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World Congress 2022 β€’ Jun 15, 2022

Search and aggregations made easy with OpenSearch and NodeJS

Olena Kutsenko

How do you build a highly scalable search engine? Discover how to integrate OpenSearch with Node.js to index, query, and visualize massive datasets effortlessly.

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#1 about 2 min

Introduction to OpenSearch and data management

The necessity of fast data stores and the transition from Elasticsearch to OpenSearch.

#2 about 3 min

Core OpenSearch cluster architecture and terminology

How mapping, indexing, shards, nodes, and clusters distribute search workloads horizontally.

#3 about 1 min

Setting up the Nodejs project and repository

Cloning the demonstration repository and preparing the local JavaScript environment.

#4 about 2 min

Provisioning a cluster with managed OpenSearch

Using open-source binaries or managed services to launch the backing search cluster.

#5 about 2 min

Introducing the sample Kaggle recipe dataset

Downloading a database of recipes for exploring search and aggregation endpoints.

#6 about 2 min

Configuring the Nodejs OpenSearch client connection

Connecting to the cluster securely using environment variables and client configuration scripts.

#7 about 3 min

Ingesting dataset files via the bulk endpoint

Pushing thousands of JSON objects iteratively into the cluster index using bulk commands.

#8 about 2 min

Retrieving automatically generated cluster index schemas

Fetching mapping metadata to observe inferred property types like dates and floats.

#9 about 1 min

Sending a fundamental match search query

Executing simple text searches against target index fields to receive relevant matching items.

#10 about 2 min

Breaking down the domain specific language request

Understanding the anatomy of the JSON payload powering complex queries and relevance scoring.

#11 about 2 min

Controlling word distance with match phrase

Adjusting query strictness and spacing flexibility using the phrase slop parameter.

#12 about 1 min

Sifting targeted values using term queries

Applying exact matching on specific numerical ranges or un-scored field values within properties.

#13 about 2 min

Combining logic with query string and boolean queries

Writing readable inclusion and exclusion rules to heavily restrict search result variations.

#14 about 2 min

Generating dataset statistics with averaging aggregations

Calling aggregation endpoints rather than queries to compute aggregate metrics across items.

#15 about 2 min

Sorting items sequentially into histogram buckets

Chunking recipes chronologically based on associated continuous properties to observe historical groupings.

#16 about 3 min

Visualizing aggregated dimensions within OpenSearch dashboards

Configuring external cluster dashboards to explicitly draw rating bar charts and tag clouds.

#17 about 3 min

Examining manual telemetry limits via discover tools

Using the explorer panels and built-in interactive requests without writing underlying Javascript functions.

#18 about 3 min

Dealing with mixed payloads and structural patterns

Audience questions addressing varied JSON mapping strategies, open-source licensing splits, and heavy collection handling.

Matching moments

3:00 min

Benchmarking SearchOLAP against existing database engines

Andrey Abramov Andrey Abramov Β· World Congress 2026 Europe

1:49 min

Reviewing the legacy search architecture using OpenSearch

Dharin Shah Dharin Shah Β· World Congress 2025

45 sec

Supported OpenSearch APIs for gRPC in version 3.2

Sakshi Nasha Sakshi Nasha Β· Europe 2026 Virtual

4:51 min

Executing simple full-text search queries using the Kibana interface

Derek Binkley Β· LIVE

1:52 min

Introducing SearchOLAP for native analytical processing

Andrey Abramov Andrey Abramov Β· World Congress 2026 Europe

1:41 min

Open source technology stack for workflow orchestration

Phil Nash Β· Coffee With Developers

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