Martijn Visser
Group Product Manager at Confluent, PMC member and Committer for Apache Flink
Amsterdam, The Netherlands
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As Group Product Manager at Confluent, Martijn is responsible for the strategy and development of stream processing capabilities using Apache Flink within Confluent Cloud. His work focuses on the Flink user experience, including APIs and languages (SQL, Java, Python), data integration with systems like Apache Kafka and Schema Registry, the Flink SQL/Table API type system, and core Flink runtime components such as data processing, checkpointing/savepointing, and observability.
An active Apache Flink PMC member and Committer, Martijn contributes to the open-source project by collaborating with the community on user-facing features. This includes work on the Table API, SQL, various connectors, and data formats, with a focus on enhancing their functionality and usability for developers.
Martijn joined Confluent following the acquisition of Immerok, where he was a Product Manager. Before that, he was a Product Manager at Ververica, working on Apache Flink and the Ververica Platform, and served as Product Lead at ING, responsible for their Streaming Data and Engagement Platform.
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Simplifying Data Processing with Apache Flink SQL
Apache Flink is a powerful open-source stream processing framework that supports unified batch and streaming processing. With its SQL support, Flink has become even more accessible to data analysts and developers who are familiar with SQL.
In this talk, we will provide a short introduction to Apache Flink and explain how you can leverage SQL under the hood. We will cover some of the SQL-specific features of Flink, such as dynamic tables, streaming SQL and support for stateful operations like windowing and pattern recognition. We will also show some real-world examples of how you can use Flink's SQL capabilities to build scalable and efficient data processing pipelines.
By the end of this talk, you will have a better understanding of how Apache Flink can be used to process large volumes of data using SQL, and how you can take advantage of Flink's powerful stream processing capabilities to build robust and scalable data applications.
Unlocking the Power of Flink's Table API: A Deep Dive into Advanced Capabilities and Use Cases
In today's fast-paced digital world, the ability to process and analyze real-time data streams sets the foundation for innovative applications across industries. Apache Flink's Table API enables developers to write complex data processing queries in a simple, declarative manner using Java, Python or even combined with SQL. This talk aims to unravel all the capabilities of the Flink's Table API, providing attendees with a thorough understanding of its architecture, functionalities, and the immense possibilities it unlocks for real-time data analytics.
We'll embark on a comprehensive deep dive into the API, exploring its seamless integration with the Flink ecosystem and how it abstracts complex stream processing operations into intuitive SQL and expression-based queries. Participants will gain insights into optimizing their data processing workflows, leveraging Flink's Table API for efficient state management, event time processing, and complex event processing patterns.
Through practical examples, this presentation will demonstrate the power and flexibility of the Flink Table API, showcasing how it can be employed to build scalable, high-performance data streaming applications. Whether you're a seasoned data engineer or new to the world of real-time data streaming, this talk will equip you with the knowledge and skills to harness the full potential of the Flink Table API, driving innovation and efficiency in your data processing projects.
Getting data in and out of Flink - Understanding Flink and its connector ecosystem
Apache Flink is a powerful open-source stream processing framework that enables real-time data processing at scale. One of the key features of Flink is its rich ecosystem of connectors that allow users to easily integrate with a wide range of data sources and sinks. However, working with connectors can be challenging, especially for users who are new to Flink or stream processing.
This talk aims to help users better understand Flink connectors, the Flink connector ecosystem, and their importance in building scalable and robust data processing pipelines. It will cover topics such as:
* An introduction to Flink connectors and their role in stream processing
* A deep dive into the different Flink connector APIs, including the Unified Source and Sink API, SourceReaderBase and the Async Sink API.
* The benefits of using unified batch and streaming APIs in Flink
By the end of this talk, attendees will have a solid understanding of Flink connectors, the connector interface, and be better equipped to build efficient and reliable data processing pipelines with Flink.
Apache Flink - Only SQL
Customers and companies are becoming more digital and the amount of available data is growing everyday. Traditionally, data engineers were needed to implement business logic via data pipelines before business users can start using it. In this talk, I will explain how data analysts and non-engineers can use only Flink SQL to explore and transform data into insights and actions, without writing any Java, Scala or Python code. This includes:
* Exploring data sources, such as a realtime clickstream and a table with historical clickstream results
* Displaying a fraud detection notification based on the customers clickstream pattern
* Combining multiple data sources to display actionable insights on your website
Uptime Conference 2022 Sessionize Event
Martijn Visser
Group Product Manager at Confluent, PMC member and Committer for Apache Flink
Amsterdam, The Netherlands
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