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In general, the Oracle NUMBER type is the best overall choice for most applications. However, there are performance implications associated with that type. The Oracle NUMBER type is a software datatype it is implemented in the Oracle software itself. We cannot use native hardware operations to add two NUMBER types together, as it is emulated in the software. The floating-point types, however, do not have this implementation. When we add two floating-point numbers together, Oracle will use the hardware to perform the operation. This is fairly easy to see. If we create a table that contains about 50,000 rows and place the same data in there using the NUMBER and BINARY_FLOAT/BINARY_DOUBLE types as follows ops$tkyte@ORA11GR2> 2 ( num_type 3 float_type 4 double_type 5 ) 6 / create table t number, binary_float, binary_double

Table created. ops$tkyte@ORA11GR2> insert /*+ APPEND */ 2 select rownum, rownum, rownum 3 from all_objects 4 / 72089 rows created. ops$tkyte@ORA11GR2> commit; Commit complete. we then execute the same query against each type of column, using a complex mathematical function such as LN (natural log). We observe in a TKPROF report radically different CPU utilization: select sum(ln(num_type)) from t call count cpu elapsed ------- ------ -------- ---------total 4 4.45 4.66 select sum(ln(float_type)) from t call count ------- -----total 4 cpu elapsed -------- ---------0.07 0.08 into t

select sum(ln(double_type)) from t call count ------- -----total 4 cpu elapsed -------- ---------0.06 0.06

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As you can see, BusinessBase inherits from UndoableBase and then implements a lot of different interfaces. Some of these are standard .NET interfaces to support things such as data binding, while others are defined by CSLA .NET and are used within the framework itself or as extensibility points for users of the framework. This class pulls together a lot of functionality. The goal is to abstract all this functionality into a set of easily understood behaviors that simplify the creation of business objects. Table 6-4 lists the functional areas.

The Oracle NUMBER type used some 63 times the CPU of the floating-point types in this example. But, you have to remember that we did not receive precisely the same answer from all three queries! ops$tkyte%ORA11GR2> set numformat 999999.9999999999999999 ops$tkyte%ORA11GR2> select sum(ln(num_type)) from t; SUM(LN(NUM_TYPE)) -------------------------734280.3209126472927309 ops$tkyte%ORA11GR2> select sum(ln(double_type)) from t; SUM(LN(DOUBLE_TYPE)) -------------------------734280.3209126447300000 The floating-point numbers were an approximation of the number, with between 6 and 13 digits of precision. The answer from the NUMBER type is much more precise than from the floats. However, when you are performing data mining or complex numerical analysis of scientific data, this loss of precision is typically acceptable, and the performance gain to be had can be dramatic.

Note If you are interested in the gory details of floating-point arithmetic and the subsequent loss of precision,

Data binding Business rules Authorization rules Object status tracking Root, parent, and child behaviors N-level undo

The NTP Synchronization project is spearheaded by David Mills of the University of Delaware with the participation of graduate students and volunteers. Funding for the project comes from such notables in the field of cutting-edge communications and space research as the Defense Advanced Research Projects Agency (DARPA), the National Science Foundation (NSF), Jet Propulsion Laboratories (JPL), the National Aeronautics and Space Administration (NASA), and the Navy Surface Weapons Center (NSWC). The time synchronization project stems from a growing recognition that even though NTP version 3 and even some early deployments of version 4 (not standardized as of the time of this writing) may be adequate for many networking environments, the NTP that can scale across the Internet needs to be more robust. Two areas of great concern are The need for autoconfiguration: Currently, the process of NTP configuration is manual, which makes it very unscalable in large and diverse networks. The lack of configuration scalability can become pronounced either during initial configuration or when NTP servers or primary clock sources become compromised because of damage, outright destruction, or prolonged communication links failures. See 5 for NTP configuration examples.

It should be noted that in this case we can sort of have our cake and eat it, too. Using the built-in CAST function, we can perform an on-the-fly conversion of the Oracle NUMBER type to a floating-point type, prior to performing the complex math on it. This results in a CPU usage that is much nearer to that of the native floating-point types: select sum(ln(cast( num_type as binary_double ) )) from t call count ------- -----total 4 cpu elapsed -------- ---------0.08 0.08

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