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blocks of matrix rows It is easy to write down the algorithm and code it for square matrices where the matrix order is evenly divided by the number of PEs But what if the matrix is not square, or what if the number of rows is much greater than the number of columns and neither number is evenly divided by the number of PEs This requires significant changes to the transpose algorithm For a rectangular matrix, for example, the buffer that will hold the matrix block will need to be large enough to hold the larger of the two blocks If either the row or column dimension of the matrix is not evenly divisible by the number of PEs, then the blocks will not be the same size on each PE Can the algorithm deal with the uneven load that will result from having different block sizes on each PE Efficiency The program should effectively utilize the available computing resources The rest of this section gives a partial list of important factors to check Note that typically it is not possible to simultaneously optimize all of these factors; design tradeoffs are inevitable

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These limits may seem restrictive when compared to the unlimited nature of data sizes you can store in other database offerings However, there are two things to keep in mind about these limits First, SimpleDB is not a general-purpose data store suitable for everything It is specifically designed for storing small chunks of data For larger data objects that you want to store in the cloud, you are advised to use Amazon S3 Secondly, consider the steps that need to be taken with a relational database at higher loads when performance begins to degradeTypical recommendations often include offloading processing from the database, reducing long-running queries, and applying selective de-normalization of the dataThese limits are what help enable efficient and automatic background replication and high concurrency and availability Some of these limits can be worked around to a degree, but no workarounds exist for you to make SimpleDB universally appropriate for all data storage needs

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currently available for reading More bytes may be available in the future, but reading more than the number of available bytes will result in a read that will block indefinitely void close() throws javaioIOException closes the input stream and frees any resources (such as file handles or file locks) associated with the input stream void mark(int readLimit) records the current position in the input stream, to allow an input stream to revisit the same sequence of bytes at a later point in the future, by invoking the InputStreamreset() method Not every input stream will support this functionality boolean markSupported() returns "true" if an input stream supports the mark() and reset() methods, "false" if it does not Unless over ridden by a subclass of InputStream, the default value returned is false int read() throws javaioIOException returns the next byte of data from the stream Subclasses of InputStream usually override this method to provide custom functionality (such as reading from a file or a string) As mentioned earlier, input streams use blocking I/O, and will block indefinitely if no further bytes are yet available When the end of the stream is reached, a value of 1 is returned int read(byte[] byteArray) throws javaioIOException reads a sequence of bytes and places them in the specified byte array, by calling the read() method repeatedly until the array is filled or no more data can be obtained This method returns the number of bytes successfully read, or 1 if the end of the stream has been reached int read(byte[] byteArray, int offset, int length) throws java ioIOException, javalangIndexOutOfBoundsException reads a sequence of bytes, placing them in the specified array Unlike the previous method, read(byte[] byteArray), this method begins stuffing bytes into the array at the specified offset, and for the specified length, if possible This allows developers to fill up only part of an array Developers should be mindful that at runtime, out-of-bounds exceptions may be thrown if the array size, offset, and length exceed array capacity void reset() throws javaioIOException moves the position of the input stream back to a preset mark, determined by the point in time when the mark() method was invoked Few input streams support this functionality, and may cause an IOException to be thrown if called long skip(long amount) throws javaioIOException reads, but ignores, the specified amount of bytes These bytes are discarded, and the position of the input stream is updated Though unlikely, it is entirely possible that the specified number of bytes could not be skipped (for example, as stated in the Java API, if the end of the stream is reached) The skip method returns the number of bytes skipped over, which may be less than the requested amount.

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