WORKSHOP
The Heart of the YTsaurus Platform: Core Components and Interactive Querying (WS12)
Date: 08 October 2026 | Duration: 3:30 - 5:30 PM
Venue: Workshop Room 3, NIMHANS Convention Centre, Bangalore
FEES:
• Rs.99 for Leaders Pass holders
• Rs.169 for Professionals Pass holders
• Rs.249 for Knowledge Pass holders
• Rs.399 for Community++ or Student Pass holders
• Rs.499 for all others
(Limited seats available)
To get common understanding of YTsaurus
Artur Turaev
Global Product Owner, YTsaurus
Andrey Grunau
Technical project manager, YTsaurus
- Data Engineers building ETL/ELT pipelines.
- Data Analysts working with massive data.
- Backend Developers interested in distributed storage systems.
- Students (senior undergraduate or graduate) studying Big Data technologies.
- Requirement: Basic familiarity with the command line (Linux/MacOS terminal) and fundamental concepts of databases (SQL/NoSQL).
1) Introduction to YTsaurus Architecture
- YTsaurus vs. Hadoop/Spark: Key differences.
- Core components: Master, File system, Scheduler.
- Tour of the Web UI (Navigation Tree & Operations Monitor).
2) Hands-on Lab 1: Table Management
- Creating Static Tables: Unsorted vs. Sorted tables.
- Understanding sort keys and their impact on read performance.
- Ingesting raw CSV/JSON data into the cluster.
3) Hands-on Lab 2: Executing MapReduce Jobs
- The concept of Operations in YTsaurus.
- Running a MapReduce job via CLI (filtering and aggregating data).
- Monitoring job progress, reading logs, and debugging via the Web UI.
4) Hands-on Lab 3: Dynamic Tables & Real-Time Updates
- Static vs. Dynamic Tables: When to use which?
- Simulating real-time data streams (upsert/lookup operations).
- Querying fresh data instantly.
5) Q&A
Benefits/Takeaways of this workshop for the attendees (What will attendees do after attending the workshop which they were not able to do before attending this)
- Interact confidently with a YTsaurus cluster using the Web UI and CLI.
- Design efficient data schemas by choosing between static and dynamic tables based on specific batch or real-time requirements.
- Execute and debug distributed data processing jobs (MapReduce) using built-in tools.
- Analyze job metrics in the web interface.
Operating System: Linux, macOS, or Windows with WSL2 installed (Linux/macOS is highly recommended for seamless CLI usage).
Software Tools:
A functional Terminal (Bash/Zsh).
Docker Desktop installed (recommended for running a pre-configured yt client container to avoid local dependency issues).
Network Access: Laptop must have internet access (or access to the organizer’s local network) to connect to the provided sandbox YTsaurus cluster.
Code Editor: Any text editor (VS Code, Vim, Nano, etc.) for writing simple processing scripts (Python/Bash) or YAML job specifications.
About Speakers
Arthur Turaev is a data product leader with over 20 years of IT experience, evolving from an ETL engineer to a Global Product Owner. He specializes in managing large-scale data warehouse and big data platforms. His expertise bridges technical engineering, project management, and business strategy to deliver high-impact data solutions. He has led major data initiatives at Yandex, Sberbank, Teradata and SAS Institute
Andrey Grunau is a Technical Project Manager with over 20 years of experience in IT, specialising in capacity planning and the development of compute clusters. He helps teams and services improve efficiency and address business challenges using the YTsaurus platform.