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In the diagram, you can see that some of these memory clusters have been used to create the hash table, which has been sliced into four separate partitions (a word that is used to mean far too many different things in Oracle). The number of partitions always seems to be a power of two, and the number of partitions is chosen to leave a few memory clusters spare for juggling the anticipated I/O that will be needed to dump the hash table to disk. (The bottom right hash partition is split to show that it is made up of two chunks, one of which seems to be on its way down to disk.) Bear in mind that the hash table is really just a collection of linked lists the image of partitions as nice tidy squares with the same number of chunks is a visual convenience I am using to try to show the logical identity of hash buckets in the hash table. At any one moment, each partition could be made up of a different number of memory chunks. You can get a lot of detail about how memory has been used by setting event 10104, the hash join trace, before executing a test query. The trace for the query from script hash_one.sql, for example, includes the following information that describes the components I have been describing: Number of partitions: 8 Number of slots: 13 Multiblock IO: 9 Block size(KB): 8 Cluster (slot) size(KB): 72 Bit vector memory allocation(KB): 32 Per partition bit vector length(KB): 4 ------13 clusters at 9 blocks each number of blocks to a cluster size of block size of cluster in KB: 9 * 8KB = 72KB total memory for bitmap: 8 * 4KB = 32KB memory per partition for bitmap

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How It Works Just as in the previous example, the proxy class and .NET infrastructure takes care of passing the information to the remote web method and handing results back. In this case, you receive a complex DataSet object back, which can be readily used to fill your DataGrid control. You take advantage of data binding, as discussed in 5. Having both the consumer application and the web service inside the Friends Reunion project makes it extremely easy to follow the execution flow. If you place breakpoints in your web methods code before starting the Acudei consumer site project, you can step into the code easily. Note that we don t handle errors that could happen, such as connectivity problems, service malfunctioning, and so on. We will introduce some error handling that is particular to web services in the Error Handling in Web Services section later in this chapter. General debugging and exception-handling techniques are covered in 11.

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My hash_area_size was set to 1MB and, as you can see, Oracle decided to run with eight partitions for the hash table, and has enough usable memory to juggle with 13 clusters of 72KB for a total of 936KB. The rest is taken up by 32KB for the bitmap (at 4KB per partition) and another 40KB, which is reported as a management overhead. The order of activity is as follows: 1. The first data set is acquired and scattered into the hash table. As a bucket is used, the corresponding bit in the bitmap is set. 2. As the memory fills up, clusters are dumped to disk. The dumping is done using a cautious strategy that tries to keep as many complete partitions in memory for as long as possible. When the build table is exhausted, it is possible that some partitions will still be held completely in memory, while the rest have only a few (but at least one) clusters left in memory. It may be that one partition has just a few clusters, in memory and the rest have only one each. Whatever the outcome, Oracle will have a detailed map of where the data from each partition can be found. Moreover, whenever a hash bucket has been used (whether the relevant data items are in memory or on disk), the corresponding bit is set in the bitmap which is always held completely in memory. At this point, Oracle tidies up the hash table, trying to get as many complete partitions into memory as possible and dumping any excess from other partitions to disk. As part of the rebuild, Oracle will reserve some clusters (a minimum of one per partition) for processing the probe table.

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, in a Month total cell, Sales_Year_ALL can be used as the total for all the years) or a total corresponding to a group on the other dimension (eg, in a Month total cell, Sales_City_ALL can be used as the total for all the cities and one year) A typical usage of these variables is to show measure values as percentages out of arbitrary level totals..

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