Registration is open - Live, Instructor-led Online Classes - Elasticsearch in March - Solr in April - OpenSearch in May. See all classes


Intro to OpenSearch

Get started with OpenSearch

If you’re just getting started, after taking this comprehensive 2-day session (two 4-hour sessions), you will understand all core OpenSearch concepts - field types and their options, mappings, analysis, search relevance scoring, aggregations and clustering.

Your trainer is an active OpenSearch consultant who worked with clients from many different industries on OpenSearch, Elasticsearch and Solr projects for 10+ years.

See Course Outline

What's Included

  • 8-hour online training
  • A digital copy of the training material, cheat-sheets, slides
  • Docker Compose files, configs, scripts, etc.
  • Certificate of Completion

Who should attend?

  • This OpenSearch online course is designed for technical attendees with any knowledge level.
  • No prior OpenSearch experience or knowledge is required. Experience with Linux is not a must, but basic familiarity with running shell commands (e.g., using curl command) will make the course more enjoyable.

Why attend?

  • Small, interactive, instructor-led classes
  • Lots of hands-on exercises
  • Customized learning experience
  • Flexible - no need to travel
  • Certificate of Completion included

Get Certified Upon Course Completion

Enroll in our course and take the next step in your professional journey.
Complete the course and receive a certificate that showcases your newly acquired skills.

Learn More

Upcoming Classes

Pick from our 8h online classes, structured to correspond to different roles and Elasticsearch knowledge levels: for beginners to experienced developers or ops who want to learn quickly. Delivery method: Live Online. Time: 09:00 AM – 01:00 PM ET (2 sessions).

opensearch Introduction to OpenSearch
May 27-28, 2024
$800 / personSee Course OutlineRegister Now!

Course Outline

Basic flow of data in OpenSearch
  • What is OpenSearch and typical use-cases
  • Indexing; what is an index and an ID
  • Mappings; stored and indexed fields
  • Analysis basics
  • Realtime get
  • Search; how searches are distributed to shards
  • Aggregations and doc values introduction
  • Updates; versioning
  • Deletes; introduction to Lucene segment merges
  • Lab
    • CRUD operations
    • Query and filter
    • Aggregations
Indexing and storing data
  • Bulk API
  • Mappings and mapping types
  • Subfield definitions
  • Default mappings
  • Texts, keywords, integers and other core types
  • Predefined fields; storing fields separately vs _source
  • Lab
    • Using the bulk API
    • Changing mapping
Text analysis
  • Built-in analyzers: standard language analyzers
  • Custom analyzers
  • Char filters
  • Tokenizers
  • Token filters: lowercase, stemming, synonyms
  • Using the Analyze API
  • Lab
    • Add stemming support
    • Add support for non-ASCII characters
Searching through your data
  • Selecting fields.
  • Sorting and pagination
  • Search basics: term, range and bool queries
  • Match query and its main options
  • Query string query
  • Lab
    • Configure sorting, pagination and select the right fields
    • Using a bool query to combine different match, range and term queries
  • Metrics aggregations: stats, cardinality, percentiles
  • Why terms, cardinality and percentiles are approximate
  • Multi-bucket aggregations: terms, ranges and histograms
  • Nesting aggregations; how nesting works
  • Lab
    • Computing the cardinality of a field
    • Sorting buckets by results of sub-aggregations
    • Nest the sum and histogram aggregations
Clustering Essentials
  • Nodes, shards and replicas
  • How replication works
  • How distributed search works
  • RAM and heap size
  • Bootstrapping a cluster
  • Cat APIs
  • Lab
    • Create an index
    • Verify the distribution of shards
    • Add a new node to the cluster

Main Topics

  • OpenSearch Basic Concepts
  • OpenSearch Strengths and Weaknesses
  • OpenSearch CRUD Operations
  • Field types and Predefined Fields
  • Using and Customizing Analyzers
  • Types of Queries and Aggregations
  • Shards, Replicas and Clustering

Course key takeaways

After taking this course you will:

  • Understand all core OpenSearch concepts – index, document, sharding, replication, mapping, search relevance, etc.
  • Be able to index data into OpenSearch and retrieve it using search and realtime get APIs
  • Have a solid grasp of the underlying query parsing, analysis, tokenization, and various types of queries
  • Learn about a number of different types of OpenSearch aggregations

Things to remember

  • Participants must use their own computer with OSX, Linux, or Windows, with a container management tool installed (Docker Desktop, Podman, nerdctl) as well as Zoom.
  • Participants should be comfortable using a terminal/command line.
  • Participants need a working audio and video setup for labs, which are done in groups.

Sematext provides:

  • A digital copy of the training material, including slides and many sample requests
  • A docker-compose.yml file for the lab environment

About the trainer

Radu Gheorghe

Radu Gheorghe

Your trainer is an active OpenSearch consultant who worked with clients from many different industries on OpenSearch, Elasticsearch and Solr projects for 10+ years.

Need On-Site or Remote Training

Get in touch with us