- Differential Dataflow - The code is ugly Rust, but the logic and linked papers are quite interesting.
- Spinning Fast Iterative Dataflows - Flink's execution model. Also, coverage in the Morning Paper.
- Discretized Streams - Spark Streaming's model of operation.
- Google's Dataflow Model - This is now also available as Apache (Incubating) Beam.
- Kafka Streams - Kafka offers "hipster stream processing," and a nice unification between tables and streams.
cons = fn (a, b) -> fn x -> x.(a, b) end end | |
car = fn (p) -> p.(fn (q, _) -> q end) end | |
cdr = fn (p) -> p.(fn (_, q) -> q end) end | |
each = fn (list, func) -> | |
iter = fn (list, func, next) -> | |
(fn (a, nil) -> func.(a) | |
(a, b) -> func.(a); next.(b, func, next) | |
end).(car.(list), cdr.(list)) | |
end | |
iter.(list, func, iter) |
-- The meta-circular interpreter from section 5 of Reynolds's Definitional | |
-- Interpreters for Higher Order Programming Languages | |
-- (http://www.cs.uml.edu/~giam/91.531/Textbooks/definterp.pdf) | |
data EXP | |
= CONST Const | |
| VAR Var | |
| APPL Appl | |
| LAMBDA Lambda | |
| COND Cond |
- 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
// Eric Wolfe: Added support for checking if mobile radios are enabled on the device | |
// Original source: http://www.enigmaticape.com/blog/determine-wifi-enabled-ios-one-weird-trick | |
#import <Foundation/Foundation.h> | |
#import <ifaddrs.h> | |
#import <net/if.h> | |
#import <SystemConfiguration/CaptiveNetwork.h> | |
@interface ERWNetworkStatus : NSObject |
At DICOM Grid, we recently made the decision to use Haskell for some of our newer projects, mostly small, independent web services. This isn't the first time I've had the opportunity to use Haskell at work - I had previously used Haskell to write tools to automate some processes like generation of documentation for TypeScript code - but this is the first time we will be deploying Haskell code into production.
Over the past few months, I have been working on two Haskell services:
- A reimplementation of an existing socket.io service, previously written for NodeJS using TypeScript.
- A new service, which would interact with third-party components using standard data formats from the medical industry.
I will write here mostly about the first project, since it is a self-contained project which provides a good example of the power of Haskell. Moreover, the proces
tl;dr: how about a virtual global flat LAN that maps static IPs to onion addresses?
[We all know the story][1]. Random feature gets unintentionally picked up as the main reason for buying/using a certain product, despite the creator's intention being different or more general. (PC: spreadsheets; Internet: porn; smartphones: messaging.)
#!/usr/bin/env python | |
""" | |
Usage: hosts.py [options] | |
Options: | |
-h, --help show this help message and exit | |
-r REGION, --region=REGION | |
Region (default us-east-1) | |
""" |
It's with a heavy heart that I announce that Friday, May 31 2013 will be my last day at Heroku.
How can I possibly put into words what Heroku has meant to me these last six years? I can say it was a tremendous experience; or the opportunity of a lifetime; or the greatest thing I have ever been a part of. I can say that Heroku has been my life's work, as I did recently in a public blog post. All of those things are true, but none seem to capture the enormity of what's transpired these past six years.
I tend to focus on mechanical elements of a company: product, code, design, process. But what has surprised me the most at Heroku is that none of these things is the best part. The best part is the team.
I've never had the chance to work with a more singular group of people. Talented, passionate, skilled, dedicated. Most of all, sharing a set of values: elegance, craft, maniacal focus on simplicity; and an uncompromising belief that the future will be made of software, and how that software gets made will shape