Olena Kutsenko
Search and aggregations made easy with OpenSearch and NodeJS
#1about 4 minutes
Understanding OpenSearch core concepts and architecture
OpenSearch analyzes and stores data in a distributed architecture of shards, replicas, and nodes, accessible via a REST API or language-specific clients.
#2about 5 minutes
Setting up the NodeJS project and OpenSearch cluster
To get started, clone the example repository, set up a managed OpenSearch cluster, and configure the NodeJS client with your service URI.
#3about 3 minutes
Bulk indexing data and inspecting the schema
Use the bulk endpoint in the NodeJS client to efficiently index large datasets, allowing OpenSearch to automatically infer the data schema or mapping.
#4about 6 minutes
Executing different types of search queries
Learn to use various query types like match, match_phrase with slop, term, and boolean queries to perform full-text and structured searches.
#5about 3 minutes
Analyzing data with metric and bucket aggregations
Go beyond search by using aggregations to calculate metrics like averages or to group data into buckets with histograms for powerful analysis.
#6about 4 minutes
Visualizing data with OpenSearch Dashboards
Use OpenSearch Dashboards to create visualizations like bar charts and tag clouds, explore raw data in the Discover panel, and run queries in Dev Tools.
#7about 4 minutes
Q&A on indexing, aggregations, and OpenSearch vs Elasticsearch
The session concludes with answers to audience questions about indexing different data types, the benefits of OpenSearch over Elasticsearch, and aggregation limits.
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03:13 MIN
The challenge of real-time aggregations in PostgreSQL
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01:52 MIN
Identifying the limitations of the OpenSearch implementation
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03:15 MIN
Combining OpenTelemetry data with the Elastic stack
Observability with OpenTelemetry & Elastic
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04:50 MIN
An overview of the data indexing pipeline architecture
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05:26 MIN
Understanding the fundamentals of the Elasticsearch search engine
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