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A query that uses this index should expect to retrieve 2 to 3 percent or less of the rows to be accessed in the table On a fat table (ie, a table with many columns or very wide columns), this fraction might go all the way up to 20 to 25 percent of the table This advice doesn t always seem to make sense to everyone immediately; it is not intuitive, but it is accurate An index is stored sorted by index key The index will be accessed in sorted order by key The blocks that are pointed to are stored randomly in a heap Therefore, as we read through an index to access the table, we will perform lots of scattered, random I/O.

B*Tree or what I call conventional indexes are the most commonly used type of indexing structure in the database. They are similar in implementation to a binary search tree. Their goal is to minimize the amount of time Oracle spends searching for data. Loosely speaking, if you have an index on a number column, then the structure might conceptually look like Figure 11-1.

In the Database Content page, select Sample Schemas to include the Sample Schemas tablespace (EXAMPLE tablespace) in your database Oracle recommends you do this in order to use the examples based on the sample schemas such as HR and OE 12 In the Initialization Parameters page, you can set the initialization parameters related to the following four areas: Memory Sizing Character Sets Connection Mode Let s take a closer look at each of these areas before continuing with creating our database..

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The Memory window lets you set initialization parameters that control how the database manages the memory allocated to it. You can choose between the Typical and the Custom options to specify a method of memory management. The easiest way to manage memory is to select Typical and enter a percentage value, such as 40 percent. The instance will then use Automatic Memory Management, a new Oracle Database 11g feature, to automatically tune both the SGA and the PGA.

By scattered, I mean that the index will tell us to read block 1, block 1,000, block 205, block 321, block 1, block 1,032, block 1, and so on it won t ask us to read block 1, then block 2, and then block 3 in a consecutive manner We will tend to read and reread blocks in a very haphazard fashion This single block I/O can be very slow As a simplistic example of this, let s say we are reading that thin table via an index, and we are going to read 20 percent of the rows Assume we have 100,000 rows in the table Twenty percent of that is 20,000 rows If the rows are about 80 bytes apiece in size, on a database with.

Note There are block-level optimizations and compression of data that take place that make the real block

In the Sizing tab, you specify the database block size and the maximum number of user processes that can connect simultaneously to the database. For the block size, accept the default value, which is 8KB. For processes, use a number such as 150, unless you know that you have a larger number of processes.

Use the default value for the database character set, which supports the language used by the operating system for all database users and database applications.

structure look different from Figure 11-1.

an 8KB blocksize, we will find about 100 rows per block. That means the table has approximately 1,000 blocks. From here, the math is very easy. We are going to read 20,000 rows via the index; this will mean, quite likely 20,000 TABLE ACCESS BY ROWID operations. We will process 20,000 table blocks to execute this query. There are only about 1,000 blocks in the entire table, however! We would end up reading and processing each block in the table on average 20 times. Even if we increased the size of the row by an order of magnitude to 800 bytes per row, and 10 rows per block, we now have 10,000 blocks in the table. Index accesses for 20,000 rows would cause us to still read each block on average two times. In this case, a full table scan will be much more efficient than using an index, as it has to touch each block only once. Any query that used this index to access the data would not be very efficient until it accesses on average less than 5 percent of the data for the 800-byte column (then we access about 5,000 blocks) and even less for the 80-byte column (about 0.5 percent or less).

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