Hi Paolo, Yes, we will stream the meetup. Usually the link will be posted to the meetup website a couple of hours before the meetup. Feel free to ping me if you don't see it.
Thanks, Jiangjie (Becket) Qin On Fri, Nov 17, 2017 at 11:59 AM, Paolo Patierno <ppatie...@live.com> wrote: > Hi Becket, > I watched some of these meetups on the related YouTube channel in the past. > Will be it available in streaming or just recorded for watching it later ? > > Thanks > Paolo > ________________________________ > From: Becket Qin <becket....@gmail.com> > Sent: Friday, November 17, 2017 8:33:04 PM > To: dev@kafka.apache.org; us...@kafka.apache.org > Subject: Stream Processing Meetup@LinkedIn (Dec 4th) > > Hi Kafka users and developers, > > We are going to host our quarterly Stream Processing Meetup@LinkedIn on > Dec > 4. There will be three speakers from Slack, Uber and LinkedIn. Please check > the details below if you are interested. > > Thanks, > > Jiangjie (Becket) Qin > > *Stream Processing with Apache Kafka & Apache Samza* > > - Meetup Link: here > <https://www.meetup.com/Stream-Processing-Meetup- > LinkedIn/events/244889719/> > - When: Dec 4th 2017 @ 6:00pm > - Where: LinkedIn Building F , 605 West Maude Avenue, Sunnyvale, CA > (edit > map > <https://www.meetup.com/Stream-Processing-Meetup- > LinkedIn/events/244889719/> > ) > > > *Abstract* > > 1. Stream processing using Samza-SQL @ LinkedIn > > *Speaker: Srinivasulu Punuru, LinkedIn* > Imagine if you can develop and run a stream processing job in few minutes > and Imagine if a vast majority of your organization (business analysts, > Product manager, Data scientists) can do this on their own without a need > for a development team. > Need for real time insights into the big data is increasing at a rapid > pace. The traditional Java based development model of developing, deploying > and managing the stream processing application is becoming a huge > constraint. > With Samza SQL we can simplify application development by enabling users to > create stream processing applications and get real time insights into their > business using SQL statements. > > In this talk we try to answer the following questions > > 1. How SQL language can be used to perform stream processing? > 2. How is Samza SQL implemented - Architecture? > 3. How can you deploy Samza SQL in your company? > > > 2. Streaming data pipeline @ Slack > *Speaker:- Ananth Packkildurai, Slack* > *Abstract: *Slack is a communication and collaboration platform for teams. > Our millions of users spend 10+ hrs connected to the service on a typical > working day. They expect reliability, low latency, and extraordinarily rich > client experiences across a wide variety of devices and network conditions. > It is crucial for the developers to get the realtime insights on Slack > operational metrics. > In this talk, I will talk about how our data platform evolves from the > batch system to near realtime. I will also touch base on how Samza helps us > to build low latency data pipelines & Experimentation framework. > > 3. Improving Kafka at-least-once performance > *Speaker: Ying Zheng, Uber* > *Abstract:* > Abstract: > At Uber, we are seeing an increased demand for Kafka at-least-once > delivery. So far, we are running a dedicated at-least-once Kafka cluster > with special settings. With a very low workload, the dedicated > at-least-once cluster has been working well for more than a year. Now, when > we want to turn on at-least-once producing on all the Kafka clusters, the > at-least-once producing performance is one of the concerns. I have worked a > couple of months to investigate the Kafka performance issues. With Kafka > code changes and Kafka / Java configuration changes, I have reduced > at-least-once producing latency by about 60% to 70%. Some of those > improvements can also improve the general Kafka throughput or reducing > end-to-end Kafka latency, when ack = 0 or ack = 1. >
