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Had I been able to complete the test (I have 2GB of real memory on this server and my SGA was 600MB; by the time I got to 325 users, the machine was paging and swapping to the point where it was impossible to continue), at 500 users I would have allocated around 2,750MB of RAM! So, the DBA would probably not set the SORT_AREA_SIZE to 5MB on this system, but rather to about 0.5MB, in an attempt to keep the maximum PGA usage at a bearable level at peak. Now at 500 users I would have had about 500MB of PGA allocated, perhaps similar to what we observed with automatic memory management but at times when there were fewer users, we would have still written to temp rather than performing the sort in memory. In fact, when running the preceding test with a SORT_AREA_SIZE of .5MB, we would observe the data in Table 4-3.

usable in more cases. The ability to transport a tablespace allows a DBA to move or copy the already formatted data files from one database and attach them to another for example, to immediately copy all of the tables and indexes from an Online Transaction Processing (OLTP) database to a Data Warehouse (DW). However, in many cases, the OLTP database might be using a small block size, such as 2KB or 4KB, whereas the DW would be using a much larger one (8KB or 16KB). Without support for multiple block sizes in a single database, you wouldn t be able to transport this information. Tablespaces with multiple block sizes should be used to facilitate transporting tablespaces; they are not generally used for anything else.

Table 4-3. PGA Memory Allocation Behavior with Increasing Numbers of Active Sessions, with SORT_AREA_SIZE Set to 0.5MB (Manual Memory Management)

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12.6.1 An overview of the rule engine Rule engines consist of two parts:

There will be the database default block size, which is the size specified in the initialization file during the CREATE DATABASE command. The SYSTEM tablespace will have this default block size always, but you can then create other tablespaces with nondefault block sizes of 2KB, 4KB, 8KB, 16KB and, depending on the operating system, 32KB. The total number of block sizes is six if and only if you

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specified a nonstandard block size (not a power of two) during database creation. Hence, for all practical purposes, a database will have at most five block sizes: the default size and then four other nondefault sizes. Any given tablespace will have a consistent block size, meaning that every block in that tablespace will be the same size. A multisegment object, such as a table with a LOB column, may have each segment in a tablespace with a different block size, but any given segment (which is contained in a tablespace) will consist of blocks of exactly the same size. Most blocks, regardless of their size, have the same general format, which looks something like Figure 3-2.

A mechanism for expressing the rules and facts A fast implementation for evaluating the rules and taking appropriate action

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Figure 3-2 The structure of a block Exceptions to this format include LOB segment blocks and hybrid columnar compressed blocks in Exadata storage, for example, but the vast majority of blocks in your database will resemble the format in Figure 3-2 The block header contains information about the type of block (table block, index block, and so on); transaction information when relevant (only blocks that are transaction-managed have this information a temporary sort block would not, for example) regarding active and past transactions on the block; and the address (location) of the block on the disk The next two block components are found on the most common types of database blocks, those of HEAP-organized tables We ll cover database table types in much more detail in 10 Database Tables, but suffice it to say that most tables are of this type.

Many of the rule engines are implementations of a well-known Rete algorithm.1 Others use a backward-reasoning algorithm. Using these algorithms, the engines can evaluate the rules several times faster than the procedural evaluation of equivalent if-then statements. Rules relate the facts pertaining to the current situation to corresponding actions. The set of facts is also called a knowledge base, or working memory. When it is run, the engine evaluates the rules based on the facts, and then triggers the actions associated with the rules that evaluate to true. The languages that the engines use to express the rules and facts vary widely from LISP-like syntax to pseudo-English. They all, however, express the if-then rules in some engine-specific way. New languages on the horizon, such as RuleML, offer the possibility of a standard way to express rules independently of the rule engine. Many rule engines are available, ranging from commercial offerings to free or open source projects. A few of them are implemented in Java. With these engines, Java objects are loaded into an engine s working memory as facts, and the engine can create facts based on those objects as well as invoke actions expressed in Java on those objects. 12.6.2 Using a rule engine Implementing business rules using a rule engine involves the following steps:

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