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Note that our step function is called str_agg_step(), and our finalizing function is called str_agg_finalize(). Also, this aggregate is registered as taking only one argument.

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

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

Listing 7-3 shows the str_agg_step() function. Listing 7-3. The str_agg() Step Function void str_agg_step(sqlite3_context* ctx, int ncols, sqlite3_value** values) { SAggCtx *p = (SAggCtx *) sqlite3_aggregate_context(ctx, sizeof(*p)); static const char delim [] = ", "; char *txt = sqlite3_value_text(values[0]); int len = strlen(txt); if (!p->result) { p->result = sqlite_malloc(len + 1); memcpy(p->result, txt, len + 1); p->chrCnt = len; } else { const int delimLen = sizeof(delim); p->result = sqlite_realloc(p->result, p->chrCnt + len + delimLen + 1); memcpy(p->result + p->chrCnt, delim, delimLen); p->chrCnt += delimLen; memcpy(p->result + p->chrCnt, txt, len + 1); p->chrCnt += len; } The value SAggCtx is a struct that is specific to this example and is defined as follows: typedef struct SAggCtx SAggCtx; struct SAggCtx { int chrCnt; char *result; }; Our structure serves as our state between aggregate iterations (calls to the step function), maintaining the growing concatenation of text, and the character count.

Figure 4-19. Comparing Outline Form (left) and Tabular Form (right)

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,

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

The first order of business is to retrieve the structure for the given aggregate instance. This is done using sqlite3_aggregate_context(). As mentioned earlier, the first call to this function allocates the data for the given context and subsequent calls retrieve it. The structure memory is automatically freed when the aggregate completes (after str_agg_finalize() is called). Note that sqlite3_aggregate_context() might return NULL if the system is low on memory. Such error checking is omitted in this example, for brevity,

Your pivot table is in the default Compact Form report layout. When you add fields to the Row Labels area, each additional field is indented from the field above it. You would like to slightly increase the indentation, to make the labels easier to read. This example is based on the Regions.xlsx workbook.

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