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The Ultimate Guide to the Standup Desk

I'm on my 6th month of using a standup desk. I waited a bit before writing this so I wasn't on my high horse writing about something then abandoning it after a month. First a little historyâ�¦ several years ago I injured by back pretty bad playing ice hockey and was bed ridden for weeks. The pain lasted almost a full year before I could do normal things again. Turned out it was a ruptured disk in my back and limited what I could/couldn't do going forward. I've also had a desk job programming since I was 18 years old (now 35) so that wasn't helping. Since then I've had ongoing back pain while working and sitting all day.Several months ago I saw a post on hacker news that kind of just woke me up. I've always wanted to try a fancy standing desk but didn't want to invest the money if I wasn't going to use it. The post was here: http://gregschlom.com/post/4555981908/standing-desk It woke me up to the fact I could just use a freaking chair or some boxes to start out with and didn't have to wait for anything, and that day that's exactly what I did. I threw a chair up on a desk and used my laptop on there for the rest of the afternoon. The chair was kind of inconvenient with wobbling and other issues, so I threw a set of drawers upside down and away I went. Here's the first picture I took of my new set up. It's crude but worked!

Close your laptop and pay attention

I recall a meeting in my stint at Panasonic when I was presenting my plan for a unified content and delivery system for in air applications and media suppliers. It had all the big wigs up to our VP of Engineering. I worked on my pitch as to why this was the right move going forward for the company and had all the relevant points to combat devil's advocates. I had been in many product pitch meetings so I was used to now seeing many people tuned out, attached to their keyboards. I vowed when my turn came that I would not let this happen as countless times I've heard in those meetings "I'm sorry, what did you say again?".

When I saw the clock struck 3pm I waited a few minutes for the attendees to take their seats. There were probably 30 or so people in the meeting as the golden rule in enterprise is "The more people's time you can waste the better". I sat there with the opening slide up, not saying a word. Eventually, minutes later the VP looked up and said "Are we starting this meeting?" I replied "Yes, as soon as all the laptops including yours are put away". There was a quiet moment of semi shock as most people didn't believe I actually just said that, but that is the beauty of a strong engineering market. When you don't fear for your job you're able to actually get work done. A little bit taken aback everyone closed their laptops and the meeting commenced. The meeting continued as planned and the project was green lighted and is still in place years later.

Startup Lesson: Why a Vacation is not just good for you

When I was in my first few Months at McAfee (Foundstone Security startup at the time) we had just finished version x of our Enterprise focused Vulnerability Scanning software. There was a lull between releases as customers started getting the new rollout of the software as it passed through our QA department (hi John!). It was a long march to the finish, the team lead (let's call him Dietrich, cause that was his name) at the time decided a much needed break was in order and he was going to head to Joshua tree for a weekend camping trip (which was purposely I think out of cell range) with the family. He left on a Thursday and wouldn't be back until the following Monday. I was next in charge in the dev team for the web side of the application and still wasn't quite up to speed on some of the core complexities of the application's internals and libraries. I thought how bad could it be, just a day to cover for him and Monday would be back to normal.

Friday afternoon our CTO and software manager ran over to my desk around 4:30pm and said "Customer X just found a major bug in the new release and we can't leave until we get a fix out for them". Customer X was our largest customer at the time and the deal was easily in the 7 figures so we all took it quite seriously. To be honest I cannot remember what the actual bug was right now, but I do remember be thrown into custom PHP extension hell(windows), a SOAP layer Dietrich had written himself(NuSOAP), and other internal libraries trying to track down where this semi-reproduceable bug was coming from. I also distinctly remember the CTO at the time getting pricing on helicopter services to actually fly to Joshua tree to pick Dietrich up as a solution was not readily presenting itself in the first hour and we couldn't get a hold of him. No pressure!

Loan Shark - Using the Loan Pattern in Scala

Today we're going to look at elegantly using the Loan Pattern in Scala. One of my big pet peeves on Java is how convoluted it is to read lines from a simple file. You're looking at 10-15 lines of code with opening/closing resources, try catches, etcâ�¦ (see here). This can be solved in Scala by making use of what's called the "Loan Pattern" (thanks to Chris Bissel for turning me on to this one). The loan pattern does exactly what it says it does, it loans a resource to a function of code. This let's you abstract away all the setup, managing, and closing of resources. Not only does this save a ton of time but it also has the side effect of reducing memory/resource leaks since the closing of those resources is abstracted away from the client code.

Here is an example of using the Loan Pattern to read lines of files in my /var/log/secure.log file and print them out to the console

How to accept command line parameters that pass to a Import Macro using Apache Pig 0.9

The docs don't specifically show an example of how to pass a command line parameter to a macro, but it does say you can't you use parameter substitution inside your Pig script. Below is an example of how to pass a command line argument through to your Pig Macro definition.

File 1 - A sample load location (schema.pig)

Load Balanced Actors with Akka and Scala

Below is some sample scala code that makes use of the Akka library to provide some examples of load balanced actors using Akka's available features.

The first thing we'll do is create an object to act as our manager that will create a series of actors for us, then a supervisor, then a load balancer. When we fire messages to the actors this configuration

will attempt a round robin style approach to distributing the messages across the actors. This is just a simple example that doesn't do any real work just to get you some boilerplate code for working with load balanced actors

Using flatmap in Scala

I was just reading Daniel Spiewak's blog regading the use of Scala's flatmap operation. It seems to be one of those confusing parts of Scala so I thought I'd post a clear example of how and why you'd want to use a flatmap on a list of things.

How to install Flume from a Tarball

This is a how to on installing the Cloudera Flume project from tarball and Ubuntu package

Installing Flume from tarball

My Todo workflow Video

Hi everyone,

just thought I'd throw up a new video of how I manage my day to day Todo list using a simple Todo.txt file inspired by todotxt.com/. So here is a video of how it works:

What happens when you are the #1 article on Hacker News

This post aims to open up the gates as to what to expect if you're fortunate to get an article featured on Hacker News. I've been a daily reader of HackerNews for months now and it's been a great source of interesting tech news. My general workflow is to scan articles in Reeder and push them to Instapaper to read fully later. If seeing these traffic patterns helps you in anyway, don't be afraid to drop me a tweet :) @jimplush

Yesterday I was surfing through a new site called Forrst thanks to an invite from @ka. I came across a resume mockup from Jamie Kite that I thought had some great ideas behind it. I crafted up a quick article and posted it to my blog with my own thoughts on it. I had just started the process of migrating my old blog to a new code base based on the Code Igniter framework. I wanted to have complete control of my blog, but it's been a challenge finding the time to actually finish it (For example I'm still putting my articles directly into my DB at this point). It was just a quick post to get some content going again.

This may be the best resume I have ever seen

UPDATE: Here is the resulting stats from all the Hacker News Traffic What happens when you are the #1 article on Hacker News

How to Auto Create Issues in Jira From PHP

Good morning again everyone, in an effort to always increase productivity and reduce friction I have a new weapon in my workflow arsenal. To gain some context regarding this post here is some background. We use Jira at Gravity for tracking issues and bugs. Since I'm not always on VPN or have access to our network managing my todos has been cumbersome. I've tried every Todo app out there and always fail to use them for more than 2 days.

I finally saw a great article on just using a simple Todo.txt file in your Dropbox folder and working from that. It's been a dream and working out great. I can use all my fav shell commands and have amazing Quicksilver integration that I'll show in a little video soon.

Anyway, the final joy was to be able to have a cron job run every hour and automatically create jira issues from my todo file for any item that has a #jira tag. That helps me sync with Jira when I want others to know what I have on my plate at the moment. My script that calls this PHP file strips out the #jira tag after it creates the issue

Goose - Article Extractor now open source, same as Flipboard/Instapaper

Today I'm releasing a project I worked on for http://gravity.com. It's an HTML Article Extractor ala Flipboard / Instapaper style. It will take an article, run some calculations on it and give you an Article object back with the text of the extracted Article as well as the main image that we think is relevant to the article.

http://github.com/jiminoc/goose/wiki

The goal is to create an open source article extractor for use with open source applications, crawlers or academic NLP processing initiatives.

JimPlush.com - New Blog Released

I spent part of the weekend moving my old blog http://www.litfuel.net/plush over to my new domain http://jimplush.com. I have been using some old, deprecated blogging software from 2005 and it has constantly been a pain to tweak and add new features to it. So I decided to finally bite the bullet and rewrite the whole thing from scratch.

My first decision was to roll my own or just use wordpress or some other mainstream blogging software but being a developer I wanted to reinvent the wheel yet again so I decided to roll my own. The next decision came down to what framework to use and what language. I've been using Zend Framework for a few years now, however after reading their updated tutorial I felt that it's jumped the shark into the over complicated for simple apps realm. I just wanted something simple, fast and intuitive. I settled on CodeIgniter as my framework for this blog. It's been amazingly fast and simple to use, definitely happy with my choice so far.

For syntax highlighting I'm using: http://alexgorbatchev.com/SyntaxHighlighter/ which is a javascript based solution. So far so good, supports almost all the languages I'd use so I'm good with that choice as well. I'm going to start plumbing in Redis for all my caching and number crunching. So I'll be posting about that as I move along

Why you should never read comments on blogs

Here is an article from 2005 on techcrunch: 85% of College Students use FaceBook

http://techcrunch.com/2005/09/07/85-of-college-students-use-facebook/

And here are some insightful comments from TechCrunchers as always:

Using the Python NLTK Bayesian Classifier for word sense disambiguation - 92% accuracy

Today's article will be going over some basic word sense disambiguation using the NLTK toolkit in Python and Wikipedia. Word sense disambiguation is the process of trying to determine if you mention the world "apple" are you talking about Apple the company or apple the fruit? I've read a few white papers on the subject and decided to try out some of my own tests to compare results. I also wanted to make it so no humans would be needed to see the initial data set and it could be done with data openly available. There are many example of classifiers out there but they all seem to focus on movie reviews so I figured another example may be helpful. Trained NLP professionals will perhaps balk on the simplistic approach but this is meant as more of an intro to NLTK and some of the things you can do with it.

I will demo this approach against real tweets from searching twitter for tweets with the word "apple" in them and creating a data set to test against. I suggest a winner take all vote off between 3 classification/similarity metrics. Jaccard Co-efficient, TF-IDF and Bayesian Classifiers. To the extent that if you were to run all three against an input tweet, whoever pulled 2 or more votes would win and give you a reasonable level of confidence. Although probably not the fastest solution, my goal is accuracy vs performance but your mileage may vary and also not trying to spend weeks developing involved solutions.

Here is a sample tweet: "I guess I'm making a stop at the Apple store along with my quest to find an ugly sweater tomorrow. boo!" It's easy for a human to determine we're talking about Apple the company in this tweet, however to a computer it's not so easy. We first need to find a dataset to seed our algorithms to compare against. Wikipedia has over 2 million ambiguous word definitions so it's important to not require manual training for each word or we'd never get anywhere. My first idea is to look at wikipedia itself. If you look at the disambiguation page for "apple" http://en.wikipedia.org/wiki/Apple_(disambiguation) you can see there are a couple entries of importance: Apple, Inc and apple the fruit. To seed my dataset I suggest grabbing each wikipedia page and storing the complete text of that topic page, along with following each link in the first paragraph and storing the text from each link against the Apple company corpus. So we're grabbing the text from http://en.wikipedia.org/wiki/Apple_Inc. , http://en.wikipedia.org/wiki/NASDAQ, http://en.wikipedia.org/wiki/Multinational_corporation , http://en.wikipedia.org/wiki/Consumer_electronics, along with all the other wiki links that are in the first paragraph of the Apple topic page. This would be something you could easily script out by looking at the openly available wiki dump pages. So this approach could be used for all the seed data for ambiguous words.

New Twitter Account

So I created a new twitter account should you care to follow: jimplush

http://twitter.com/#!/jimplush

Fix when compiling the Redis php extension on OSX - mach-o, but wrong architecture

If you happen to get the error:

PHP Warning: PHP Startup: Unable to load dynamic library '/Users/jim/Downloads/owlient-phpredis-2675d15/modules/redis.so' - dlopen(/Users/jim/Downloads/owlient-phpredis-2675d15/modules/redis.so, 9): no suitable image found. Did find:

/Users/jim/Downloads/owlient-phpredis-2675d15/modules/redis.so: mach-o, but wrong architecture in Unknown on line 0

This is one reason I quit corporate coding

I got this instant msg from a buddy today at Panasonic:

MyBud

1:07

Example of Hadoop Python Streaming job script

here is a sample job script I got running to test out some hadoop mapreduce jobs for our new cluster. You can put this in the same directory with the map/reducer files. the -file parameter will package up those files and send them to the tasknodes in the cluster so you don't have to install them yourself.

#!/bin/sh