classes and codes.

#8 about 5 min

Executing simple full-text search queries using the Kibana interface

Running raw queries to rapidly analyze large numbers of documents based on a matched search score.

#9 about 5 min

Filtering query outputs and structuring complex boolean search requests

Applying keyword filters alongside fuzzy matching to exclude irrelevant documents without affecting relevancy scores.

#10 about 2 min

Grouping distinct dataset values using Elasticsearch bucket aggregation queries

How bucket aggregations behave like database groupings to isolate distinct properties for exploration.

#11 about 2 min

Leveraging native search functions like the more like this feature

Exploring native performance boosts and feature behaviors like retrieving similar records to help discover nested items.

#12 about 2 min

Optimizing index data ingestion using bulk insert operations

Preparing chunked data payloads in PHP to optimize the speed of ingesting large quantities of records.

#13 about 2 min

Outlining the architecture needed for geographic distance search operations

The basic goals of querying mapping endpoints via latitude, longitude, and custom spatial radii.

#14 about 3 min

Restricting search locations matching a radial geographic distance query

Applying a spatial radius filter around a specific coordinate to precisely constrain matching query responses.

#15 about 4 min

Chaining full-text string matching algorithms with strict geospatial filters

Unifying string matching behaviors with a coordinate distance boundary using a boolean combined query pattern.

#16 about 6 min

Sorting matched coordinate search results by accurate geographical distances

Arranging the final search payloads geographically and customizing mathematical plane algorithms to evaluate distance spans.

#17 about 3 min

Constraining geographic record sets using map bounds and polygons

Drawing custom map boxes or custom polygon shapes to strictly bind valid matching results.

#18 about 3 min

Updating dynamic schema mappings to support nested data arrays

Modifying schemas dynamically to append new metadata fields like arrays of nested location comments.

Matching moments

4:33 min

Core search and resiliency capabilities of Elasticsearch

Alexander Reelsen · LIVE

6:56 min

Managing geospatial queries and analytical endpoints with Redis

Miki Lombardi · LIVE

3:02 min

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1:06 min

Utilizing Elasticsearch infrastructure as a vector database

Iulia Feroli Iulia Feroli · LIVE

3:55 min

Core architecture and federated execution of SearchOLAP

Andrey Abramov Andrey Abramov · World Congress 2026 Europe

2:19 min

Core OpenSearch cluster architecture and terminology

Olena Kutsenko · World Congress 2022

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