OK, I think what I will do is create a new BIGINT column with 
AUTO_INCREMENT and use that as my primary key, and just pass that column 
along with my VARCHAR columns to FT_CREATE_INDEX. Thank you for the help.

On Friday, March 8, 2013 8:42:30 AM UTC-5, Noel Grandin wrote:
>
>  No, it will add all of the columns to the index.
>
> On 2013-03-08 15:31, Zach wrote:
>  
> The BINARY column is always 20 bytes (a SHA1 hash). Can I assume 
> that FT_CREATE_INDEX will not try to tokenize this column if I pass NULL in 
> the third parameter? Like I said, I need this column to be present in the 
> indexed table, so I can properly JOIN it on the original table, but I don't 
> want it to try indexing a SHA1 hash (i.e. try to find tokens that may 
> randomly exist in the hash).
>
> On Friday, March 8, 2013 1:18:44 AM UTC-5, Thomas Mueller wrote: 
>>
>> Hi, 
>>
>>  It's absolutely no problem to use a primary key of type binary. It's 
>> not inefficient if the data is small (even thought bigint is faster).
>>
>>  For fulltext indexing, it makes sense to only index those columns that 
>> you are interested in (CLOB columns mainly).
>>
>>  Regards,
>> Thomas
>>
>>   
>>
>> On Fri, Mar 8, 2013 at 2:52 AM, Ryan How <[email protected]> wrote:
>>
>>> I think you've figured it out yourself. You'd have to have a pretty 
>>> compelling use case to use a BINARY column for a PK I think. It would be 
>>> very inefficient! Unless it is a really small BINARY column. 
>>>
>>>
>>> On 7/03/2013 10:23 PM, Zach wrote:
>>>
>>>> I have a table with a BINARY column that acts as a primary key. I want 
>>>> to index this table for searching, but I obviously don't want it to index 
>>>> this column. When I call "FT_CREATE_INDEX('PUBLIC', 'TEST', NULL)" on the 
>>>> table, will it ignore the column because it's BINARY, or will it try 
>>>> indexing it?
>>>>
>>>> I know I can specify a comma-delimited list of columns in the third 
>>>> parameter. However, since this BINARY column acts as a primary key, I 
>>>> think 
>>>> I need it in the indexed table so I can properly JOIN it to the original 
>>>> table.
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>>>>  
>>>
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