Apache Spark and Databricks in Action -and- Enhancing Java Apps with LangChain4j


Details
Please note that registration via EventBrite is required for in-person or on-line attendance.
We are pleased to announce that Vladimir Shipovalov and Alok Tribrewala will be presenting their own topics at this month's meeting.
Apache Spark and Databricks in Action: Driving Cost Transparency Platform Through Intelligent Data Processing (presented by Vladimir Shipovalov)
This talk focuses on implementing Apache Spark and Databricks within the Cost Transparency (CT) Platform for intelligent data processing. The CT Platform processes diverse expense data, employing Spark for essential tasks like filtering, merging, enriching, and aggregating information.
A key feature is the Rule Service, a microservice enabling flexible business logic and dynamic rule updates without code changes. The DraftRun Service allows for testing new rules on data subsets. Apache Spark is an open-source distributed engine for various workloads, known for its speed through in-memory computing. Databricks enhances Spark as a cloud platform, offering streamlined cluster management, an optimized runtime, and collaborative tools.
The presentation demonstrates how Spark and Databricks drive efficient data processing in the CT Platform, including practical examples.
Enhancing Java Applications with LangChain4j: Practical AI Integrations (presented by Alok Tribrewala)
This talk explores practical strategies and insights for integrating LangChain4j and Large Language Models (LLMs) within Java applications. Attendees will learn how Java developers can leverage LangChain4j for tasks such as:
- Interpreting Complex Swarm Intelligence: Enhance transparency and interpretability of autonomous drone behaviors by translating complex swarm decisions into clear, actionable insights.
- Automating High-Quality Code Documentation: Improve developer productivity by automating accurate, consistent code documentation and facilitating efficient onboarding.
- Enterprise Integration of LLMs: Simplify and streamline the integration of advanced LLM capabilities in enterprise-grade Java systems.
Attendees will gain actionable knowledge to immediately implement AI-driven solutions using Java and LangChain4j.

Apache Spark and Databricks in Action -and- Enhancing Java Apps with LangChain4j