creating barcode 128 in c# Patterns for message processing in C#

Generate Code128 in C# Patterns for message processing

16.5 Patterns for message processing
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As simple as queues are, they can prove valuable in a lot of complex scenarios. This section will focus on some common approaches developers tend to use with queues.
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16.5.1 Shared counters
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You might run into a scenario where a piece of work is broken into many small pieces, and you need to make sure all of those small pieces are completed before you move on to the next step in your process. Sometimes these pieces are subsets of the main problem. This is called single instruction, multiple data. The same processing will be performed to each piece of data, but each piece is a subset of the whole. Consider working on an image. If you break the image into 100 pieces and apply the same process to each piece, you need to know for sure that all 100 pieces are completed before you can stitch them back into the larger picture. If you just break the image into 100 pieces and throw them into the queue, it can be difficult to know for sure when all of the 100 units of work have been completed. This has to do with the visibility timeout and the nondeterministic nature of queues. You might think that you could simply check the estimated length of the queue using q.ApproximateMessageCount:
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q.RetrieveApproximateMessageCount(); if (q.ApproximateMessageCount != null) int remainingMsg = q.ApproximateMessageCount;
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If you do, you must call RetrieveApproximateMessageCount, which fetches the information into the ApproximateMessageCount property from the queue in the cloud,
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Messaging with the queue
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before you call the property itself. This property returns an approximate count of the items in the queue, not an exact count, for two reasons. The first is that the queue is running in triplicate, and an add operation might have completed on one instance but not the other two, which would lead to an inconsistent result. The second reason is that you might get a zero back from your check, only to have an invisible message turn visible again when its timeout expires. Then you would have a message in the queue you didn t know about. You need a deterministic way to know for sure that all 100 pieces have been processed. One way to do this is to use a shared counter, perhaps in an Azure table. You can see a visualization of this process in figure 16.7. When the processing starts, a table is Producer made with a counter set to 0. As items are (website) 1 1 submitted into the queue by the producer Consumer 1 2 w, the counter is incremented q. As the work is completed in the consumer and 3 Consumer 2 the messages are deleted e, the counter Consumer 3 is decremented r. There is one small flaw this approach 3 suffers from, and it s a flaw all shared Shared counter counters have: it s possible to run into a concurrency problem. If one process Figure 16.7 Using a shared counter is one way reads the counter, adds 1 to it, and then to deterministically track how many messages have been processed. This is a good approach if writes it back to the table while another you have a specific number of messages to process is doing the same thing, they process and you need a precise count. could end up overwriting each other, resulting in losing track of the count. In order to fix this, you need to use locking on the counter. Another solution, which is used in eventually consistent scenarios, is to read the counter a second time before you write to it, to make sure it wasn t changed by someone else while you weren t looking. This approach will give you a simple count indicating the progress of the work. What if you want to know which pieces are done and which aren t No problem. You can do this with a small change to the previous approach. Instead of writing to a shared counter on each put operation, create a new record in the shared table. This will result in one record per queue message. As they re processed and the queue messages are deleted, the corresponding row should be deleted in the table. Another option would be to mark a property of the row in the table as complete, or store a completed time and date for performance tracking. In either of these ways with the shared counter or the shared message tracking table you can know with a simple query whether all of the work has been completed or not. You should think about wiring up a management portal that monitors the counter or table to show the progress to an administrator.
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