Simple ranked text search for MongoDB

In this code snippit you can see how to do a basic ranked text search for MongoDB. The code relies on two simple mapreduce operations. One to create an inverted index from some demo text, and a second one to score the matching documents based on query term hits.

MongoDB first impressions

For a customer we have developed log analytics software. It’s currently uses MYSQL as the database backend. The system reads in a hourly log file, and calculates all kinds of fancy statistics. I wanted to see how the system would work if I used MongoDB, a schema-less document DB, instead of MYSQL. My impressions in no particular order:

• Importing log data is much easier than on MYSQL because MongoDB is schema-less. Just create a collection (=bucket) and insert every log line into it as a hash. For log files that don’t have a fixed amount of fields, it’s a great fit.
• Like MYSQL, you do need to create indexes to make searching fast(er).
• MongoDB supports map reduce operations. It made some of the calculations much more elegant and better readable than the code that was written for MYSQL.
• Chaining of map reduce operations is supported, and works as you would expect.
• Queries are written in javascript. I’m happy that they didn’t invent yet another ’scripting’ language. Javascript looks capable enough.
• Map reduce operations are not particularly fast. They are upgrading their javascript engine to V8 to improve the execution speed.
• MongoDB community is nowhere near the size of MYSQL. Don’t expect a lot of Google results for a specific mongoDB issue. The moderated Google group is a better place to go currently.
• I liked the API. Calls are not verbose and their intented use is easy to understand.
• Although quite capable, mongoDB is still a young project. I need to have more time with it before using it on a customer project.

5 Must-have iPhone libraries

A list of  5 must-have iPhone libraries that we use at tty.nl for our iPhone dev needs:

#1 ASIHTTPRequest

The network API of Apple’s Cocoa Touch framework is not a pretty sight. It’s verbose and hard to put into use. The ASIHTTPRequest library by All-Seeing Interactive is high quality wrapper around the CFNetwork API that makes http communication trivial to implement. Love it!

#2 Json-framework

REST & JSON are here to stay. (Bye bye SOAP, won’t miss you!). The json-framework library enables your killer iPhone app to parse & generate strict JSON.

#3 Touchcode

Cocoa’s NSXML API is much too complex for the 95% of the use cases. For that 95% you should just use touchcode. It’s based on the Open Source libxml2 and supports most XPATH queries.

#4 Pinch analytics

Pinch analytics is best described as Google Analytics for your iPhone app. It allows you to track the amount of unique users, the time spent per user, device types and much more. And just like Google’s package it’s totally free.

#5 RegexKitLite

I was shocked to discover the Cocoa Touch framework doesn’t support Regular Expressions out of the box. No worries though: RegexKitLite allows you to continue to use your carefully crafted regular expressions.