Gilles Zumbach, Adrian Trapletti
Orla: A data flow programming system for very large time series
***************************************************************

To analyze tick-by-tick financial time series, programs are needed which are
able to handle several millions of data points. For this purpose we have
developed a data flow programming framework called "Orla".
The basic processing unit in Orla is a "block", and blocks are connected to form
a "network". During execution, the "data" flow through the network and are
processed as they pass through each  block. The main advantages of Orla are that
there is no limit to the size of the data sets, and that the same program works
both with historical data and in real time mode. In order to tame the diversity
of financial time series, the Orla data structure is specified through a BNF
description called SQDADL, and the Orla data are expressions in this language.
For storage, the times series are written in a "tick warehouse" which is
configured completely by the SQDADL description. Queries to the tick warehouse
are SQDADL expressions and the repository returns the matching time series. In
this way, we achieve a seamless integration between storage and processing,
including real time mode. Currently, our tick warehouse contains 20'000
"elementary" time series. In this paper, we provide a brief overview of Orla and
present a few examples of actual statistical analysis computed with Orla.