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Even in the case of inserting large numbers of items with BatchPutAttributes, there is still an obstacle to maximizing throughputThe difficulty is in the fact that the call is not blazingly fast, but it can be called concurrentlyThis is both a benefit and a drawbackThe drawback is the difficulty in the implementation of your own multithreaded import tool The threads need to be coordinated, and some state will need to be shared across threads Multithreaded code is error prone to write even for concurrency expertsThis is the type of task that, for typical application developers, is distinctly non-simpleApplication developers who are unfamiliar with writing multi-threaded code will find it to be difficult to write a custom multi-threaded import toolAlthough it may be difficult depend-

public ActivationDesc( String classname, String codebase, MarshalledObject data) throws javarmiactivationActivationException creates an activation descriptor associated with the default activation group for the JVM The classname parameter specifies the name of the class, and the codebase parameter specifies a URL to the

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643 Other Communication Constructs We have looked at only the most common message passing constructs: point to point message passing and collective communication There are many important variations in message passing In MPI, it is possible to fine tune performance by changing how the communication buffers are handled or to overlap communication and computation Some of these mechanisms are described in the MPI appendix, Appendix B Notice that in our discussion of communication, there is a receiving UE and a sending UE This is called two sided communication For some algorithms (as discussed in the Distributed Array pattern), the calculations involved in computing indices into a distributed data structure and mapping them onto the process owning the desired data can be very complicated and difficult to debug Some of these problems can be avoided by using one sided communication One sided communication occurs when a UE manages communication with another UE without the explicit involvement of the other UE For example, a message can be directly "put" into a buffer on another node without the involvement of the receiving UE The MPI 20 standard includes a one sided communication API Another example of one sided communication is an older system called GA or Global Arrays [NHL94, NHL96, NHK+02, Gloa] GA provides a simple onesided communication environment specialized to the problem of distributed array algorithms

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ing on your background, it is certainly not impossible If you take on this task and need some guidance, here are some suggestions for getting it done Storing data in SimpleDB using the BatchPutAttributes call can yield higher data throughput versus plain PutAttributes calls by a factor of six or seven In addition, the box usage charges for batches are in the neighborhood of 30% to 40% less Even so, you are going to want to issue these calls concurrently to get the best data transfer rate Concurrency is going to involve either multiple threads or non-blocking I/OThe choice is going to depend on which SimpleDB client you use, unless you write your ownThe number of simultaneous connections required to maximize throughput depends, in large part, on the size of the itemsThere is no single optimal number for all situationsThe best way to manage this is to track throughput dynamically as you increase the concurrency and be prepared to back off when you encounter either throttling with 503 ServiceUnavailable errors, or HTTP timeouts

public ActivationDesc( String classname, String codebase, MarshalledObject data, boolean restart ) throws javarmi activationActivationException creates an activation descriptor associated with the default activation group for the JVM The class name parameter specifies the name of the class, and the codebase parameter specifies a URL to the resource (though this can also be a local file:// URL) The restartFlag parameter specifies whether the

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