data type mapping for RMySQL

Hullo

I?m not sure whether this is a bug, but I would expect some sort of warning where mappings may lose precision.

I?ve got a mysql table with large numbers in it:

CREATE TABLE if not exists `tester` (
      `id` bigint(20) NOT NULL AUTO_INCREMENT,
      `address` bigint(20) NOT NULL,
      PRIMARY KEY (`id`),
      UNIQUE KEY `idx_address` (`address`)
    ) ENGINE=InnoDB AUTO_INCREMENT=78628 DEFAULT CHARSET=latin1 ;

The key aspect of this is that the ?address? column needs to be used to distinguish between values. If I put one value into this table, and read it back with the mysql client:

mysql> \. test.sql
Query OK, 1 row affected, 1 warning (0.00 sec)

Database changed
Query OK, 0 rows affected (0.05 sec)

Query OK, 1 row affected (0.01 sec)

+---------------------+
| address             |
+---------------------+
| 2029716610205351937 |
+---------------------+
1 row in set (0.00 sec)

But if I try to read the value using R:

library(RMySQL)

Loading required package: DBI

options(digits=20)

hubdb <- dbConnect("MySQL", username="root", host="localhost", password="dummy", dbname="dummy" )
q = sprintf("select * from tester;")


testvals <- fetch(dbSendQuery(hubdb, q), n=-1)

print (testvals)

address
1 2029716610205351936

Note that the address value is different

The issue is that the precision of the sql type (20 decimal characters) is larger than the precision of the R type that it?s been matched to.  I don?t know whether this is a bug or not - it would have help to have a warning about the possible precision mismatch, rather than to spot the emerging bug ;-) - that aside, is there a simple way to map the bigint type to something else, eg for this situation, character would do. I know that I can cast the type in the sql query, but I?d prefer to set the mapping at a more global scope if I could in the data definition.

tia

Tim