Segmenting the Queue across Multiple Instances in Windows Azure
A common usage pattern in cloud computing is to process all tasks that are similar in the same instance, at the same time leveraging the scalability of cloud computing by running multiple instances for all the tasks. Grouping like tasks within an instance is done for a couple of reasons: Avoid data contention across tenants. For example, if you are aggregating data you might want to performance all the aggregation in memory before writing the data to storage. If you can segment the data that need to be aggregated together on a single tenant you will not have another tenant beating you to the write. Optimize your local memory cache. If you are caching expensive to retrieve data in the instance, segmenting your tasks to a instance with the task appropriate cache can increase your cache hit ratio. In other words different cached data specific to the work that the instance is doing. This article will talk about how to successfully accomplish task segmentation in Windows Azure. ...