Re: Big Data Meetup @ LinkedIn tomorrow at 5:30pm
Yes, the event will be recorded and we will be posting the link on our website - http://pinot.apache.org/ Cheers, Shraddha On Mar 26, 2019, at 9:40 PM, Seunghyun Lee mailto:sn...@apache.org>> wrote: I think that it will probably be recorded. Let me double check on this tomorrow and will get back to you. On Tue, Mar 26, 2019 at 9:16 PM Sai Boorlagadda mailto:sai.boorlaga...@gmail.com>> wrote: Is this streamed or recorded? On Tue, Mar 26, 2019 at 9:08 PM Seunghyun Lee mailto:sn...@apache.org>> wrote: Hi all, I just found that we have advertised on the website but not in the mailing list about the meetup happening tomorrow. LinkedIn is hosting a Big Data Meet Up(focused on Pinot and Presto) on Mar 27 from 5:30PM - 9:00 PM. Come join us and learn about the different OLAP systems that are powering companies like LinkedIn, Facebook, Uber and Slack. Please RSVP using the link below: https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsuperchargedolap.splashthat.comdata=02%7C01%7Cssahay%40linkedin.com%7Ca4c7d205044141cd30b008d6b26e48c2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C636892584068692694sdata=QbIFuNpP4PnYvYgYCI%2Bpg3Yb3mioh4A1Do404WZV84A%3Dreserved=0 Best, Seunghyun
Re: Big Data Meetup @ LinkedIn tomorrow at 5:30pm
I think that it will probably be recorded. Let me double check on this tomorrow and will get back to you. On Tue, Mar 26, 2019 at 9:16 PM Sai Boorlagadda wrote: > Is this streamed or recorded? > > On Tue, Mar 26, 2019 at 9:08 PM Seunghyun Lee wrote: > > > Hi all, > > > > I just found that we have advertised on the website but not in the > mailing > > list about the meetup happening tomorrow. > > > > LinkedIn is hosting a Big Data Meet Up(focused on Pinot and Presto) on > Mar > > 27 from 5:30PM - 9:00 PM. Come join us and learn about the different OLAP > > systems that are powering companies like LinkedIn, Facebook, Uber and > > Slack. > > > > Please RSVP using the link below: > > > > https://superchargedolap.splashthat.com > > > > Best, > > Seunghyun > > >
Re: Apache Pinot Dev,uSer, Committer mailing lists
Thank you for your interest in contributing to Pinot! I think that you can start to read documentation and get familiarized with the code base. https://pinot.readthedocs.io/en/latest/dev_guide.html Also, please join to slack channel using the below link. https://join.slack.com/t/apache-pinot/shared_invite/enQtNDY4NDczOTYyNjk1LTExODVjY2QxYzBkMzJjNTk0ZGQ3NThiYTU2YzdlNjE0MWI5ZjUwYjI2ZTgxNjNiYWJiNmEzYjkxMTIzMzUxNTQ In terms of the roadmap, some major features that we are currently working are: 1. segment merge service 2. HCON based configs 3. distributed controllers I think that other people can add more information about the roadmap. If you have some ideas on new features, feel free to suggest and we can discuss. Also, if you happen to live in bay area, please join to the meetup tomorrow. Most of contributors will be there :) https://superchargedolap.splashthat.com Best, Seunghyun On Tue, Mar 26, 2019 at 8:50 PM Sai Boorlagadda wrote: > I am also interested to get involved and contribute to the community. > Do we have a roadmap of things that we want to do? > > On Tue, Mar 26, 2019 at 5:00 PM Seunghyun Lee wrote: > > > Hi Sujay, > > > > Welcome to Pinot community. Please let us know if you have any question > or > > you want to discuss on Pinot > > > > Best, > > Seunghyun > > > > On Sun, Mar 24, 2019 at 4:31 AM sujay hegde > > wrote: > > > > > Hi Apache Pinot, > > > > > > I am interested in Apache Pinot Dev, user and Committer communities. > > > > > > > > > Thanks and Regards, > > > Sujay > > > > > >
Re: Big Data Meetup @ LinkedIn tomorrow at 5:30pm
Is this streamed or recorded? On Tue, Mar 26, 2019 at 9:08 PM Seunghyun Lee wrote: > Hi all, > > I just found that we have advertised on the website but not in the mailing > list about the meetup happening tomorrow. > > LinkedIn is hosting a Big Data Meet Up(focused on Pinot and Presto) on Mar > 27 from 5:30PM - 9:00 PM. Come join us and learn about the different OLAP > systems that are powering companies like LinkedIn, Facebook, Uber and > Slack. > > Please RSVP using the link below: > > https://superchargedolap.splashthat.com > > Best, > Seunghyun >
Big Data Meetup @ LinkedIn tomorrow at 5:30pm
Hi all, I just found that we have advertised on the website but not in the mailing list about the meetup happening tomorrow. LinkedIn is hosting a Big Data Meet Up(focused on Pinot and Presto) on Mar 27 from 5:30PM - 9:00 PM. Come join us and learn about the different OLAP systems that are powering companies like LinkedIn, Facebook, Uber and Slack. Please RSVP using the link below: https://superchargedolap.splashthat.com Best, Seunghyun
Re: Apache Pinot Dev,uSer, Committer mailing lists
I am also interested to get involved and contribute to the community. Do we have a roadmap of things that we want to do? On Tue, Mar 26, 2019 at 5:00 PM Seunghyun Lee wrote: > Hi Sujay, > > Welcome to Pinot community. Please let us know if you have any question or > you want to discuss on Pinot > > Best, > Seunghyun > > On Sun, Mar 24, 2019 at 4:31 AM sujay hegde > wrote: > > > Hi Apache Pinot, > > > > I am interested in Apache Pinot Dev, user and Committer communities. > > > > > > Thanks and Regards, > > Sujay > > >
Re: Pinot VS Kafka Streams (or Spark SQL)
Thanks, Seunghyun for confirming my understanding. On Tue, Mar 26, 2019 at 5:06 PM Seunghyun Lee wrote: > Hi Sai, > > Thank you for the mail. Your understanding is correct. > > Systems that you mentioned (Pinot, Kafka, Spark SQL) are built for > different purposes and they are all critical components when you need to > build the data analytics data pipeline. > > Kafka is a pub-sub message delivering system that is usually used to build > the streaming data pipeline. Spark SQL is built to add SQL interface layer > on top of Spark. You can think it as one of offline OLAP query engines like > Hive or Presto that are used for computing complex ad-hoc queries over > large data. > > Pinot aims to support "interactive" analytics use cases (e.g. dashboard, > site facing reporting - who's viewed my profile on LInkedIn) where latency > requirements are more strict than offline reporting use cases. > > You mentioned that "I can write a consumer that processes events from a > stream and computes the needed analytic/metric and store it into a data > store to serve". This is basically what Pinot does (consuming data from a > stream, index it for serving, allow query interface) > > Below links are some references that we have published to public. Please > let us know if you have any other question. > > Best, > Seunghyun > > cc. > > LinkedIn Blog Posts > > https://engineering.linkedin.com/analytics/real-time-analytics-massive-scale-pinot > https://engineering.linkedin.com/blog/2019/03/pinot-joins-apache-incubator > > Slides > https://www.slideshare.net/jeanfrancoisim/intro-to-pinot-20160104 > > https://www.slideshare.net/seunghyunlee1460/pinot-realtime-olap-for-530-million-users-sigmod-2018-107394584 > > On Tue, Mar 26, 2019 at 3:46 PM Sai Boorlagadda > > wrote: > > > Hello Devs, > > > > Is there any content or blog post to understand the difference between > > Pinot vs Kafka Streams (or Spark SQL)? At a high level after reading > Pinot > > is actually bringing off-the-shelf components which otherwise data > > engineers have to write on top of KAFKA streams? > > > > I mean I can write a consumer that processes events from a stream and > > computes the needed analytic/metric and store it into a data store to > > serve. Though my application layer has to route the requests either to > the > > streaming analytics datastore or batch analytics data store. > > > > So my understanding is Pinot abstracts these two things from the > > application. Is that correct? > > Sai > > >
Re: Pinot VS Kafka Streams (or Spark SQL)
Hi Sai, Thank you for the mail. Your understanding is correct. Systems that you mentioned (Pinot, Kafka, Spark SQL) are built for different purposes and they are all critical components when you need to build the data analytics data pipeline. Kafka is a pub-sub message delivering system that is usually used to build the streaming data pipeline. Spark SQL is built to add SQL interface layer on top of Spark. You can think it as one of offline OLAP query engines like Hive or Presto that are used for computing complex ad-hoc queries over large data. Pinot aims to support "interactive" analytics use cases (e.g. dashboard, site facing reporting - who's viewed my profile on LInkedIn) where latency requirements are more strict than offline reporting use cases. You mentioned that "I can write a consumer that processes events from a stream and computes the needed analytic/metric and store it into a data store to serve". This is basically what Pinot does (consuming data from a stream, index it for serving, allow query interface) Below links are some references that we have published to public. Please let us know if you have any other question. Best, Seunghyun cc. LinkedIn Blog Posts https://engineering.linkedin.com/analytics/real-time-analytics-massive-scale-pinot https://engineering.linkedin.com/blog/2019/03/pinot-joins-apache-incubator Slides https://www.slideshare.net/jeanfrancoisim/intro-to-pinot-20160104 https://www.slideshare.net/seunghyunlee1460/pinot-realtime-olap-for-530-million-users-sigmod-2018-107394584 On Tue, Mar 26, 2019 at 3:46 PM Sai Boorlagadda wrote: > Hello Devs, > > Is there any content or blog post to understand the difference between > Pinot vs Kafka Streams (or Spark SQL)? At a high level after reading Pinot > is actually bringing off-the-shelf components which otherwise data > engineers have to write on top of KAFKA streams? > > I mean I can write a consumer that processes events from a stream and > computes the needed analytic/metric and store it into a data store to > serve. Though my application layer has to route the requests either to the > streaming analytics datastore or batch analytics data store. > > So my understanding is Pinot abstracts these two things from the > application. Is that correct? > Sai >
Re: Apache Pinot Dev,uSer, Committer mailing lists
Hi Sujay, Welcome to Pinot community. Please let us know if you have any question or you want to discuss on Pinot Best, Seunghyun On Sun, Mar 24, 2019 at 4:31 AM sujay hegde wrote: > Hi Apache Pinot, > > I am interested in Apache Pinot Dev, user and Committer communities. > > > Thanks and Regards, > Sujay >
Pinot VS Kafka Streams (or Spark SQL)
Hello Devs, Is there any content or blog post to understand the difference between Pinot vs Kafka Streams (or Spark SQL)? At a high level after reading Pinot is actually bringing off-the-shelf components which otherwise data engineers have to write on top of KAFKA streams? I mean I can write a consumer that processes events from a stream and computes the needed analytic/metric and store it into a data store to serve. Though my application layer has to route the requests either to the streaming analytics datastore or batch analytics data store. So my understanding is Pinot abstracts these two things from the application. Is that correct? Sai
