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mrflip / datasets.md
Created Aug 9, 2012
Overview of Datasets
View datasets.md

== Overview of Datasets ==

The examples in this book use the "Chimpmark" datasets: a set of freely-redistributable datasets, converted to simple standard formats, with traceable provenance and documented schema. They are the same datasets as used in the upcoming Chimpmark Challenge big-data benchmark. The datasets are:

  • Wikipedia English-language Article Corpus (wikipedia_corpus; 38 GB, 619 million records, 4 billion tokens): the full text of every English-language wikipedia article, in

  • Wikipedia Pagelink Graph (wikipedia_pagelinks; ) --

  • Wikipedia Pageview Stats (wikipedia_pageviews; 2.3 TB, about 250 billion records (FIXME: verify num records)) -- hour-by-hour pageview

@mrflip
mrflip / CareerDayInterview-20180411.md
Last active Apr 20, 2018
Career Day Interview with Ethan Grigsby
View CareerDayInterview-20180411.md

Career Day Interview with Ethan Grigsby

What is your name? What is your career?

My name is Flip Kromer, I’m an inventor and entrepreneur — meaning that I start businesses from scratch. Added all up, the companies I’ve started earn tens of millions each year in revenue, and have grown from a couple friends at the start to create more than eighty highly satisfying jobs.

What do you do at your job?

My latest company is Vigilante, a restaurant with more than 150 board games to play right at your table. I designed and worked to build special tables that make playing board games super awesome: dice, chargers, card holders and other fun things are built into the table. Probably the most magical feature is that each table has a robot above it — when you push the button at your seat the robot waves its arms, which tells the server to come over and take your order or bring you a fork or help you with a game. I custom designed the mechanics of the robot and the tiny computers inside each robot and each table

View Wood FAQ.md

Veneer is obtained either by "peeling" the trunk of a tree or by slicing large rectangular blocks of wood known as flitches. The appearance of the grain and figure in wood comes from slicing through the growth rings of a tree and depends upon the angle at which the wood is sliced. There are three main types of veneer-making equipment used commercially:

A rotary lathe in which the wood is turned against a very sharp blade and peeled off in one continuous or semi-continuous roll. Rotary-cut veneer is mainly used for plywood, as the appearance is not desirable because the veneer is cut concentric to the growth rings.

A slicing machine in which the flitch or piece of log is raised and lowered against the blade and slices of the log are made. This yields veneer that looks like sawn pieces of wood, cut across the growth rings; such veneer is referred to as "crown cut".

A half-round lathe in which the log or piece of log can be turned and moved in such a way as to expose the most interesting parts of the grain, c

@mrflip
mrflip / 2017 RSS Christmas Quiz - ROT13.md
Created Jan 6, 2018
Solutions for 2017 RSS Christmas Quiz, ROT13 encoded
View 2017 RSS Christmas Quiz - ROT13.md

EFF 2017 Puevfgznf Dhvm

1.  …TB!  [10 cbvagf]

  • Nyy ner anzrq Nyblfvhf
  • Nyy ner fheanzrq Cnexre
  • Ynql Crarybcr’f SNO 1, 2, 3 va “Guhaqreoveqf ner Tb!” (srnghevat ure punhssrhe Nyblfvhf Cnexre)

(n) Jung pbaarpgf gur sbyybjvat?

  • Nyblfvhf Fahssyhcnthf, Ovt Oveq’f orfgvr sebz Frfnzr Fgerrg — N funttl oebja perngher jvgu n gnyy, lryybj sevraq
  • Puvrs Nyblfvhf bs gur Fnagn Ebfn CQ va Vg’f n Znq, Znq, Znq, Znq Jbeyq — Puvrs bs gur ‘FECQ’ va n pbzrql jubfr gvgyr pbagnvaf n dhnqehcyr ercrng
@mrflip
mrflip / 2017 RSS Christmas Quiz.md
Last active Jan 6, 2018
Solutions by my brother Matt, my mom and me for the 2017 RSS Christmas quiz
View 2017 RSS Christmas Quiz.md

RSS 2017 Christmas Quiz

1.  …GO!  [10 points]

  • All are named Aloysius
  • All are surnamed Parker
  • Lady Penelope’s FAB 1, 2, 3 in “Thunderbirds are Go!” (featuring her chauffeur Aloysius Parker)

(a) What connects the following?

  • Aloysius Snufflupagus, Big Bird’s bestie from Sesame Street — A shaggy brown creature with a tall, yellow friend
  • Chief Aloysius of the Santa Rosa PD in It’s a Mad, Mad, Mad, Mad World — Chief of the ‘SRPD’ in a comedy whose title contains a quadruple repeat
@mrflip
mrflip / notes_and_links.md
Created Mar 21, 2012
Notes for ISchool class
View notes_and_links.md
@mrflip
mrflip / 2014 TED w Friday.md
Last active Dec 24, 2016
Notes from the 2014 TED conference
View 2014 TED w Friday.md

TED 2014 Friday

Friday mid-Morning: Onward (final session)

Andrew Solomon, author

  • Reports on experience of people in extreme circumstances
  • Avoidance and Endurance
  • Take traumas and make them part of who you'll be
  • Mother of a child due to rape: I think of him (rapist) with pity -- he has a beautiful daughter he doesn't know, and I do, and so I’m the lucky one
View consistent_vote_counts_in_cassandra-example_data.txt
votes CF
"back in black" => { 201005211200 => '1', 201005201159 => '1', 201005201157 => '1', 201005011900 => '1', 201004190600 => '1' },
"black album" => { 201005021800 => '1', 201005010600 => '1' },
"black star" => { 201005011000 => '1' }
cached_counts CF
"back in black" => { 'cached_count' => 2, 'counted_until' => 201005011931 },
"black album" => { 'cached_count' => 1, 'counted_until' => 201005010600 }
@mrflip
mrflip / KafkaState.java
Created Jun 29, 2013
Trident Kafka State
View KafkaState.java
package com.infochimps.storm.trident;
import kafka.javaapi.producer.Producer;
import kafka.javaapi.producer.ProducerData;
import kafka.message.Message;
import kafka.serializer.Encoder;
import kafka.producer.ProducerConfig;
import backtype.storm.task.IMetricsContext;
import storm.trident.operation.TridentCollector;
View performance_qualification.md

Performance Qualification

Identify all reasons why (eg) Elasticsearch cannot provide acceptable performance for standard requests and Qualifying load. The "Qualifying load" for each performance bound is double (or so) the worst-case scenario for that bound across all our current clients.

  • Performance
    • bandwidth (rec/s, MB/s) and latency (s) for 100B, 1kB, 100kB records
    • under read, write, read/write
    • in degraded state: a) loss of one/two servers and recovering; b) elevated packet latency + drop rate between "regions"
    • High concurrency
  • keepalive