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AutoNumber

This statement creates a unique integer value for each distinct evaluated value in a field encountered during the script execution.

You can also use the autonumber - script function function inside a LOAD statement, but this has some limitations when you want to use an optimized load. You can create an optimized load by loading the data from a QVD file first, and then using the AutoNumber statement to convert values to symbol keys.

Syntax:  

AutoNumber *fieldlist [Using namespace] ]

Arguments:  

Arguments
Argument Description
*fieldlist

A comma-separated list of the fields where the values should be replaced by a symbol key.

You can use wildcard characters ? and * in the field names to include all fields with matching names. You can also use * to include all fields. You need to quote field names when wildcards are used.

namespace

Using namespace is optional. You can use this option if you want to create a namespace, where identical values in different fields share the same key.

If you do not use this option all fields will have a separate key index.

Limitations:  

When you have several LOAD statements in the script, you need to place the AutoNumber statement after the final LOAD statement.

Example:

In this example we replace field values with symbol table keys using the AutoNumber statement to conserve memory. The example is brief for demonstration purpose, but would be meaningful with a table containing a large number of rows.

Example data
Region Year Month Sales
North 2014 May 245
North 2014 May 347
North 2014 June 127
South 2014 June 645
South 2013 May 367
South 2013 May 221

The source data is loaded using inline data. Then we add an AutoNumber statemenet with the Region, Year and Month fields.

RegionSales: LOAD * INLINE [ Region, Year, Month, Sales North, 2014, May, 245 North, 2014, May, 347 North, 2014, June, 127 South, 2014, June, 645 South, 2013, May, 367 South, 2013, May, 221 ]; AutoNumber Region, Year, Month;

The resulting table would look like this:

Results table
Region Year Month Sales
1 2 1 245
1 2 1 347
1 2 2 127
2 2 2 645
2 1 1 367
2 1 1 221

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