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The pricing model for SimpleDB is straightforwardThere are data transfer charges for moving data in and out of Amazon s cloud, frequently with discounts on inbound data There are storage charges, currently at $025 per GB-month ($0275 for Singapore, N California and Ireland) Finally, there are charges for the box usage of each operation Each SimpleDB response includes a number indicating the fractional hours to be billed Box usage charges stand at $014 per hour ($0154 for Singapore, N California and Ireland), with the first 25 hours free (at the time of this writing) Data transfer usage is measured directly Data storage is measured at intervals throughout the month Box usage, however, is not measured; it is assigned for each request based on formulas and variables Formula-based assignments eliminate the variability that might otherwise be present across SimpleDB replicas running on heterogeneous hardware It also obviates the overhead of measuring every operation Although the box usage is computed and not measured, the pricing turns out to be reasonableThere are, however, two noteworthy exceptions to that reasonablenessThe first exception includes certain forms of PutAttributes/DeleteAttributes/BatchPutAttributes and the second is the cost of QueryTimeout
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Automatically Optimizing for Box Usage Cost
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The Exponential Cost of Write Operations
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Back in June of 2008, Colin Percival broke down the SimpleDB box usage formulas in a post on his blog at wwwdaemonologynet/blog He reported that the formula for PutAttributes and DeleteAttributes box usage was as follows: 00000219907 + 00000000002 N^3 In the equation, N is the number of attributes passed to the operationThe important fact is that the operation cost rises proportionally to the attribute count cubed I verified the accuracy of the formula when it was posted, and it is still accurate at the time of this writingThe numbers are the same whether you pass single-valued attributes or multivalued attributes, and the formula holds true for BatchPutAttributes as well What this means is that the cost of these write operations grows outrageously fast at the top end of the range Figure 11-1 shows a graph of the cost of SimpleDB write as the number of attributes in the request grows
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Figure 11-1
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The charges for write operations as a function of attribute count
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The x-axis in Figure 11-1 is the number of attributes, from 1 to 256The y-axis is the box usage charge per million requests, in dollars There is a base charge for the operation, independent of the data you pass, of slightly more than $3 per millionAt the bottom end of the graph, where the number of attributes is small, the base charge dominates the total charge In fact, as you increase the number of attributes in a request up to 32, the charge per million never exceeds $4
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At this point, the incremental attribute cost begins to rise quickly By the time you get to 53 attributes per request, the cost is above $7 per million, and it would actually be cheaper to write the data using two requests The remainder of this graph has charges rising fast enough to make your head spinAt 120 attributes, you pay above $50 per millionAdd 50 more attributes, and the charges triple to above $150 per millionAt the per-item limit of 256 attributes, the charge is a mammoth $47284 per million What this all means is that if you have 256 attributes to put into an item, and you do it in a single request, you will pay a charge an order of magnitude higher than if you sent the exact same data in five smaller requestsTo make the point in dollars, imagine that you have an application that sends data to SimpleDB at an average rate of two writes per second If those writes each contain 2KB of data in 20 attributes, the monthly box usage charges will be roughly $34, or about half the cost of a small EC2 instance If, however, those writes contain the same 2KB of data, but in 256 attributes, the charges will be about $4,902, which is enough to run 80 small EC2 instances all month long Attribute Counting Applications that naturally have 50 or fewer attributes per item are not going to suffer from those punitive box usage chargesThere are a wide variety of applications in this group For applications writing larger quantities of attributes, there are a few workarounds to reduce the cost However, there are tradeoffs with each choice, so none of them can apply to every situation The first thing to realize is that using SimpleDB for some applications would be prohibitively expensive If 256 attributes per item feels restrictive for a given project, and you need to use the full 256 to make it work, SimpleDB may not be the best choiceThis is especially true if none of the workarounds is suitable For those applications that fall somewhere in the middle, one workaround is merging values into composite attributesWith attribute merging, multiple attributes values are appended together and stored in one attributeThis was discussed in the context of query performance, and it can be used here as wellThe benefit comes from reducing the number of attributes that need to be written One drawback is the 1,024-byte limit on attribute values that limits how much data can be mergedAnother drawback is that you only have the ability to query efficiently the first of the merged attribute Subsequent attribute values stored within the composite can only be queried by combining the prior values as query constant, or using LIKE Since using LIKE to match the end or middle of a value cannot use an index, the query can be done, but it will require a table scan and will not be efficient unless there are other criteria that limit the items that must be scanned A different option is to write all the attributes that you normally would, but write them in multiple requests, each with 52 or fewer attributesThe benefit is the significant reduction in cost by avoiding the high-attribute count in any single request However, there are two downsidesThe first is the loss of atomicityWhen you perform a write of any kind in SimpleDB, the change is applied atomicallyThis is true for both normal writes and condi-
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