It’s been a while since I have posted… in the midst of trying to plow through this dissertation while working on papers for submission to some conferences.
Hadoop has become the de facto standard in the research and industry uses of small and large-scale MapReduce. Since its inception, an entire ecosystem has been built around it including conferences (Hadoop World, Hadoop Summit), books, training, and commercial distributions (Cloudera, Hortonworks, MapR) with support. Several projects that integrate with Hadoop have been released from the Apache incubator and are designed for certain use cases:
Pig, developed at Yahoo, is a high-level scripting language for working with big data and Hive is a SQL-like query language for big data in a warehouse configuration. HBase, developed at Facebook, is a column-oriented database often used as a datastore on which MapReduce jobs can be executed. ZooKeeper and Chukwa Mahout is a library for scalable machine learning, part of which can use Hadoop. Cascading (Chris Wensel), Oozie (Yahoo) and Azkaban (LinkedIn) provide MapReduce job workflows and scheduling.
Hadoop is meant to be modeled after Google MapReduce. To store and process huge amounts of data, we typically need several machines in some cluster configuration. A distributed […]
I woke up early and cheery Wednesday morning to attend the 2011 Hadoop Summit in Santa Clara, after a long drive from Los Angeles and the Big Data Camp that lasted until 10pm the night before. Having been to Hadoop Summit 2010, I was interested to see how much of the content in the conference had changed.
This year, there were approximately 1,600 participants and the summit was moved a few feet away to the Convention Center rather than the Hyatt. Still, space and seating was pretty cramped. That just goes to show how much the Hadoop field has grown in just one year.
Keynotes
We first heard a series of keynote speeches which I will summarize. The first keynote was from Jay Rossiter, SVP of the Cloud Platform Group at Yahoo. He introduced how Hadoop is used at Yahoo, which is fitting since they organized the event. The content of his presentation was very similar to last year’s. One interesting application of Hadoop at Yahoo was for “retiling” the map of the United States. I imagine this refers to the change in aerial imagery over time. When performed by hand, retiling took 6 weeks; with Hadoop, it took […]
It has been a while since I have been to Silicon Valley, but Hadoop Summit gave me the opportunity to go. To make the most of the long trip, I also decided to check out BigDataCamp held the night before from 5:30 to 10pm. Although the weather was as predicted, I was not prepared for the deluge of pouring rain in the end of June. The weather is one of the things that is preventing me from moving up to Silicon Valley.
The food/drinks/networking event must have been amazing because it was very difficult to get everyone to come to the main room to start the event! We started with a series of lightning talks from some familiar names and some unfamiliar ones.
Chris Wensel, the developer of Cascading, is also the founder of Concurrent, Inc. Cascading is an alternate API for Map-Reduce written in Java. With Cascading, developers can chain multiple map-reduce jobs to form an ad hoc workflow. Cascading adds a built-in planner to manage jobs. Cascading usually infers Hadoop, but Cascading can run on other platforms including EMC Greenplum and the new MapR project. RazorFish and BestBuy use Cascading for behavioral targeting. Flightcaster uses a domain specific […]
Recently, I have been thinking about alternate ways of specifying search queries other than with text. A couple of weeks ago I came across a piece of music that I could not identify. I thought it would be a huge win for a search engine to allow me to upload this piece, and it would present me with matches, or near matches to other pieces that sound similar, or have similar characteristics. Some services already exist. Shazam allows a user to place a microphone near playing music and it will identify the artist and song. Some uses of search-by-sound:
Music identification (“solved” – Shazam) Music personalizaton and recommendation (“solved” – Pandora) Identification of the source of a sound (i.e. a species of bird, a musical instrument, an inanimate object) MP3 and media file search Finding material that violates copyright
As our motivating example, consider we find some really cool graphic on the web and we want to know where it likely originated (i.e. art, a meme). In such a search engine, we could upload the graphic and get results containing the exact image, or images that are very similar such as variations of the image (crop, resize, borders, different effects), […]
I am usually pretty reserved with cash, but after working full-time for six months, I finally decided to spend some of my money on building a new research development server. This process was long overdue and the reason it took me so long to commit to this project was all of the new technology developed since building my last server. This “new technology” can be pretty confusing unless one specializes in computer architecture. I want to share what I have learned throughout this process, while giving some background. These are only my opinions, and I may be wrong on some things as I am not a hardware expert. I encourage you to read and learn more on your own.
The CPU/Processor
If you are reading this article, I probably do not need to explain what the CPU/processor does. For high performance computing, you will want to get a CPU that is very “fast” and also has multiple cores. The definition of the word “fast” is in the eyes of the beholder and typically refers to more than just clock speed (GHz). In the constant war between AMD and Intel, I stick with Intel. AMD processors are powerful, but they seem […]
Some time over the past 6 weeks I randomly saw a tweet announcing the “Data Scientist Summit” and shortly below it I saw that it would be held in Las Vegas at the Venetian. Being a Data Scientist myself is reason enough to not pass up this opportunity, but Vegas definitely sweetens the deal! On Wednesday I woke up at 6am to partake on the 5.5 hour voyage to Las Vegas.
The Pre-Party
The Venetian and all close hotels were booked, so I ended up at the Aria; a new experience. The hotel is beautiful and very ritzy. I had heard that the rooms were very technologically advanced but I wasn’t prepared for the recorded welcome message, music and automatic shades opening upon entry to the room. The Aria is a geek’s paradise. Everything is computerized. Key cards are “waved” rather than swiped, lights are turned on/off and dimmed by use case (“sleep”, “read” etc.), rather than manually. There are no paper “Do Not Disturb” signs; rather, a switch on the wall (or via TV) toggles an indicator light outside the door. And the best part… Internet is FREE!
The rhododendrons hydrangeas are real! Work desk panel contains Ethernet, […]
Elastic Compute Cloud (EC2) is a service provided a Amazon Web Services that allows users to leverage computing power without the need to build and maintain servers, or spend money on special hardware. The idea is simple, the user “boots” up one or more machines and then accesses those machines as if they were logged into any other machine remotely. I used EC2 and Elastic MapReduce extensively for my M.S. thesis last spring, but mainly used its large memory capabilities rather than its potential for explicit parallelism.
Recently, I ran a crawling job on EC2 using a parellel crawler I wrote in Python with twill. Using EC2 poses its own challenges. Using parallel code poses more challenges. Combining these two facts with the fact that crawling is I/O bound can create some more interesting challenges. If you have taken a course in operating systems, you have heard this stuff over and over again. So have I, but I am stubborn. I tend to learn lessons from experience, and this was no exception. Through this series of posts, I want to point out difficulties and “gotchas” that are important to keep in mind when using EC2, and in this post, […]
This week it was revealed that the iPhone stores users’ locations, and this immediately caused a huge firestorm of commentary by tech geeks, panic among privacy advocates, and delight to data geeks like myself. Even better/worse, it seems that the iPhone caches location traces long-term, possibly back to the date the phone was activated.
I ditched my iPhone this past December (good riddance) in favor of the Droid X (Android). I figured, on such an open source OS, Google must be doing the same thing. After surfing through Hacker News, it turns out I was right.
Compared to the iPhone though, getting the data on an Android phone is not simple.
The data is stored in two files, cache.cell and cache.wifi in the directory /data/data/com.google.android.location/files. First, the user cannot browse this directory by attaching it to a computer. I installed an SSH daemon QuickSSHD to allow remote access into my phone. Second, it is not possible to access this directory without getting a Permission denied error, even if logged in as “root” as Google has not made this directory readable. Finally, for those (myself) that are still determined to crack this nut, you will need to root your phone. This […]
Programming defensively requires knowing the input that your code should be able to handle. Typically, the programmer may be intimately familiar with the type of data that his/her code will encounter and can perform checks and catch exceptions with respect to the format of the data.
Web mining requires a lot more sophistication. The programmer in many cases does not know the full formatting of the data published on a web site. Additionally, this format may change over time. There are certain standards that do apply to certain types of data on the web, but one cannot rely on web developers to follow these standards. For example, the RSS Advisory Board developed a convention for the formatting of web pages so that browsers can automatically discover the links to the site’s RSS feeds. I have found in my research that approximately 95% of my sample actually implemented this convention. Not bad, but not perfect.
Always Have a Plan B, C, D, …
One might say that 95% is good enough. I am a bit obsessive when it comes to data quality, so I wanted to extract a feed for 99% of the sites I had on my list. Also, I […]
Wow. I can’t believe it has been a month since I have posted. On December 1, I started a new chapter in my life, working full time as a Data Scientist at the Rubicon Project. Needless to say, that has been keeping me occupied, as well as thinking about working on my dissertation. For the time, I am getting settled in here.
When I accepted this position, one of my hopes/expectations would be to become professionally competent and confident in C, Java, Python, Hadoop, and the software development process rather than relying on hobby and academic knowledge. That is something a degree cannot help with. It has been a great experience, although very frustrating, but that is expected when jumping into development professionally.
I am writing this post to chronicle what I have learned about using Hadoop in production and how it majorly differs from its use in my research and personal analysis. To start, I was asked to check out a huge stack of code from a Subversion repository. But then what?
But you’re a Computer Scientist! This should be easy!
The first part is true, but there is a stark difference between a garden variety computer […]
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