$\backslash$table$[[$EXISTING$\_$CUSTOMER$],[$Customer$\_$ID$],[$Customer$\_$FirstName$],[$Customer$\_$LastName$],[$Address$\_1],[$Address$\_2],[$City$],[$State$],[$Zip$],[$Country$]]$

You may have heard about the address matching exercise. For example: A company has a customer database which includes all existing customers' information. We would like to determine the number of existing customers by State from daily transaction records. i$.$e$.$ the number of existing customers who made the purchases$($s$)$ recently from daily transactions and as result, we will be able to determine the number of repetitive customers.

You need to write a SQL that compares the addresses $($TRANSACTION$)$ to the address attributes of a reference dataset $($EXISTING$\_$CUSTOMER$)$ to determine whether the first $20$ characters of a particular address $($from the TRANSACTION table$)$ would be the same as an address of the existing customer address $($from the EXISTING$\_$CUSTOMER table$).$ You may also need to consider additional attributes which improve the accuracy of the address matching.

$(15$ points$)$