Archive for May, 2008
Realtime Aggregations
May 30th, 2008
ActivePivot offloads pivot calculations and aggregations from the client process to a backend server. It exposes XMLA interface (among others), which means that if you are an Excel user, you simply define a pivot table and point the data source to the ActivePivot server. From that point onwards, Excel interacts with ActivePivot natively.
The result is a very thin Excel spreadsheet which only displays the aggregated result, and all the number crunching and aggregations take place at the server side. When the user interacts with the pivot table, Excel queries ActivePivot and display the next level. Very nice!
ActivePivot provides hooks for the correlation and aggregation execution, so custom logic can easily be applied.
ActivePivot stores the aggregated cube in memory, which allows it to update the cube and respond to market events, and by that provide intra-day aggregations.
The real time bit is where GigaSpaces fits in
Market data feeds are written into a space using one of GigaSpaces’ APIs (JMS, Remoting, JavaSpaces, etc’), and ActivePivot connect to the space and register for space events. When a tick is updated in the space, the space sends a notification to ActivePivot which in turn re-aggregates the relevant cube branch. This means that the aggregated cube is always updated and reflects the latest market state. In addition ActivePivot queries the space for the raw data when Excel sends a drill-down request, which allows ActivePivot a very quick response time.
ActivePivot can be applied at different areas and provide real time P&L, real time Risk, etc’
-Guy
OpenSpaces Developer Challenge WINNERS
May 28th, 2008Hurray and congrats to the 3 winners of our developer contest OpenSpaces Developer Challenge!
And the winners are (sorted alphabetically)…
Jason Carreira with DomainProxy
Kirill Ishanov with Gigapult
Leonardo Goncalves with GoDo - Goods Donation System
Who won the grand prize?
How was the review/judging process?
What is so special about the winning projects?
How do I join the next contest?
And the Winners [...]
GigaSpaces Blog - New Version and Location
May 27th, 2008With the recent move of both gigaspaces.com and openspaces.org to a new server, we've now also moved our team blog (which you are now reading) to the new server, running on the latest version of WordPress (2.5.1). Although the blog is still accessible from www.gigaspacesblog.com, the official url is now blog.gigaspaces.com.
We soon [...]
Deployment Predictability
May 23rd, 2008My colleague Uri raised an interesting point in his post. I completely agree with Uri, and would like to give an example.
I have been involved in a project for a mobile operator in the UK during the second half of last year. We built a scale-out SOA activation platform for a new mobile device launch using GigaSpaces. The GigaSpaces platform replaced an existing system.
The original system was built using JBoss as a backend server. Predictions were for a huge increase in activation-requests the system had to handle due to the new device launch. While the system worked fine using the JBoss as a platform, there was no way these guys could predict how many instances of JBoss they would need to run in order to cope with anticipated load. They started to do some benchmarking and performance testing to figure out where the system’s limits were, but they soon found out, that the process was leading them nowhere. This is mainly because the JBoss’s were inconsistent and they hit the scalability ceiling using a few (very few…) nodes. When adding more instances, the overhead of synchronising the JBoss cluster grow exponentially as suggested by Ahmdal’s Law, so the gain in TP that each instance added varied depending on the cluster size and other nodes’ load, which kills predictability all together.
JBoss is just an example in this case. It’s not a JBoss specific flaw, but rather a tier based approached which imposes a limited architecture.
They then came to us to resolves the predictability challenge.
We did an exercise to figure out how the deployment would look like using GigaSpaces, and came up with a linear formula of the HW and number of instances needed to support the given load. More than that, they knew that if the business predictions had been pessimistic, supporting extra load would mean simply deploying more spaces… On top of that, their back office systems did not support HA, and would explode if load increased suddenly, so GigaSpaces also provided HA and throttling for the backend servers. During one overnight test the database failed for about 4 hours, and the system was fully functional and completed users’ requests, while completed requests waited for the database to be brought up again to complete the archiving process. The customer was truly impressed!
Needless to say that the launch went flawless, and there were no issues what so ever with the GigaSpaces based system.
So, yes – Uri makes a good point. GigaSpaces’ customers can predict and properly plan ahead the deployment needed to support their business.
-Guy
GigaSpaces 6.0.5
May 22nd, 2008We just released GigaSpaces 6.0.5, our fifth Service Pack.
The release addresses some critical issues detected over the last couple of months that are related to failover and the Service Grid (see the release note snapshot at the bottom of this post).
The release is available for all version of the product, namely XAP, EDG and the [...]
