Reporting Import Progress in Java

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For small deployments, the time requirement to process the import might not be a concern For larger data sets that will take hours to import, the percentage of import completion is valuable informationAs you design and implement your tool, consider ways to display the import progress or status
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It is always possible to run queries on the domain to count the number of records Eventual consistency normally gives you a count that is only a few seconds oldThis can be sufficient provided you know the total number of records to be imported or even when you just need to verify that the import tool is still adding records
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When creating an import tool using BatchPutAttributes, the 25-item limit on a single batch is immediately obvious However, the second limit on batch size is one that you might not be aware of, and, depending on your data, you might not run into it during testingYou might not even encounter it immediately during actual use If you are going to reach this limit, you don t want it to happen while in the middle of importing a large data set The maximum request size of a BatchPutAttributes call is 1MB It is uncommon to reach this limit Part of the reason is that, although 256 attributes are allowed per item, actual data commonly has many fewer than that, typically less than a few dozen However, be aware that the SimpleDB request-formatting characters are included in the 1MB limit, and that the length of those character strings are longer for BatchPutAttributes than for other operations For example, a small name/value pair might look like this:
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It shows up within a BatchPutAttributes request in a much more verbose and URL-encoded form like this, taking up more than double the size of the raw data:
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&Item17Attribute14Name=CreationDate &Item17Attribute14Value=2010-08-01T13%3A37%3A59723
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The typical ways to reach the 1MB limit are by filling up many attributes to the 1,024 limit or by using all 256 attributes in an item Doing either of those things does not guarantee that you will reach this limit, just that your chances are increasedThe only step you need to take is to check the request size before you send it and move items that overflow the limit into the next batch
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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-
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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
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