Storing Text in S3 in Java

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A very simple option is to store the actual text in Amazon s Simple Storage Service and use a SimpleDB item attribute to point to the location of the text file If the application using this data is on EC2 in the same region, it will have fast free data transfer to both S3 and SimpleDB It can be made available using the same AWS credentials used with SimpleDBAdditionally, S3 supports versioning, so you can easily maintain older versions of files Depending on the application, it may be useful to store the previous S3 text file version-identifiers as attribute values in SimpleDB for quick access or querying Even though the actual text data in this case in not available to SimpleDB queries, you may want to store keywords, topics, or tags in SimpleDB for this purpose When storing the large text in S3, consider storing the full bucket location and path of the text fileThis can work in the same way as when you store any type of file in S3, and you may want to implement a common mechanism for referencing data in S3 It may be helpful to use a naming convention to match domains to buckets if the data is not going to be used externally
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When you know the maximum size of the text that you need to store, and if it is larger than the 1k attribute limit, you may be able to reserve a few attributes for storing that text For instance, if the maximum text length is 100k, you can break it into 100 1k chunks and have 100 attributes like BodyText , BodyText01 , BodyText02 , and so on This can work even if you don t know what the maximum size of the text will be, so long as you don t overflow the number of attributes allowed within an item A situation where this technique is useful is storing user-entered data where the text could be large in theory, but where a very low percentage of entries ever exceed 1,024 bytes In these cases, an attribute like BodyText will hold the full text in almost all cases, with extra overflow attributes for those few items that actually need it Examples of applications where this can be useful include user comments on blogs, product review websites, and social news and bookmarking sitesAssuming that users will generally type in 1,024 bytes or fewer is reasonable in many situations, even though it may not be intuitive Consider an extreme example of this principle: the website stackoverflowcom Stackoverflow is a large question-and-answer site for programming questions, where the users are specifically encouraged to post detailed questions and responses Not only is markup permitted within the user-submitted text, but it is also stored in the database with the full HTML markup With these forces pushing the size of user posts upward, it is interesting to note that more than 72% of questions and answers on the site are smaller than 1,024 bytes Stackoverflow does not use SimpleDB, but they do publish data dumps that can be analyzed, and they are an excellent example of how difficult it can be to get users to type in large blocks of text, even for a fraction of the time The trade-off from using this approach is that you lose a few of the conveniences you would normally have with a queryYou cannot easily do a query for text matches across the variable number of attributesAlso, it makes it difficult to use that attribute specifically as part of the output selection clause; you end up needing to use SELECT * anytime you need that attribute in a query However, the benefit is that it is easy to split up and reassemble the text because it doesn t require any special processing It is most applicable when the majority of read operations are in the form of GetAttributes rather than Select In these cases, you don t suffer the query inconvenience It is more difficult to update the text stored in these types of items, however, because there are more steps involvedAnytime the text needs to be updated, you must be sure to delete any attributes no longer usedThe procedure for processing an update of text would be something like this: 1 Read the item using GetAttributes or Select 2 Reassemble the original text using the attribute naming conventions 3 Present this text to the user 4 Accept the user s new text and break it into chunks
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