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I have to make a couple of passes on this data First, I find all records that were modified only on the Palm and make the corresponding changes in Oracle Next, I find all records that were modified on both the Palm and my database since the last synchronization and rectify them Then I find all records that were modified only on the database and place their changes into the temporary table Lastly, the Palm sync application pulls the changes from the temporary table and applies them to the Palm device itself Upon disconnection, the temporary data goes away The issue I encountered, however, is that because the permanent tables were analyzed, the CBO was being used The temporary table had no statistics on it (you can analyze the temporary table, but no statistics are gathered), and the CBO would guess many things about it.

The figure is a little higher than this due to the way extents are rounded and/or by using locally managed tablespaces with uniformly sized extents This example points out one of the issues with hash clusters you need to be aware of Normally, if we create an empty table, the number of blocks under the HWM for that table is 0 If we full scan it, it reaches the HWM and stops With a hash cluster, the tables will start out big and will take longer to create, as Oracle must initialize each block, an action that normally takes place as data is added to the table They have the potential to have data in their first block and their last block, with nothing in between Full scanning a virtually empty hash cluster will take as long as full scanning a full hash cluster.

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I, as the developer, knew the average number of rows I might expect, the distribution of the data, the selectivity of the indexes, and so on I needed a way to inform the optimizer of these better guesses There are three ways to give the optimizer statistics on the global temporary tables One is via dynamic sampling (new in Oracle9i Release 2 and above) and the other is the DBMS_STATS package, which has two ways to accomplish this First, let s look at dynamic sampling Dynamic sampling is the optimizer s ability, when hard parsing a query, to scan segments in the database (sample them) to collect statistics useful in optimizing that particular query It is akin to doing a miniature gather statistics command during a hard parse.

This is not necessarily a bad thing; we built the hash cluster to have very fast access to the data by a hash key lookup We did not build it to full scan it frequently Now we can start placing tables into the hash cluster in the same fashion we did with index clusters: Ops$tkyte@ORA11GR2> create table hashed_table 2 ( x number, data1 varchar2(4000), data2 varchar2(4000) ) 3 cluster hash_cluster(x); Table created To see the difference a hash cluster can make, I set up a small test I created a hash cluster, loaded some data in it, copied this data to a regular table with a conventional index on it, and then did random reads on each table (the same random reads on each) Using runstats, SQL_TRACE, and TKPROF, I was able to determine the characteristics of each.

public class TestAssociation { public static void main(String[] args) throws Exception { SavingsAccount account1 = new SavingsAccount(12245); SavingsAccount account2 = new SavingsAccount(67890); account1.credit(100); account1.debit(100); account2.credit(100); account2.debit(100); } }

The following is the setup I performed, followed by the analysis: ops$tkyte%ORA11GR2> create cluster hash_cluster 2 ( hash_key number ) 3 hashkeys 75000 4 size 150 5 / Cluster created ops$tkyte%ORA11GR2> create table t_hashed 2 cluster hash_cluster(object_id).

In Oracle 10g, dynamic sampling will work out of the box, because the default setting has been increased from 1 to 2, and at level 2, the optimizer will dynamically sample any unanalyzed object referenced in a query processed by the optimizer prior to evaluating the query plan In 9i Release 2,.

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