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That was back in 2002 A Yeah, 2002 I think it was November 2002 Q That makes you probably one of the first thousand bloggers out there A It was a much smaller medium back then I guess I was impressed by the fact that there were quite a few people talking on that topic, which isn t really a mainstream topic Blogging was at the beginning I just started a cheap Blogspot blog straight away, and swapped out of that a few months later when I discovered some of the limitations of using that system, and set up a Movable Type blog with the help of a friend Q At that point, what were you doing for a living A I was a minister at a church completely different Q Very different What denomination A Baptist Q.



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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





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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

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We would not be able to view the contents directly of the root directory, but once we traversed into a subfolder, such as /Applications (possible because it is executable), we would be subject to the Application s folders permissions, and subsequently the permissions on any of the individual files in that subdirectory Now, because we don t have read access to list the contents of the root volume, we wouldn t be able to traverse into a subfolder unless we knew that it existed and what it was named But this type of security through obscurity can also be bypassed What we want to emphasize here is that denying users read privileges on a directory will not prevent them from traversing into its subdirectories, where they ll have any access granted at the applicable owner, group or everyone classes, a potentially less secure environment.

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

So that was 2002, and if I characterized where you were today as a full-time blogger who has stated several times that you re making income in excess of $100,000 a year American, would I be wrong A No, that s correct Still above that figure..

Modes are established on a file through the use of a bit-flag system To truly understand this system, it is best to look at it from a command line system (we will cover GUI permissions a bit further on in this section) For example, consider the list of files and directories in the /Users folder that the command ls al /Users produces, shown in Figure 4 1..

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,

Figure 4 1. Output of command `ls al /Users` with Permissions, owner, group, and folder name identified.

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