Re: ML in Heron weekly meeting
@Dave Apache Samoa seemed like a good starting point as they’ve already implemented a set of algorithms as storm topologies, additionally regardless of whether that community is active , we could still take that code and iterate on it within heron as a good starting point. To that end I feel the biggest challenge with the machine learning initiative is figuring out the exact use cases and operationalizing ml topologies within heron. Sent from my iPhone > On Jul 5, 2018, at 3:11 PM, Ning Wang wrote: > > Hmm. Good question. Maybe not yet reaching out. > > > >> On Thu, Jul 5, 2018 at 11:49 AM, Dave Fisher wrote: >> >> Hi - >> >> Has anyone reached out to the SAMOA podling? Or is their architecture >> inverted from that being proposed I’m not sure how well the SAMOA community >> is doing as they have had low activity since early this year. >> >> Regards, >> Dave >> >>> On Jun 29, 2018, at 11:01 PM, Ning Wang wrote: >>> >>> Brief notes for the meeting on June 29: >>> >>> - We need to hook up heron with Apache samoa. Saikat to create new issues >>> in github. >>> - Create a slack channel: #machine-learning >>> - Let's add potential use cases in the design doc: >>> https://docs.google.com/document/d/1LrO7XRcMxJoMM83wjRd- >> Ov74VAaomA_mXOAhCStgGng/edit >>> >>> On Sat, Jun 23, 2018 at 3:44 PM, Ning Wang wrote: Brief notes for the meeting on June 22th: - still studying the documents. --- https://mapr.com/blog/monitoring-real-time-uber-data-using- spark-machine-learning-streaming-and-kafka-api-part-2/ --- https://databricks.com/blog/2018/06/05/introducing-mlflow-an -open-source-machine-learning-platform.html --- https://eng.uber.com/michelangelo/ - stateful storage might need to be improved (data size) to support big state object which could be required by ML jobs. >> >>
Re: ML in Heron weekly meeting
Hmm. Good question. Maybe not yet reaching out. On Thu, Jul 5, 2018 at 11:49 AM, Dave Fisher wrote: > Hi - > > Has anyone reached out to the SAMOA podling? Or is their architecture > inverted from that being proposed I’m not sure how well the SAMOA community > is doing as they have had low activity since early this year. > > Regards, > Dave > > > On Jun 29, 2018, at 11:01 PM, Ning Wang wrote: > > > > Brief notes for the meeting on June 29: > > > > - We need to hook up heron with Apache samoa. Saikat to create new issues > > in github. > > - Create a slack channel: #machine-learning > > - Let's add potential use cases in the design doc: > > https://docs.google.com/document/d/1LrO7XRcMxJoMM83wjRd- > Ov74VAaomA_mXOAhCStgGng/edit > > > > > > On Sat, Jun 23, 2018 at 3:44 PM, Ning Wang wrote: > > > >> Brief notes for the meeting on June 22th: > >> > >> - still studying the documents. > >>--- https://mapr.com/blog/monitoring-real-time-uber-data-using- > >> spark-machine-learning-streaming-and-kafka-api-part-2/ > >>--- https://databricks.com/blog/2018/06/05/introducing-mlflow-an > >> -open-source-machine-learning-platform.html > >>--- https://eng.uber.com/michelangelo/ > >> - stateful storage might need to be improved (data size) to support big > >> state object which could be required by ML jobs. > >> > >
Re: ML in Heron weekly meeting
Hi - Has anyone reached out to the SAMOA podling? Or is their architecture inverted from that being proposed I’m not sure how well the SAMOA community is doing as they have had low activity since early this year. Regards, Dave > On Jun 29, 2018, at 11:01 PM, Ning Wang wrote: > > Brief notes for the meeting on June 29: > > - We need to hook up heron with Apache samoa. Saikat to create new issues > in github. > - Create a slack channel: #machine-learning > - Let's add potential use cases in the design doc: > https://docs.google.com/document/d/1LrO7XRcMxJoMM83wjRd-Ov74VAaomA_mXOAhCStgGng/edit > > > On Sat, Jun 23, 2018 at 3:44 PM, Ning Wang wrote: > >> Brief notes for the meeting on June 22th: >> >> - still studying the documents. >>--- https://mapr.com/blog/monitoring-real-time-uber-data-using- >> spark-machine-learning-streaming-and-kafka-api-part-2/ >>--- https://databricks.com/blog/2018/06/05/introducing-mlflow-an >> -open-source-machine-learning-platform.html >>--- https://eng.uber.com/michelangelo/ >> - stateful storage might need to be improved (data size) to support big >> state object which could be required by ML jobs. >> signature.asc Description: Message signed with OpenPGP
