Tuesday, June 26, 2012

UberConf 2012 notes



Ken Sipe

Complexity of ComplexityPDF

by Ken Sipe - Wednesday 3:15 PM


 

Essential complexity = plane 
Accidental complexity = Indian power lines 
V1 user does not like 
V2 overly complex 

Everything is diffing mental models 
Size of team matters adding ppl is counterproductive 

Application of knowledge, level of experience 

Dreyfus model 

Experts create recipes for novices and advanced beginners 

Brian Goetz, extending Java with backward comp 

1952 
Make coding comprehensible 

Test reviews more important than code reviews 

2.0 - 0.9 = 0.89999999 
Have to have humans working on code that understand this 

Possible to create obj hierarchy where legal equals is not possible 

Must use most powerful language at disposal 

Increased flexibility = increased complexity 

ESB - complexity does not go away, need to be smart 
Internals are not standardized 

CAP Availability = caching 
"if u can't split it u can't scale it" shoelz eBay 

Level 3 = competent
Super observer sees all consistency - not necessary? 

What is core business? Can solve with fault tolerant hardware instead of sware complexity? 

Context... Hard problem 
Google talk hardest problem is social graph (friend status) 
IO throughput, CPU throughput, two solutions 

Request, asynchronous mq, response 
Don't cache preemptively
Ken Sipe

MongoDB: Scaling Web ApplicationsPDF

by Ken Sipe - Wednesday 5:00 PM


 

Sharing 3x3 is magic 
3 shards, replicate sets
Pratik Patel

Mobile Performance Tips n' TricksPDF

by Pratik Patel - Wednesday 5:00 PM


 

Blaze.io/testing
Brian Sletten

Visualizing Data on the WebPDF

by Brian Sletten - Wednesday 8:30 PM


 

Preattentive 200ms 

Stevens power law ppl find length easier to perceive than area - pie charts are harder to understand 

Show the data - don't accentuate, "lie factor" 

Max ideas presented min time, min ink, min space 
"Chart junk" 

Spark lines, word-size graphics, eg glucose level inline with text 

Jquery sparkling 
Rgraph 
Highcharts commercial eg Gatling 
Raphael 
D3 data drives with little code, based on protovis 
- multivariate relationships 
- parallel coordinates 100g 
Tangle worrydream, Bret Victor 
- interactive document 
exhibit, simile-widgets 

Flowingdata.com "visualize this" book 

Many eyes IBM 
Selection.datavisualization.ch 
inmaps.linkedinlabs.com
Neal Ford

Clojure Workshop

by Neal Ford - Thursday 9:00 AM



Watch Rich Hickey videos 

Dynamic 
Strongly typed 
Functional 
High-performance 
Lisp 

Homoiconic 
Only references are mutable 

Regex #"" 
Symbols 
Keywords special symbols :foo ::foo, constant intern strings 
Data literals 
-List. Singly linked insert at front () 
-Vector. Indexed, insert at rear [] 
-Map key/value {:} 
-Set #{} 

Few data structures many functions 

Seq interface


Convert Groovy NodeChild xml element to XML string

new groovy.xml.StreamingMarkupBuilder().bindNode(nodeChild) as String

Monday, June 25, 2012

ElasticSearch terminology

Relational DB ⇒ elasticsearch
database ⇒ index
table ⇒ type
row ⇒ document
column ⇒ field
schema ⇒ mapping
index ⇒ everything is indexed
SQL ⇒ query DSL

Sunday, June 24, 2012

Kibana: A brower based log analysis tool for Logstash and ElasticSearch


You have logs. Billions of lines of data. You shipped, dated it, parsed it and stored it. Now what do you do with it? Now you make sense of it. Kibana helps you do that. Kibana is an alternative browser based interface for Logstash and ElasticSearch that allows you to efficiently search, graph, analyze and otherwise make sense of a mountain of logs. 


Wednesday, June 20, 2012

Installing Clojure

Neo4j

Download from: http://neo4j.org/download_a/
Start server
Connect: http://localhost:7474/webadmin
or
http://localhost:7474/db/data/

Thursday, June 7, 2012