Releases Introduction SVN SourceForge Page


an innovative CEP (Complex Event Processing) engine

The most recent information about the status of the project is available in the blog


snapshot 1.0.93-20130623 No official documentation.
Read the blog at label 2_0.
Snapshot of the future version 2.0, with improved build.
snapshot 1.0.92-20130527 No official documentation.
Read the blog at label 1_1_0.
Snapshot of the future version 2.0 (formerly 1.1.0) with the preview of the Streaming Functions, TQL, improved scheduling, multithreading.
snapshot 1.0.91-20121129 No official documentation.
Read the blog at label 1_1_0.
Snapshot of the future version 1.1.0 with the preview of the Streaming Functions, TQL, improved scheduling.
1.0.1 Developer's Guide:
CPAN release, with minor fixes to the versioning.
1.0.0 Developer's Guide:
The first official release, with Perl API documentation.


What is the CEP?

CEP stands for the Complex Event Processing. If you look at Wikipedia, it has separate articles for the Event Stream Processing and the Complex Event Processing. In reality it's all the same thing, with the naming driven by the marketing. I would not be surprised if someone invents yet another name, and everyone will start jumping on that bandwagon too.

In general a CEP system can be thought of as a black box, where the input events come in, propagate in some way through that black box, and come out as the processed output events. There is also an idea that the processing should happen fast, though the definitions of fast vary widely.

If we open the lid on the box, there are at least three ways to think of its contents:

Hopefully you've seen a spreadsheet before. The cells in it are tied together by formulas. You change one cell, and the machine goes and recalculates everything that depends on it. So does a CEP system. If we look closer, we can discern the CEP engine (which is like the spreadsheet software), the CEP model (like the formulas in the spreadheet) and the state (like the current values in the spreadsheet). An incoming event is like a change in an input cell, and the outgoing events are the updates of the values in the spreadsheet.

Only a typical CEP system is bigger: it can handle some very complicated formulas and many millions of records. There actually are products that connect the Excel spreadsheets with the behind-the-curtain computations in a CEP system, with the results coming back to the spreadsheet cells. Pretty much every commercial CEP provider has a product that does that through the Excel RT interface. The way these models are written are not exactly pretty, but the results are, combining the nice presentation of spreadsheets and the speed and power of CEP.

A data flow machine, where the processing elements are exchanging messages, is your typical academical look at CEP. The events represented as data rows are the messages, and the CEP model describes the connections between the processing elements and their internal logic. This approach naturally maps to the multiprocessing, with each processing element becoming a separate thread. The hiccup is that the research in the dataflow machines tends to prefer the non-looped topologies. The loops in the connections complicate the things.

And many real-world relational databases already work very similarly to the CEP systems. They have the constraints and triggers propagating these constraints. A trigger propagates an update on one table to an update on another table. It's like a formula in a spreasheet or a logical connection in a dataflow graph. Yet the databases usually miss two things: the propagation of the output events and the notion of being fast.

The lack of propagation of the output events is totally baffling to me: the RDBMS engines already write the output event stream as the redo log. Why not send them also in some generalized format, XML or something? Then people realize that yes, they do want to get the output events and start writing some strange add-ons and aftermarket solutions like the log scrubbers. This has been a mystery to me for some 15 years. I mean, how more obvious can it be? But nobody budges. Well, with the CEP systems gaining popularity and the need to connect them to the databases, I think it will eventually grow on the database vendors that a decent event feed is a competitive advantage, and I think it will happen somewhere soon.

The feeling of fast or lack thereof has to do with the databases being stored on disks. The growth of CEP has coincided with the growth in RAM sizes, and the data is usually kept completely in memory. People who deploy CEP tend to want the performance not of hundreds or thousands but hundreds of thousands events per second. The second part of fast is connected with the transactions. In a traditional RDBMS a single event with all its downstream effects is one transaction. Which is safe but may cause lots of conflicts. The CEP systems usually allow to break up the logic into multiple loosely-dependent layers, thus cutting on the overhead.

The uses of CEP

Despite what Wikipedia says (and honestly, the Wikipedia articles on CEP and ESP are not exactly connected with reality), the pattern detection is not your typical usage, by a wide, wide margin. The typical usage is for the data aggregation: lots and lots of individual events come in, and you want to aggregate them to keep a concise and consistent picture for the decision-making. The actual decision making can be done by humans or again by the CEP systems. It may involve some pattern recognition but usually even when it does, it doesn't look like patterns, it looks like conditions and joins on the historical chains of events.

The usage in the cases I know of includes the ad-click aggregation, the decisions to make a market trade, the watching whether the bank's end-of-day balance falls within the regulations, the choosing the APR for lending.

A related use would be for the general alert consoles. The data aggregation is what they do too. The last time I worked with it up close (around 2006), the processing in the BMC Patrol and Nagios was just plain inadequate for anything useful, and I had to hand-code the data collection and console logic. I've been touching this issue recently again at Google, and apparently nothing has changed much since then. All the real monitoring is done with the systems developed in-house.

But the CEP would have been just the ticket. I think, the only reason why it has not been widespread yet is that the commercial CEP licenses had cost a lot. But with the all-you-can-eat pricing of Sybase, and with the Open Source systems, this is gradually changing.

Well, and there is also the pattern matching. It has been lagging behind the aggregation but growing too.

What led to Triceps

It had happened that I've worked for a while on and with the Complex Event Processing (CEP) systems. I've worked for a few years on the internals of the Aleri CEP engine, then after Aleri acquired Coral8, some on the Coral8 engine, then after Sybase gobbled up them both, I've designed and did the early implementation of a fair bit of the Sybase CEP R5. After that I've moved on to Deutsche Bank and got the experience from the other side: using the CEP systems, primarily the former Coral8, now known as Sybase CEP R4.

This made me feel that writing the CEP models is unnecessarily difficult. Even the essentially simple things take too much effort. I've had this feeling before as well, but one thing is to have it in abstract, and another is to grind against it every day.

Which in turn led me to thinking about making my own Open Source CEP system, where I could try out the ideas I get, and make the streaming models easier to write. I aim to do better than the 1950's style, to bring the advances of the structured programming into the CEP world.

Thus the Triceps project was born. For a while it was called Biceps, until I've learned of the existence of a recearch project called BiCEP. It's spelled differently, and is in a substantially differnt area of CEP work, but it's easier to avoid confusion, so I went one better and renamed mine Triceps.

Since then I've moved on from DB, and I'm currently not using any CEP at work (though you never know what would happen), but Triceps has already gained momentum by itself.

The Triceps development has been largely shaped by two considerations:

Both of these considerations point into the same direction: an embeddable CEP system. Adapting an integrated system for an embedded usage is not easy, so it's a good open niche. Yeah, this niche is not empty either. There already is Esper. But from a cursory look, it seems to have the same issues as Coral8/StreamBase. It's also Java-centric, and Triceps is aimed for embeddability into different languages.

And an embeddable system saves on a lot of components.

For starters, no IDE. Anyway, I find the IDEs pretty useless for development in general, and especially for the CEP development. Though it comes handy once in a while for the analysis of the code and debugging.

No new language, no need to develop compilers, virtual machines, function libraries, external callout APIs. Well, the major goal of Triceps actually is the development of a new and better language. But it's one of these paradoxes: Aleri does the relational logic looking like procedural, Coral8 and StreamBase do the procedural logic looking like relational, and Triceps is a design of a language without a language. Eventually there probably will be a language, to be mixed with the parent one. But for now a lot can be done by simply using the Triceps library in an existing scripting language. The existing scripting languages are already powerful, fast, and also support the dynamic compilation.

No separate server executable, no need to control it, and no custom network protocols: the users can put the code directly into their executables and devise any protocols they please. Well, it's not a real good answer for the protocols, since it means that everyone who wants to communicate the streaming data for Triceps over the network has to implement these protocols from scratch. So eventually Triceps will provide a default implementation. But it doesn't have to be done right away.

No data persistence for now either. It's a nice feature, and I have some ideas about it too, but it requires a large amount of work, and doesn't really affect the API.

The language used to implement Triceps is C++, and the scripting language is Perl. Nothing really prevents embedding Triceps into other languages but it's not going to happen anywhere soon. The reason being that extra code adds weight and makes the changes more difficult.

The multithreading support has been a major consideration from the start. All the C++ code has been written with the multithreading in mind. However for the first release the multithreading did not propagate into the Perl API yet.

Even though Triceps is a system aimed for quick experimentation, that does not imply that it's of a toy quality. The code is written in production quality to start with, with a full array of unit tests. In fact, the only way you can do the quick experimentation is by setting up the proper testing from the scratch. The idea of move fast and break things is complete rubbish.

Read more in the Developer's Guide and the blog.

Source Code Repository

The most recent code base of Triceps can be obtained directly from the SVN repository on SourceForge:

svn co

Or if you have a SourceForge accound, you can use it with an SSH key:

svn co svn+ssh://

Or you can browse SVN online.

Get Triceps at Fast, secure and Free Open Source software downloads

Also, read my book on parallel programming: