Data Stream Processing Night - Silicon Valley

Nov 02, 06:00PM PST(01:00AM GMT).
  • Silicon Valley AICamp
  • Free 129 Attendees

This is in-person only event in Silicon Valley.


Data streaming platforms provide the tools needed to bring together real-time streams of data. It enables data intelligent, real-time applications and systems, and empowers teams to act on data instantly.

We will host a series of meetup events to showcase some of the cutting edge developments that are happening in data stream processing in the open sourced tools and industry. We will invite the PMCs of Apache Beam, Airflow, Spark, Flink, Kafka, etc.. and teams who use these tools to share practical experiences, best practices in building data stream processing pipelines. The community of real-time technology leaders and developers will come together to share best practices and use cases as well as explore the vision and future of data streaming.

Agenda (PST):
* 6:00pm~6:30pm: Checkin and Food/drink
* 6:30pm~8:00pm: Tech talks
* 8:00pm~8:30pm: Networking and closing

Tech Talk 1: Apache Beam - fully language portable and scalable batch and streaming data processing.
Abstract: Apache Beam introduces a unified programming model for batch and streaming data processing. Beam provides SDKs for various programming languages, for example, Java, Python and Go and Beam pipelines are executed in a runner, for example, Apache Flink, Apache Spark and Google Cloud Dataflow. Beam provides a portability framework that allows a given runner to execute transforms defined in any given SDK. This lets Beam runners maintain one implementation that supports all current and future SDKs. Additionally, this allows Beam runners to use transforms from different SDK languages in the same pipeline. In this talk, we will look into Apache Beam’s portability framework and its benefits.
Speaker: Chamikara Jayalath, Google

Tech Talk 2: TBD

Z-park Silicon Valley Innovation Center
4500 Great America Pkwy, Santa Clara, CA

Chamikara Jayalath(Google)

Senior Software Engineer at Google and a PMC member for the Apache Beam project. Chamikara has been contributing to Apache Beam from its inception and has primarily contributed to various Beam I/O connector frameworks and Apache Beam’s Multi-language pipelines framework. Prior to Google, Chamikara completed his PhD at Purdue University focussing on large scale distributed data processing
The event ended.
Watch Recording
*Recordings hosted on Youtube, click the link will open the Youtube page.