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This histogram points out that the first and last partitions have just half as many rows as the interior partitions. The data is not very evenly distributed at all. We ll see the trend continue for six and seven hash partitions: ops$tkyte@ORA11GR2> exec hash_proc( 6, :x ); PL/SQL procedure successfully completed. PN CNT HG -- ---------- -----------------------------p1 6104 ************** p2 6175 *************** p3 12420 ****************************** p4 12106 ***************************** p5 6040 ************** p6 6009 ************** 6 rows selected. ops$tkyte@ORA11GR2> exec hash_proc( 7, :x ); PL/SQL procedure successfully completed. PN CNT HG -- ---------- -----------------------------p1 6105 *************** p2 6176 *************** p3 6161 *************** p4 12106 ****************************** p5 6041 *************** p6 6010 *************** p7 6263 *************** 7 rows selected. As soon as we get back to a number of hash partitions that is a power of two, we achieve the goal of even distribution once again: ops$tkyte@ORA11GR2> exec hash_proc( 8, :x ); PL/SQL procedure successfully completed. PN CNT HG -- ---------- -----------------------------p1 6106 ***************************** p2 6178 ***************************** p3 6163 ***************************** p4 6019 **************************** p5 6042 **************************** p6 6010 **************************** p7 6264 ****************************** p8 6089 ***************************** 8 rows selected. If we continue this experiment up to 16 partitions, we would see the same effects for the ninth through the fifteenth partitions a skewing of the data to the interior partitions, away from the edges and then upon hitting the sixteenth partition, you would see a flattening-out again. The same would be true again up to 32 partitions, and then 64, and so on. This example just points out the importance of using a power of two as the number of hash partitions.

List partitioning was a new feature of Oracle9i Release 1. It provides the ability to specify in which partition a row will reside, based on discrete lists of values. It is often useful to be able to partition by some code, such as a state or region code. For example, we might want to pull together in a single partition all records for people in the states of Maine (ME), New Hampshire (NH), Vermont (VT), and Massachusetts (MA), since those states are located next to or near each other and our application queries data by geographic region. Similarly, we might want to group together Connecticut (CT), Rhode Island (RI), and New York (NY). We can t use a range partition, since the range for the first partition would be ME through VT, and the second range would be CT through RI. Those ranges overlap. We can t use hash partitioning since we can t control which partition any given row goes into; the built-in hash function provided by Oracle does that. With list partitioning, we can accomplish this custom partitioning scheme easily: ops$tkyte@ORA11GR2> create table list_example 2 ( state_cd varchar2(2), 3 data varchar2(20) 4 ) 5 partition by list(state_cd) 6 ( partition part_1 values ( 'ME', 'NH', 'VT', 'MA' ), 7 partition part_2 values ( 'CT', 'RI', 'NY' ) 8 ) 9 / Table created. Figure 13-3 shows that Oracle will inspect the STATE_CD column and, based on its value, place the row into the correct partition.

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Looks simple enough, but the outcomes (notice plural) are as follows: Only one user at a time may process a transaction row. You need to update that row to increment a counter, and this will cause your program to serialize on that operation. At best, one person at a time will generate a new value for this key. In Oracle (and the behavior might be different in other databases), all but the first user to attempt to concurrently perform this operation would receive the error ORA-08177: can't serialize access for this transaction in the SERIALIZABLE isolation level.

Table 3-1. Potential Entities Discovered in the Initial Design Project manager Project name Administrator Resource Supervisor List of roles List of resources Project Start date List of projects Employee name List of assignments Assignment List of assigned resources Project number End date Employee Employee ID Role Date assigned

For example, using a serializable transaction (which is more common in the J2EE environment, where many tools automatically use this as the default mode of isolation, often unbeknownst to the developers), you would observe the following behavior. Notice that the SQL prompt contains information about which session is active in this example: OPS$TKYTE session(261,2586)> set transaction isolation level serializable; Transaction set. OPS$TKYTE session(261,2586)> update id_table 2 set id_value = id_value+1 3 where id_name = 'MY_KEY'; 1 row updated. OPS$TKYTE session(261,2586)> select id_value 2 from id_table 3 where id_name = 'MY_KEY'; ID_VALUE ---------2 Now, we ll go to another SQL*Plus session and perform the same operation, a concurrent request for a unique id: OPS$TKYTE session(271,1231)> set transaction isolation level serializable; Transaction set. OPS$TKYTE session(271,1231)> update id_table 2 set id_value = id_value+1 3 where id_name = 'MY_KEY'; This will block at this point, as only one transaction at a time can update the row. This demonstrates the first possible outcome we would block and wait for the row. But since we re using SERIALIZABLE in Oracle, we ll observe the following behavior as we commit the first session s transaction: OPS$TKYTE session(261,2586)> commit; Commit complete. The second session will immediately display the following error: OPS$TKYTE session(271,1231)> update id_table 2 set id_value = id_value+1 3 where id_name = 'MY_KEY';

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