MATCH Examples
Suppose you want to find out if you have customers who have never bought
anything:
CLEAR
A
FILL
A SALES
MATCH
A SALES THRU CUST# WITH CUSTOMERS
FILL
B CUSTOMERS
C
CUSTOMERS = A XOR B
First, make sure that A is clear. Then via the FILL and MATCH we isolate in A
all the customers who have bought something. In B we isolate all the customers.
The last line subtracts the two subsets so that at the end of this, if the
CUSTOMERS portion of C is non-zero, it contains customers who have never bought
anything.
MATCHing in the Same Table
Suppose you want to find out what else your "Blue Suit" customers are
buying. You exclude customer AA0000 as that one buys large quantities of
everything:
FIND
A SALES WHERE DESCR="BLUE SUIT" AND CUST# NE AA0000
MATCH
A SALES THRU CUST# WITH SALES
Now use a SHOW command to see what else the Blue Suit customers are buying:
SHOW
A SALES DESCR
MATCH When Fields Sharing The Same Data Have Different Names
An example of this can be found in the Example Data Base in the relationship
between the INVENTORY and ASSEMBLIES tables.
Some of the Inventory records are marked as Make as opposed to Buy
(from vendors). The manufacturing assembly trees associated with these
Inventory records are stored in the ASSEMBLIES table.
All of the records that make up an assembly tree for a particular inventory
item contain the inventory's ITEM# as a common identifier. This data is contained
in the field called TREE in the ASSEMBLIES table.
So, a one-to-many relationship exists between INVENTORY and ASSEMBLIES. The
only thing exceptional about it is that the fields that share the common data
have different names. That's what the ON is for:
CLEAR
A
FIND
A INVENTORY WHERE DESCRIPTION SV JET
MATCH
A INVENTORY THRU ITEM# WITH ASSEMBLIES ON TREE
The object of this sequence is to find the assemblies tree that describes the
Jet Plane. But the query was still based on something familiar rather than
esoteric.
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