There are some options you will need to consider

InnoDB Buffer Pool

The reason 26G was picked is that you have 32GB of RAM and 80% of that is 25.6 G. Since you mentioned that you will have 100 databases and 100 applications making this a multitenant DB Server, you are going to have to get the InnoDB Buffer Pool just right.

Please run this query:

SELECT IFNULL(B.engine,'Total') "Storage Engine",
CONCAT(LPAD(REPLACE(FORMAT(B.DSize/POWER(1024,pw),3),',',''),17,' '),' ',
SUBSTR(' KMGTP',pw+1,1),'B') "Data Size", CONCAT(LPAD(REPLACE(
FORMAT(B.ISize/POWER(1024,pw),3),',',''),17,' '),' ',
SUBSTR(' KMGTP',pw+1,1),'B') "Index Size", CONCAT(LPAD(REPLACE(
FORMAT(B.TSize/POWER(1024,pw),3),',',''),17,' '),' ',
SUBSTR(' KMGTP',pw+1,1),'B') "Table Size" FROM
(SELECT engine,SUM(data_length) DSize,SUM(index_length) ISize,
SUM(data_length+index_length) TSize FROM
information_schema.tables WHERE table_schema NOT IN
('mysql','information_schema','performance_schema') AND
engine IS NOT NULL GROUP BY engine WITH ROLLUP) B,
(SELECT 3 pw) A ORDER BY TSize;

This will tell you how much space is currently occupied by your MySQL instance. Whatever the total of InnoDB Data Size and Index Size is, that is what you use. If that total is over the 80% limit then you must you the 80% (leaving innodb_buffer_pool_size at 26G).

Since you have a quad-core server, set innodb_buffer_pool_instances to 4.

InnoDB Transaction Log Files

Since 26G was selected as innodb_buffer_pool_size, you are going to need the biggest possible transaction logs. The value 512M was probably picked for innodb_log_file_size because there is nothing to suggest the amount of transaction data (in bytes) that will actually be processed.

To resize your transaction logs

mysql -u... -p... -e"SET GLOBAL innodb_fast_shutdown = 0;"
service mysql stop

Next edit my.cnf, replacing

innodb_log_file_size           = 512M

with this

innodb_log_file_size           = 2047M

Then, replace the transaction logs like this

mv /var/lib/mysql/ib_logfile0 /var/lib/mysql/ib_logfile0.bak
mv /var/lib/mysql/ib_logfile1 /var/lib/mysql/ib_logfile1.bak
service mysql start

After a few months of peak activity, you could then run this query during a peak:

SET @TimeInterval = 300;
SELECT variable_value INTO @num1 FROM information_schema.global_status
WHERE variable_name = 'Innodb_os_log_written';
SELECT SLEEP(@TimeInterval);
SELECT variable_value INTO @num2 FROM information_schema.global_status
WHERE variable_name = 'Innodb_os_log_written';
SET @ByteWrittenToLog = @num2 - @num1;
SET @KB_WL = @ByteWrittenToLog / POWER(1024,1) * 3600 / @TimeInterval;
SET @MB_WL = @ByteWrittenToLog / POWER(1024,2) * 3600 / @TimeInterval;
SET @GB_WL = @ByteWrittenToLog / POWER(1024,3) * 3600 / @TimeInterval;
SELECT @KB_WL,@MB_WL,@GB_WL;

Based on what comes back, you should resize the transaction logs again.

Please see my earlier posts on doing this:

• Jul 21, 2012 : InnoDB - High disk write I/O on ibdata1 file and ib_logfile0
• Feb 16, 2011 : How to safely change MySQL innodb variable 'innodb_log_file_size'?

Multicore Engagement

When the InnoDB Plugin was introduced in MySQL 5.1.38, it set the world of MySQL on fire. Why? Because InnoDB was single threaded. You had to install the plugin to have new setting that allowed InnoDB to use multiple cores.

Rather than writing something lengthy, please read my earlier posts of tweaking MySQL 5.5 to have InnoDB utilitze multiple cores:

• May 26, 2011 : About single threaded versus multithreaded databases performance
• Sep 12, 2011 : Possible to make MySQL use more than one core?
• Sep 20, 2011 : Multi cores and MySQL Performance

You can simplify your query to something along these lines. I expect MySQL will generate a simpler execution plan.

SELECT date(date) period, count(*) clicks
FROM visits
WHERE url_id = 3
  AND DATE > DATE_SUB( CURRENT_TIMESTAMP( ) , INTERVAL 1 MONTH ) 
GROUP BY period;

If returning results on high-traffic links in one second is a hard requirement, you might need to upgrade your hardware.

Expect to need an index on each column used in a WHERE clause. You might benefit from some multicolumn indexes; {url_id, date} is a candidate.

Test at scale, if that's at all possible. (It's usually possible, although it might take some time.) Use EXPLAIN to see what MySQL is doing with your queries.

You don't have to query browsers, countries, and everything else all at one time. When I was running web development, I rarely looked at countries--they weren't relevant to the niche I was working in. Also consider other asynchronous UI technologies.

PostgreSQL has a better optimizer. It might work better than MySQL. Test it.