Spyced

I ran across A case study in building layered DHT applications while doing some research on implementing load-balancing in Cassandra . The question addressed is, "Are DHTs a general-purpose tool that you can build more sophisticated services on?" Short version: no. A few specialized applications can and have been built on a plain DHT, but most applications built on DHTs have ended up having to customize the DHT's internals to achieve their functional or performance goals. This paper describes the results of attempting to build a relatively complex datastructure (prefix hash trees, for range queries) on top of OpenDHT. The result was mostly failure: A simple put-get interface was not quite enough. In particular, OpenDHT relies on timeouts to invalidate entries and has no support for atomicity primitives... In return for ease of implementation and deployment, we sacrificed performance. With the OpenDHT implementation, a PHT query operation took a median of 2–4 seconds...

I was asked to put my slides up again -- sorry it took so long. The slides and code samples are now up here . Video of the tutorial is also up . (3 parts, first is linked). There's definitely audio problems in parts but at least some is watchable.

We have a release candidate out for Cassandra 0.3. Grab the download and check out how to get started . The facebook presentation from almost a year ago now is also still a good intro to some of the features and data model. Cassandra in a nutshell : Scales writes very, very well: just add more nodes! Has a much richer data model than vanilla key/value stores -- closer to what you'd be used to in a relational db. Is pretty bleeding edge -- to my knowledge, Facebook is the only group running Cassandra in production. (Their largest cluster is 120 machines and 40TB of data .) At Rackspace we are working on a Cassandra-based app now that 0.3 has the extra features we need. Moved to the Apache Incubator about 40 days ago, at which point development greatly accelerated. Changes in 0.3 include Range queries on keys, including user-defined key collation. Remove support, which is nontrivial in an eventually consistent world. Workaround for a weird bug in JDK select/register that see...

Vladimir Sedach wrote a three-part dive into Cassandra . (Almost two months ago now. Guess I need to set up Google Alerts. Trouble is there's a surprising amount of noise around the word `cassandra.`) Part 0 Part 1 Part 2 A few notes: We now have an order-preserving partitioner as well as the hash-based one Yes, if you tell Cassandra to wait for all replicas to be ack'd before calling a write a success, then you would have traditional consistency (as opposed to "eventual") but you'd also have no tolerance for hardware failures which is a main point of this kind of system. Zookeeper is not currently used by Cassandra, although we have plans to use it in the future. Load balancing is not implemented yet. The move to Apache is finished and development is active there now.

The Cassandra distributed database supports two partitioning schemes now: the traditional consistent hashing scheme, and an order-preserving partitioner. The reason that almost all similar systems use consistent hashing (the dynamo paper has the best description; see sections 4.1-4.3) is that it provides a kind of brain-dead load balancing from the hash algorithm spreading keys across the ring. But the dynamo authors go into some detail about how this by itself doesn't actually give good results in practice; their solution was to assign multiple tokens to each node in the cluster and they describe several approaches to that. But Cassandra's original designer considers this a hack and prefers real load balancing . An order-preserving partitioner, where keys are distributed to nodes in their natural order, has huge advantages over consistent hashing, particularly the ability to do range queries across the keys in the system (which has also been committed to Cassandra now...

David MacIver has an interesting blog entry up about determining logical project structure via commit logs . I was very interested because one of Cassandra's oldest issues is creating categories for our JIRA instance. (I've never been a big fan of JIRA, but you work with the tools you have. Or the ones the ASF inflicts on you, in this case.) The desire to add extra work to issue reporting for a young project like Cassandra strikes me as slightly misguided in the first place. I have what may be an excessive aversion to overengineering, and I like to see a very clear benefit before adding complexity to anything, even an issue tracker. Still, I was curious to see what David's clustering algorithm made of things. And after pestering him to show me how to run his code I figure I owe it to him to show my results . In general it did a pretty good job, particularly with the mid-sized groups of files. The large groups are just noise; the small groups, well, it's not e...

There were a lot of good talks at PyCon but I humbly submit that the best one you haven't seen yet is Robert Brewer's talk on DejaVu . Robert describes how his Geniusql layer disassembles and parses python bytecode to let his ORM turn python lambdas into SQL. Microsoft got a lot of press for doing something similar for .NET with LINQ , but Bob was there first. box = store.new_sandbox() print [c.Title for c in box.recall( Comic, lambda c: 'Hob' in c.Title or c.Views > 0)] This is cool as hell. The Geniusql part start about 15 minutes in.

I'm starting to conclude that git just doesn't fit my brain . Several months in, I'm still confused when things don't work the way they "should." My co-worker says I should start a wiki for weird-ass things to do with git: "You keep coming up with use cases that would never occur to me." But, I have to give the git community credit: I've never gone in to #git on freenode and gotten less than fantastic help. Even with git-svn.

I'll be leading an open-spaces discussion about distributed database architecture, implementation, and use today at 5:00 PM in the Lambert room. Specifically, we will cover bigtable, dynamo, and cassandra, and how to port a typical relational schema to cassandra's ColumnFamily model. I wrote a little background information yesterday about why I think Cassandra in particular is compelling .

I need a distributed database. A real distributed database; replication doesn't count because under a replication-oriented db, each node still needs to be able to handle the full write volume, and you can only throw hardware at that for so long. So, I'm working on the Cassandra distributed database. I gave a lightning talk on it at PyCon this morning. Cassandra is written in Java and implements a sort of hybrid between Dynamo and Bigtable . (Both papers are worth reading.) It takes its distribution algorithm from Dynamo and its data model from Bigtable -- sort of the best of both worlds. Avinash Lakshman, Cassandra's architect, is one of the authors of the Dynamo paper. There is a video about Cassandra here . The first 1/4 is about using Cassandra and then the rest is mostly about the internals. Cassandra is very bleeding edge. Facebook runs several Cassandra clusters in production (the largest is 120 machines and 40TB of data ), but there are sharp edges th...

I'm running Linux on my desktop at work after a year of OS X, and Gnome as shipped by Ubuntu 8.10 has just been a world of hurt. The panel looks and works like ass when moved to the left side of the screen (the only sane place to put it in today's world of widescreen monitors), network-manager just decided to quit working one day (I got by with wicd after that), alt-tab behavior sucks both ways you can configure it, etc. I installed KDE 4.2 over the weekend to see if I was missing anything there. Wow. It's like daylight after being in a cave for two months. I didn't realize how hard it has been to use a butt-ugly environment until I wasn't anymore. (Yes, I tried all the gnome themes I could find. Even Nimbus which took a bit of work. What's that recently-famous phrase? "Lipstick on a pig?") What is better in KDE? In a word, everything. And put me in the camp that really likes having the desktop turned into a usable area for the first time. ...

I will be giving an Introduction to SQLAlchemy tutorial and Mike Bayer and Jason Kirtland will be teaching Advanced SQLAlchemy , both on Thursday. I'll be covering similar material as last year , updated for 0.5. I'm also trying to see if I can get the emails of the registrants so far to see what else they would like covered. My tutorial style is exercise-heavy, so if you've read the docs or my slides but still find it hard to write SQLA code, coming to the tutorial is a great way to fix that. (Note: the blog link to the 2008 slides is broken since we moved utahpython.org. If you want them, drop me a note.)

It seems like Bloom filters are all the rage these days. Three years ago I had barely heard of them and now it seems like I see articles and code using them all the time. That's mostly a good thing, since bloom filters are a very useful tool to avoid performing expensive computations without the full memory overhead of a standard map/dictionary. Bloom filters are surprisingly simple: divide a memory area into buckets (one bit per bucket for a standard bloom filter; more -- typically four -- for a counting bloom filter). To insert a key, generate several hashes per key, and mark the buckets for each hash. To check if a key is present, check each bucket; if any bucket is empty, the key was never inserted in the filter. If all buckets are non-empty, though, the key is only probably inserted -- other keys' hashes could have covered the same buckets. Determining exactly how big to make the filter and how many hashes to use to achieve a given false positive rate is a solved p...

This is my attempt to clear up some misconceptions about CouchDB and point out some technical details that a lot of people seem to have overlooked.  For the record, I like Damien Katz's blog, he seems like a great programmer, and Erlang looks cool.  Please don't hurt me. First, and most important: CouchDB is not a distributed database.  BigTable is a distributed database.   Cassandra and dynomite are distributed databases.  (And open source, and based on a better design than BigTable.  More on this in another post.)  It's true that with CouchDB you can "shard" data out to different instances  just like you can with MySQL or PostgreSQL.  That's not what people think when they see "distributed database." It's also true that CouchDB has good replication, but even multi-master replication isn't the same as a distributed database: you're still limited to the write throughput of the slowest machine. Here are some reasons you should think tw...

Today marks one month that I've been working for Rackspace's RackLabs with the Mosso group in San Antonio, Texas.  (Anyone want to start a Python group?  The closest one is in Austin.) It's kind of a gentle introduction to big company culture for me; at around 2,000 employees, Rackspace is easily ten times as large as any other company I've worked for, and 100 times as large as most.  Mosso is a lot smaller and RackLabs itself is smaller still, but I still had to go to five days (!) of corporate orientation.  Other than that, though, we're pretty much left alone by our corporate parent. To start with, I'm working on Mosso's Cloud Files , which is basically an S3 competitor.  Cloud Files is similar to the work I did at Mozy, but there are a lot of technical differences.  Some are driven by Cloud Files being more of a general purpose storage engine than the one I wrote for Mozy; others stem from the Cloud Files authors being Twisted fans. Strange coincidence:...

I'm a little over a week into a git immersion program.  Let me just say that git's reputation of being a little arcane (okay, more than a little) and having a steep learning curve is 100% deserved. One thing that would mitigate things is if git would give you feedback when you tell it to do nonsense.  But it doesn't.  Here's me trying to get machine B to always merge the debug branch from machine A when I pull: 232 git config branch.debug.remote origin 234 git config branch.master.remote origin 236 git config branch.master.remote origin/debug All of these commands completed silently. None accomplished what I wanted. In the end I renamed master to old and debug to master to avoid having to fight it. Then I blew away my working copy and re-cloned because those config statements had created a new problem that I didn't know how to undo. I'm sure the git virtuosos out there will know what was wrong.  That's not the point.  The point is that the tool gave me n...

FormAlchemy 1.1 is out, so you no longer need to run trunk to get the admin app goodness -- now with i8n support. We also added support for all composite primary keys, and most composite foreign keys. (The distinction is, rendering an object depends on the PK, but loading relations depends on FKs.) Gael also added the fsblob extension , which allows storing blobs on the filesystem and the path in the database. (FormAlchemy can handle blob-in-the-db out of the box.) (I previously blogged about basic FormAlchemy and the admin app , which are still good introductions.) FormAlchemy has pretty good documentation . The most important page is form generation ; instructions to configure the admin app are here .

I saw an interesting article about logging today on reddit, and it struck a nerve with me, specifically how most text logs are not designed for easy parsing.  (I don't agree with the second point, though -- sometimes logging is tracing, or perhaps more accurately, sometimes tracing is logging.) We had a lot of log and trace data at Mozy, several GB per day.  A traditional parsing approach would have been tedious and prone to regressions when the messages generated by the server changed.  So Paul Cannon, a frustrated lisp programmer , designed a system where the log API looked something like this: self.log('command_reply(%r, %r)' % (command, arg)) Then the log processor would define the vocabulary ( command_reply , etc.) and, instead of parsing the log messages, eval them!   This is an approach that wouldn't have occurred to me, nor would I have thought of using partial function application to simplify passing state (from the log processor and/or previous log entrie...

I said that it would be possible to build a django-style admin interface for Pylons using FormAlchemy . (That is, generate a UI for basic CRUD operations for all your models, with no further configuration necessary.) I have a proof of concept in FA svn; it's missing some obvious features like internationalization so there is no official release yet. But the basics are there, so in the meantime, if you'd like to kick the tires , just install FA from svn and give it a try. Here are some screenshots from a pylons app incorporating models from the FA test suite. (The admin controller is fully customizable using standard FA (and Pylons) techniques, but these are what you'd see out-of-the-box.) Index: Order page: Creating a new Order: Deleting an Order: The User page: Editing a User instance: Documentation on using and customizing the pylons admin app is here .

A little background: a few months ago, I went looking for a web framework that was good at automating CRUD (create/retrieve/update/delete) against an existing database schema. I tried django but its database introspection abilities are beyond feeble, and django-sqlalchemy was not mature enough. I tried dbmechanic but its dozen-plus dependencies, most of which were alpha-quality, gave me pause; so did its basic architecture on top of toscawidgets, which I think is The Wrong Way to build web apps. (I understand that the former problem has since been reduced; the latter has not.) So, I went back to option #3, FormAlchemy . I knew SQLAlchemy could reflect very hairy schemas indeed, and what it could not reflect, it could certainly represent with a little manual help. And FormAlchemy was a decent start to automating CRUD with SA models. I added the ability to represent relations, automatic syncing of form input back to SA objects, Grid support, and a test suite. Then Gael came alo...