We welcome you to join us for an in-person Meetup hosted by Uber and the Apache Pinot community. We will kick off with opening marks by Ujwala Tulshigiri followed by a series of three interesting talks by the speakers from Uber, Startree.ai, and LinkedIn.
Event Details
- This Meetup is a co-hosted by Uber and Startree.ai
- This Meetup is an in-person event only
- Registration is required for the Meetup. Please RSVP & answer the questions (full name & email address)
- Event location details will be emailed a few days before the event to those who have registered for the event and provided an email address
Event Agenda
- 5:00 PM - Networking and Snacks
5:30 PM - Opening Remarks
5:40 PM - Talk 1 - Uncorking Real-time Analytics with Apache Kafka®, Apache Flink, and Apache Pinot:tm:, Startree
6:10 PM - Talk 2 - Real-Time Text Indexing at Uber Scale , Uber
6:40 PM - Talk 3 - Using Pinot analytics for Differential Privacy, Linkedin
7:10 PM - Closing Remarks
Presentation Info
- Real-Time Text Indexing at Uber Scale
In this session, we'll explore the recent enhancements in Pinot's Lucene-based text indexing and discuss how we successfully scaled ingestion to support the log-search needs of thousands of Uber engineers. We'll highlight key optimizations that enhance index freshness and throughput, ensuring that our users have access to up-to-date, searchable data. Attendees will discover how these improvements empower users to quickly and effectively access the insights they require.
- Speaker Bio: Chris Peck is Senior Software Engineer in the Real-Time Analytics team at Uber, working with ClickHouse and Pinot to support a range of observability needs. Outside of work, he enjoys discovering new coffees and when he can, exploring the eastern Sierras.
- Uncorking Real-time Analytics with Apache Kafka®, Apache Flink, and Apache Pinot™️
Discover how to harness the power of Apache Pinot, Kafka, and Flink for high-performance real-time analytics. This talk will cover:
- Introduction to Apache Pinot, Kafka, and Flink: Core functionalities and their synergy.
- Batch Data Ingestion and Querying in Pinot: Efficiently ingest and query static data.
- Integrating Streaming Data with Kafka and Pinot: Enrich analytics with combined data sources.
- Optimizing Analytics Operations: Deciding what to process in Pinot or Flink.
- Learn how to set up data pipelines and perform real-time analytics, equipping you with the knowledge to implement these technologies in your applications.
- Speaker Bio: Viktor Gamov is the Head of Developer Advocacy at StarTree, a company specializing in real-time analytics with Apache Pinot™. With a strong background in distributed systems and cloud-native architectures, Viktor excels in open-source technologies. He is dedicated to helping architects, developers, and operators build low-latency, scalable, and highly available systems. As a Java Champion and a respected speaker, Viktor is renowned for his insightful presentations at major industry events. He has co-authored books on enterprise web development and Apache Kafka®
- Using Pinot analytics for Differential Privacy
PEDAL (Privacy-Enhanced Data Analytics for Learning) is a framework designed to allow LinkedIn customers to gain insights from analytics without compromising LinkedIn member privacy. PEDAL uses differential privacy techniques to ensure that data can be analyzed in a secure and confidential manner, paving the way for more responsible data practices in the digital age. This approach can be applied across various domains where privacy is a concern, including social media, healthcare, and finance. At Linkedin, PEDAL acts as an intermediary service between applications and Pinot, to ensure differential privacy for analytics use-cases (like Creator, Post & Pages Analytics). In this talk, we present a brief overview of Differential Privacy, and discuss how PEDAL works with various privacy-algorithms in order to provide privatized results to our customers.
- Speaker Bio: Praveen is a Systems Software Engineer in the Data Infrastructure team at LinkedIn, working on Pinot. He plays a crucial role in enhancing the platform's scalability, efficiency, and privacy features to support LinkedIn's vast user base. Outside of work, Praveen enjoys playing video games and traveling to new destinations.
- Speaker Bio: Subbu Subramaniam is a member of Apache Pinot PMC. He built the real-time ingestion system in Pinot and has also contributed in many other areas of the pinot code base. He is currently the tech lead of the Online Analytics Organization at LinkedIn.
More Info on Pinot