Notes from Hadoop World 2010 NYC

Recently attended Hadoop World 2010, NYC. Here are my thoughts on the presentations I attended:

Tim O’Riley
Tim covered some of the roles Hadoop can play as part of the Internet Operating System, and how data can be correlated across many channels to yield unexpected information. For example, utilizing log analytics to develop a smart phone that can recognize it’s owner by the way they move (motion sensors) and use the phone, or how analysis of power grid spikes can tell companies which appliances you have in your home and when you use them. Essentially he showed how Hadoop is helping herald in an era where logs correlated across multiple channels yields an unprecedented amount of detailed information about individuals and their behavior.

Hadoop Analytics: More Methods, Less Madness
Shevek Mankin, Karmasphere
Shevek presented essentially the same information you can get on the web about his products.  However, in a followup conversation with him I asked him about compatibility with with the .21 Hadoop API and he replied that they are writing the code now.
Not sure when the release date is… following up to see if anything has changed with recent releases after HWNYC.

Making Hadoop Security Work in Your IT Environment
Todd Lipcon, Cloudera
Todd covered how to implement security in Hadoop. Eagerly awaiting the video feed on this one. Main highlights include the addition of strong authentication throughout the framework components and ACLs for Job Queues. Todd also details some tricks and gotchas on integrating Hadoop Security with Active Directory. Hadoop uses Kerberos so the integration flows more smoothly than one might expect!

Hadoop: Best Practices and Real Experience Going From 5 to 500 Nodes
Phil Day, HP
Phil described the challenges and learning experiences HP has had in deploying large Hadoop clusters on time and on budget. Of particular interest was the ability of HP to build and test whole racks of servers at the factory and then ship them and plug them in at the data center (HP Factory Express). Normally I don’t appreciate vendor tag lines but this one is extremely relevant given the issues a small deviation in configuration can cause in a cluster that large! Phil also noted that since the recovery features in Hadoop are so advanced: a failed job can continue on and on and produce reams of logs before complete failure occurs. This emphasizes the need for a management console able to sift through reams of logs to isolate the original failure root cause. Also of interest was some of the build details he had for the data-intensive cluster they designed:

  • The use of 1Gb network cards for the data nodes to save costs, but retaining 10Gb cards for the network intensive components such as the name node
  • Using 6 local drives for each Intel Xeon quad core to increase data throughput
  • Using what he called Edge Nodes to control access to the cluster

HBase in Production at Facebook
Jonathan Grey, Facebook
Brilliant presentation by Jonathan Grey about how Facebook is using HBase. Particularly of interest was using the counters feature in HBase to track real time statistics from incoming logs. Also, that Facebook is using HBase in the online applications as well as the batch applications was news to me. Apparently some parts of the FB site use HBase directly, which is a testament to it’s availability and performance characteristics.
In the batch world, they are loading into HBase tables from the web logs via cascading and then fronting the HBase tables with Hive. It was great to hear talks from these guys (esp, Yahoo, Facebook, and StumbleUpon) about how they are using these tools together. Even though they are all open source it is not always obvious how to use the tools together in a real world architecture. Bravo to all of you guys for being so open about real world usage!
Also of note:

  • Facebook will be distributing it’s own version of Hadoop via Github
  • They are running HA for Name Node via an Avatar Node
  • They are using 16 drives at 2 TB each per data node

ZooKeeper in Online Systems, Feed Processing, and Cluster Management
Mahadev Konar, Yahoo!
Very interesting presentation from Mahadev about how Yahoo! is using ZooKeeper for command, control, and meta-data during feed processing. Mainly the most interesting part was how they are using BitTorrent for data feeds (I wonder which client they are using, maybe Vuze). The torrent meta-data is published on ZooKeeper and subscriber nodes process the feed and update status on ZooKeeper as well. ZooKeeper is also used for heartbeats and coordinating feed re-processing logic in case a node dies. Also of note was Yahoo!’s use of BookKeeper for ultra high performance durable publish and subscribe (bye bye message queues). And that Yahoo! recommends a 5 node ZooKeeper cluster but has seen installations up to 12 nodes. ZooKeeper is Hadoop’s diamond in the rough =)

Cloudera Roadmap Review
Charles Zedlewski, Cloudera
Charles went through all the cool management features being added to Cloudera Enterprise. Of course he emphasized that this does not mean the free version is dumbed down, just does not include all the management stuff for big clusters (see Phil Day’s presentation on the importance of management software for large clusters).

Apache Hadoop in the Enterprise
Arun Murthy, Yahoo!
This presentation was HUGE! (that’s the running joke because he said HUGE a lot)
Anyway on a serious note Yahoo! did put in a huge effort to productionize Hadoop 0.20 by introducing 4400 patches. Totally awesome for the community. On top of adding security and the Capacity Scheduler, very cool stuff. Of note also is the upcoming addition of Name Node Federation where a name node is mapped to a HDFS path so you can run as many name nodes as you wish and a failure means only that path is down.
He had a funny comment about using HDFS ls (directory list) on a 4000 node cluster can take down the name node. They use ZooKeeper to check if a file exists instead. Just one of those nice to knows =)
Also, I had an offline conversation about adding CPU and I/O caps to jobs in the Capacity Scheduler (infinite loops in Hadoop jobs can be nasty). I’ll be sending them a followup email soon because they had some other tricks they mentioned for implementing CPU caps, whether or not they actually end up adding it to the Capacity Scheduler.

Mixing Real-Time Needs and Batch Processing: How StumbleUpon Built an Advertising Platform using HBase and Hadoop
Jean-Daniel Cryans, StumbleUpon
StumbleUpon is using a vary similar architecture to Facebook, with the difference that HBase really seems to be at the core of StumbleUpon’s online presence. With an 11 million user base this is another very significant testimony to the availability and performance of HBase. They are using the atomic increment functionality in HBase to track users in real time from web logs (similar to Facebook). They also created opentsdb, based on HBase, to help monitor their environment. Also of note: they are using cascading to join HBase to native Hadoop formats such as sequence files and MapFiles.

Putting Analytics in Big Data Analysis
Richard Daley, Pentaho
Apparently Richard had to bow out at the last minute, but the guy they had presenting for him did a fairly good job of getting into the nitty grits of Pentaho for Hadoop. I have to say that the integration was so smooth: and this was a real time demonstration that this guy had to throw together in an hour (that actually worked!). Good litmus test for the tool: I ended up wishing I had this kind of environment to build, run, and monitor Hadoop jobs. Don’t get me wrong, I love the command line but I do not like busy work. So, very excited to get my hands on that software some time soon.

So, fantastic experience to learn from the people who hit the wall on big data years ago so we don’t have to!

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