BASE Meeting #25, Monday 10th May, 7pm, LinkedIn in Mountain View

[Dick Wall]

http://svscala.ning.com/events/base-meeting-25-monday-10th

Our 25th meeting - I guess we are more than a flash-in-the-pan now.

IMPORTANT: Due to re-modelling work, the meeting this month will be in
the LinkedIn kitchen area, rather than the usual presentation area.
Please see below for details of where to go.

This month we have a couple of Berkeley PhD students talking about
distributed computing. In particular the spark and scads projects. We
also have a couple of lightning talks and some announcements, plus
pizza courtesy of LinkedIn.

As always, please try to arrive a few minutes early to get into the
building and registered.

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[Dhananjay Ragade]

I've set up a Google spreadsheet to get an idea of how much pizza we
should order :)

https://spreadsheets.google.com/viewform?formkey=dER0WjZJSFZ6WWRadXlnaUdlY1J1WGc6MQ

thanks,
Dhananjay

--
--
Dhananjay Ragade
rag...@alum.mit.edu

[Dick Wall]

More details on tonight's meeting.

The subjects (which really do look riveting this evening) are as
follows:

Michael Armbrust will talk on:
Large-scale, user-facing applications are increasingly moving from
relational databases to distributed key/value stores for high-request-
rate, low-latency workloads. Often, this move is motivated not only by
key/value stores’ ability to scale simply by adding more hardware, but
also by the easy to understand predictable performance they provide
for all operations. For complex queries, this approach often requires
onerous explicit index management and imperative data lookup by the
developer. We propose PIQL, a Performance Insightful Query Language
that allows developers to express many queries found on these websites
while still pro- viding strict bounds on the number of I/O operations
that will be performed.

And Matei Zaharia on:
Although the MapReduce programming model has been highly successful,
some applications are not well-suited to MapReduce. We present Spark,
a framework optimized for one such type of applications - iterative
jobs where a dataset is shared across multiple parallel operations, as
is common in machine learning algorithms. Spark provides a functional
programming model similar to MapReduce, but also lets users ask for
data to be cached between iterations, leading to up to 10x better
performance than Hadoop on some jobs. This is achieved while
preserving MapReduce's fault tolerance. Spark also makes programming
jobs easy by integrating cleanly into the Scala programming language
(a high-level language on the JVM), so that parallel operations look
like loops. Finally, the ability of Spark to load a dataset into
memory and query it repeatedly makes it especially suitable for
interactive analysis of big datasets. We have modified the Scala
interpreter to make it possible to use Spark interactively in this
manner, providing a significantly more responsive experience than Hive
and Pig.

See you there. If you haven't done so already, please be sure and
register for Pizza (if you want some).

http://www.google.com/url?sa=D&q=https://spreadsheets.google.com/viewform%3Fformkey%3DdER0WjZJSFZ6WWRadXlnaUdlY1J1WGc6MQ&usg=AFQjCNFsnwjnSXMJm7JJjoL635oZoDzl7g

On May 7, 2:09 pm, Dhananjay Ragade <drag...@gmail.com> wrote:
> I've set up a Google spreadsheet to get an idea of how much pizza we
> should order :)
>

> https://spreadsheets.google.com/viewform?formkey=dER0WjZJSFZ6WWRadXln...

>
> thanks,
> Dhananjay
>
>
>
>
>
> On Wed, May 5, 2010 at 10:14 AM, Dick Wall <dickw...@gmail.com> wrote:
> >http://svscala.ning.com/events/base-meeting-25-monday-10th
>
> > Our 25th meeting - I guess we are more than a flash-in-the-pan now.
>
> > IMPORTANT: Due to re-modelling work, the meeting this month will be in
> > the LinkedIn kitchen area, rather than the usual presentation area.
> > Please see below for details of where to go.
>
> > This month we have a couple of Berkeley PhD students talking about
> > distributed computing. In particular the spark and scads projects. We
> > also have a couple of lightning talks and some announcements, plus
> > pizza courtesy of LinkedIn.
>
> > As always, please try to arrive a few minutes early to get into the
> > building and registered.
>
> > --
> > You received this message because you are subscribed to the Google Groups "Bay Area Scala Enthusiasts" group.
> > To post to this group, send email to scala...@googlegroups.com.
> > To unsubscribe from this group, send email to scala-base+...@googlegroups.com.

> > For more options, visit this group athttp://groups.google.com/group/scala-base?hl=en.

[Vlad Patryshev]

Knock-knock,

Can we have the slides from the last talk please? (I'd love to see if
the the parallel infrastructure from one of the talks is applicable to
Simon Peyton Jones' example from his Data parallel Haskell talk.)