Andrew Gwozdziewycz apg

Subject: Round 20: Happy Hacking!

Hello Hackers-

(This wrap up is a little late--you can blame life.)

Thanks to Lot18 for hosting us! BTW, if it wasn't obvious from all the wine, they sell wine online.

Last month's wrap up "fun way to spend some time"

Round 30: Things We Say

Hello Hackers.

Thank you to The Ladders for hosting Round 30, and providing pizza and alcohol. Not unlike any other company in NYC, they're hiring, and because they were so nice to us, we repeat that here. They've hired a few Hacker Schoolers, none of which run away, which says something good about their culture. Reach out to John Connolly if you're interested: [email protected]

Projects

Aditya Mukerjee

Internet Scale Services Checklist

A checklist for designing and developing internet scale services, inspired by James Hamilton's 2007 paper "On Desgining and Deploying Internet-Scale Services."

http://mvdirona.com/jrh/talksandpapers/jamesrh_lisa.pdf

Basic tenets

Does the design expect failures to happen regularly and handle them gracefully?
Have we kept things as simple as possible?

General Background and Overview

Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

Streaming Systems:

Differential Dataflow: https://github.com/frankmcsherry/timely-dataflow - The code is ugly Rust, but the logic and linked papers are quite interesting.
Spinning Fast Iterative Dataflows: http://vldb.org/pvldb/vol5/p1268_stephanewen_vldb2012.pdf - Flink's execution model. See also http://us9.campaign-archive2.com/?u=4188b6afbe9e5d43111fef4d4&id=46ab8c2adf&e=04a33a53a5
Discretized Streams: http://www.cs.berkeley.edu/~matei/papers/2013/sosp_spark_streaming.pdf - Spark Streaming's model of operation.
Google's Dataflow Model: http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43864.pdf - This is now also available as Apache (Incubating) Beam https://wiki.apache.org/incubator/BeamProposal

Streaming More Generally:

Algorithms + Data Structures: https://gist.github.com/debasishg/8172796

Make it real

Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discuss around concrete examples, not hand-waving abstractions. Don't say you did something, provide a URL that proves it.

Ship it

Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.

	DCPU-16 Specification
	Copyright 1985 Mojang
	Version 1.7



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	* 16 bit words
	* 0x10000 words of ram