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In a hash cluster, this query would result in a full table scan unless you had an index on the DEPTNO column Only exact equality searches (including IN lists and subqueries) may be made on the hash key without using an index that supports range scans In a perfect world, with nicely distributed hash key values and a hash function that distributes them evenly over all of the blocks allocated to the hash cluster, we can go straight from a query to the data with one I/O In the real world, we will end up with more hash key values hashing to the same database block address than fit on that block This will result in Oracle having to chain blocks together in a linked list to hold all of the rows that hash to this block.

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HelloWorld() = "Hello world from F#!" The assembly that must be exposed as a COM component should be added to the global assembly cache (GAC), which is where shared NET assemblies are stored Assemblies present in the GAC must be strongly named, which means a public key cryptographic signature must be used to certify the assembly To perform the test, you generate a key pair to be used to sign the assembly using the snexe command available with the NET SDK: C:> sn k testkeysnk Microsoft (R) NET Framework Strong Name Utility Version 205072742 Copyright (c) Microsoft Corporation All rights reserved Key pair written to testkeysnk Now you can compile the program in a DLL called hwfsdll: C:\> fsc -a keyfile testkeysnk hwfs.

Now, when we need to retrieve the rows that match our hash key, we might have to visit more than one block Like a hash table in a programming language, hash tables in the database have a fixed size When you create the table, you must determine the number of hash keys your table will have, forever That does not limit the amount of rows you can put in there In Figure 10-9, we can see a graphical representation of a hash cluster with table EMP created in it When the client issues a query that uses the hash cluster key in the predicate, Oracle will apply the hash function to determine which block the data should be in It will then read that one block to find the data.

If there have been many collisions, or the SIZE parameter to the CREATE CLUSTER was underestimated, Oracle will have allocated overflow blocks that are chained off the original block..

fs Note that you use the keyfile switch to indicate to the compiler that the output should be signed using the specified key pair Now you can add the assembly to the GAC (note that under Windows Vista the shell used should run with administrator privileges): C:\ > gacutil /i hwfsdll Microsoft (R) NET Global Assembly Cache Utility Version 205072742 Copyright (c) Microsoft Corporation All rights reserved Assembly successfully added to the cache.

Figure 10-9 Depiction of a hash cluster When you create a hash cluster, you ll use the same CREATE CLUSTER statement you used to create the index cluster with different options You ll just be adding a HASHKEYS option to it to specify the size of the hash table Oracle will take your HASHKEYS value and round it up to the nearest prime number; the number of hash keys will always be a prime Oracle will then compute a value based on the SIZE parameter multiplied by the modified HASHKEYS value It will allocate at least that much space in bytes for the cluster This is a big difference from the preceding index cluster, which dynamically allocates space as it needs it A hash cluster pre-allocates enough space to hold (HASHKEYS/trunc(blocksize/SIZE)) bytes of data.

For example, if you set your SIZE to 1,500 bytes and you have a 4KB block size, Oracle will expect to store two keys per block If you plan on having 1,000 HASHKEYs, Oracle will allocate 500 blocks It is interesting to note that unlike a conventional hash table in a computer language, it is OK to have hash collisions in fact, it is desirable in many cases If you take the same DEPT/EMP example from earlier, you could set up a hash cluster based on the DEPTNO column Obviously, many rows will hash to the same value, and you expect them to (they have the same DEPTNO) This is what the cluster is about in some respects: clustering like data together.