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Conditional formatting rules are applied in a specified order, and if a cell meets the criteria for multiple conflicting rules, it uses the formatting from the last rule. You can control the rules order, and move rules up or down in the list. Follow these instructions to change the rules order, so the Top 3 rule is applied last. 1. Select a cell in the pivot table, and on the Ribbon, click the Home tab. 2. In the Styles group, click Conditional Formatting, and then click Manage Rules. The Conditional Formatting Rules Manager dialog box opens, where you can see the two rules you created (see Figure 4-17).

The RAWTOHEX function is invoked implicitly by SQL*Plus when it fetches a RAW type into a string, and the HEXTORAW function is invoked implicitly when inserting the string. It is a good practice to avoid implicit conversions and to always be explicit when coding. So the previous examples could have been written as follows: ops$tkyte@ORA11GR2> select rawtohex(raw_data) from t; RAWTOHEX(RAW_DATA) -------------------------------FD1EB03D3718077BE030007F01002FF5 ops$tkyte@ORA11GR2> insert into t values ( hextoraw('abcdef') ); 1 row created.

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Oracle 10g and above supports three native datatypes suitable for storing numbers. Oracle9i Release 2 and earlier support exactly one native datatype suitable for storing numeric data. In this list, the NUMBER type is supported by all releases, and the subsequent two types are new datatypes supported only in Oracle 10g and above: NUMBER: The Oracle NUMBER type is capable of storing numbers with an extremely large degree of precision 38 digits of precision, in fact. The underlying data format is similar to a packed decimal representation. The Oracle NUMBER type is a variable length format from 0 to 22 bytes in length. It is appropriate for storing any number as small as 10e-130 and numbers up to but not including 10e126. This is by far the most common NUMBER type in use today. BINARY_FLOAT: This is an IEEE native single-precision floating-point number. On disk it will consume 5 bytes of storage: 4 fixed bytes for the floating-point number and 1 length byte. It is capable of storing numbers in the range of ~ 1038.53 with 6 digits of precision. BINARY_DOUBLE: This is an IEEE native double-precision floating-point number. On disk it will consume 9 bytes of storage: 8 fixed bytes for the floating-point number and 1 length byte. It is capable of storing numbers in the range of ~ 10308.25 with 13 digits of precision.

This is a simple wrapper around sqlite3_prepare_v2() and friends that executes a SQL statement and prints the results.

As you can see from this quick overview, the Oracle NUMBER type has significantly larger precision than the BINARY_FLOAT and the BINARY_DOUBLE types, but a much smaller range than the BINARY_DOUBLE. That is, you can store numbers very precisely with many significant digits in a NUMBER type, but you can store much smaller and larger numbers in the BINARY_FLOAT and BINARY_DOUBLE types. As a quick example, we can create a table with the various datatypes in them and see what is stored given the same inputs: ops$tkyte@ORA11GR2> create table t 2 ( num_col number, 3 float_col binary_float, 4 dbl_col binary_double 5 ) 6 / Table created. ops$tkyte@ORA11GR2> insert into t ( num_col, float_col, dbl_col ) 2 values ( 1234567890.0987654321, 3 1234567890.0987654321, 4 1234567890.0987654321 ); 1 row created. ops$tkyte@ORA11GR2> set numformat 99999999999.99999999999 ops$tkyte@ORA11GR2> select * from t; NUM_COL FLOAT_COL DBL_COL ------------------------ ------------------------ -----------------------1234567890.09876543210 1234567940.00000000000 1234567890.09876540000

Note that the NUM_COL returns the exact number we provided as input There are fewer than 38 significant digits in the input number (I supplied a number with 20 significant digits), so the exact number is preserved The FLOAT_COL, however, using the new BINARY_FLOAT type, was not able to accurately represent this number In fact, it preserved only 7 digits accurately The DBL_COL fared much better, accurately representing the number in this case out to 17 digits Overall, though, this should be a good indication that the BINARY_FLOAT and BINARY_DOUBLE types will not be appropriate for financial applications! If you play around with different values, you ll see different results: ops$tkyte@ORA11GR2> delete from t; 1 row deleted ops$tkyte@ORA11GR2> insert into t ( num_col, float_col, dbl_col ) 2 values ( 99999999999999999999, 3 99999999999999999999, 4 99999999999999999999 ); 1 row created.

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