In: Linux

8 Jul 2007

I’ve had alot of experience with other programming languages, however I had to learn C++ from scratch in a very short period of time, a number of weeks ago. This was to develop a real-time stock quote client, the goal was simply to push data from remote servers into our databases, filter what messages it would receive and get something up and running fast as deadlines lingured. This was simple enough, however with the rush the application had its inherent flaws, due to my lack of knowledge of C++, the API, and the goals it had to acomplish.

I’ve since had time to learn a little more C++ and limited time to design the application properly.

The Problems

The core problems with the application:

  • refactor, refactor, refactor
  • database connection pooling
  • Query remote CSP servers*1
  • Query remote CSP servers*1 from PHP
  • Configuration management
  • Monitoring
  • Flexible Database schema
    • Add columns to database schema dependent on datatype.
    • Log messages in XML per trade message with date/time, columns and values.

Compatible GCC

The first issue was that I used an API from interactive-data, which was compatible with “gcc version 3.2.3″ and is not kept up to date. This meant compiling a compatible gcc from source for 32bit platforms only.

./configure --prefix=/usr/local/gcc/ --mandir=/usr/share/man --infodir=/usr/share/info --enable-shared --enable-threads=posix --disable-checking --with-system-zlib --enable-__cxa_atexit --enable-languages=c,c++,objc,obj-c++

make bootstrap
cd gcc
sudo make install

Once having a compatible compiler, I then had to make modifications to the Makefile, move a number of lib/so files to get MySQL to compile and get things working. Unfortunately I did not have a local machine to attach a debugger, so everything was trial and error from the command line with g++32, which makes life difficult identifying runtime errors.

The Logic

Once everything was in place, the logic was fairly simple, foreach field retreived construct a query with the field name, checking the fields values datatype whether it be a datetime, varchar etc. Insert each trade message in a table, update another and if either failed, check if the fault was due to a missing column, if so add it and re-execute queries.

The problem soon arrises when you need to know when each column was actually last updated, with which field, value, datetime and the last insert id for the trade messages. Whilst looping through each trade message, I constructed an XML schema containing the above, however the tricky part is to ensure that it only updates the fragment matching the field in the schema. Not an ideal format to query from a database.

Storing Data

One of the fundemental issues is managing and storing data. For some exchanges you don’t want to store every trade message; simply storing the current data for a number of instruments is enough. Which servers or databases do you peg data to? If one database goes down, how do you handle fault tolerance? MySQL cluster is not a feasible solution, requiring multiple servers and large memory requirements per installation. The databases are highly susceptible to curruption or faults. Also particular sites may require data from multiple exchanges, so seperating trade messages per database is not also ideal.

All of this fundamentally comes down to configuration management.


One of the fundamental aspects of the application is configuration management. This contains where data should be stored for a particular exchange, the type of data to store, whether it is per trade message, current data or both. Which servers to source data from, whether it is real time or delayed, whether to source data for bonds, equities, automated trades etc… All queries can be grouped, or to query remote servers. Some of the products for example just for the London Stock Exchange is:

  • London Stock Exch – Covered Warrants L1
  • London Stock Exch – International Equity Mkt Service L1
  • London Stock Exch – International Equity Mkt Service Level 2
  • London Stock Exch – UK Equity Mkt Service L1
  • London Stock Exch – UK Equity Mkt Service Level 2 (Depth Refresh)
  • London Stock Exchange: UK Equity Market Service Level 2

All of which is stored in several database tables and managed via a MySQL database and PHP frontend.

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About this blog

I have been a developer for roughly 10 years and have worked with an extensive range of technologies. Whilst working for relatively small companies, I have worked with all aspects of the development life cycle, which has given me a broad and in-depth experience.