MySQL: Getting data for histogram plot?

Question

Is there a way to specify bin sizes in MySQL? Right now, I am trying the following SQL query:

select total, count(total) from faults GROUP BY total;

The data that is being generated is good enough but there are just too many rows. What I need is a way to group the data into predefined bins. I can do this from a scripting language, but is there a way to do it directly in SQL?

Example:

+-------+--------------+
| total | count(total) |
+-------+--------------+
|    30 |            1 | 
|    31 |            2 | 
|    33 |            1 | 
|    34 |            3 | 
|    35 |            2 | 
|    36 |            6 | 
|    37 |            3 | 
|    38 |            2 | 
|    41 |            1 | 
|    42 |            5 | 
|    43 |            1 | 
|    44 |            7 | 
|    45 |            4 | 
|    46 |            3 | 
|    47 |            2 | 
|    49 |            3 | 
|    50 |            2 | 
|    51 |            3 | 
|    52 |            4 | 
|    53 |            2 | 
|    54 |            1 | 
|    55 |            3 | 
|    56 |            4 | 
|    57 |            4 | 
|    58 |            2 | 
|    59 |            2 | 
|    60 |            4 | 
|    61 |            1 | 
|    63 |            2 | 
|    64 |            5 | 
|    65 |            2 | 
|    66 |            3 | 
|    67 |            5 | 
|    68 |            5 | 
------------------------

What I am looking for:

+------------+---------------+
| total      | count(total)  |
+------------+---------------+
|    30 - 40 |            23 | 
|    40 - 50 |            15 | 
|    50 - 60 |            51 | 
|    60 - 70 |            45 | 
------------------------------

I guess this cannot be achieved in a straight forward manner but a reference to any related stored procedure would be fine as well.

Answer 1

You need to make a Procedure for this, only with SQL is not possible.

Answer 2

SELECT b.*,count(*) as total FROM bins b 
left outer join table1 a on a.value between b.min_value and b.max_value 
group by b.min_value

The table bins contains columns min_value and max_value which define the bins. note that the operator "join... on x BETWEEN y and z" is inclusive.

table1 is the name of the data table

Answer 3

Ofri Raviv's answer is very close but incorrect. The count(*) will be "1" even if there are zero results in a histogram interval. The query needs to be modified to use a conditional sum:

SELECT b.*, SUM(a.value IS NOT NULL) AS total FROM bins b
  LEFT JOIN a ON a.value BETWEEN b.min_value AND b.max_value
GROUP BY b.min_value;

Answer 4

I made a procedure that can be used to automatically generate a temporary table for bins according to a specified number or size, for later use with Ofri Raviv's solution.

CREATE PROCEDURE makebins(numbins INT, binsize FLOAT) # binsize may be NULL for auto-size
BEGIN
 SELECT FLOOR(MIN(colval)) INTO @binmin FROM yourtable;
 SELECT CEIL(MAX(colval)) INTO @binmax FROM yourtable;
 IF binsize IS NULL 
  THEN SET binsize = CEIL((@binmax-@binmin)/numbins); # CEIL here may prevent the potential creation a very small extra bin due to rounding errors, but no good where floats are needed.
 END IF;
 SET @currlim = @binmin;
 WHILE @currlim + binsize < @binmax DO
  INSERT INTO bins VALUES (@currlim, @currlim+binsize);
  SET @currlim = @currlim + binsize;
 END WHILE;
 INSERT INTO bins VALUES (@currlim, @maxbin);
END;

DROP TABLE IF EXISTS bins; # be careful if you have a bins table of your own.
CREATE TEMPORARY TABLE bins (
minval INT, maxval INT, # or FLOAT, if needed
KEY (minval), KEY (maxval) );# keys could perhaps help if using a lot of bins; normally negligible

CALL makebins(20, NULL);  # Using 20 bins of automatic size here. 

SELECT bins.*, count(*) AS total FROM bins
LEFT JOIN yourtable ON yourtable.value BETWEEN bins.minval AND bins.maxval
GROUP BY bins.minval

This will generate the histogram count only for the bins that are populated. David West ought to be right in his correction, but for some reason, unpopulated bins do not appear in the result for me (despite the use of a LEFT JOIN — I do not understand why).