is there a limit to what sql fiddle can handle? sql fiddle doesn't compile anything and returns no error messages

Question

I recently created a query that compiles successfully and returns the desired result. When I used that piece of code as a subquery in another piece of code that a user on stackoverflow came up with for me, I encountered a few problems, which were ultimately solved. I attempted to use this query as a subquery in that piece of code given to me. However, sql fiddle doesn't return anything. No errors or compiled messages. When I tried putting in a syntax error on purpose-like a random + sign, nothing happened. is it because the query is too long?

schema

CREATE TABLE sampleData 
    (
     id MEDIUMINT NOT NULL AUTO_INCREMENT,
      timecode int, 
     count int,
      PRIMARY KEY (id)
    )
#ENGINE=MyISAM
;

INSERT INTO sampleData
(timecode, count)
VALUES
(1344893440, 1), ( 1346014720, 1),( 1344898688,1),( 1345654784,1),( 1345978368,1),
( 1345959296,1), (1345064704,1), ( 1345156352,1),( 1345225600,1),
(1345017984,1),( 1345640960,1),( 1346019968,1),( 1345834752,1),
( 1345438464,1),( 1344986880,1),( 1345045632,1),( 1345557888,1),( 1344973056,1),( 1345087232,1),( 1345433216,1),( 1345691008,1),
( 1344917760,1),( 1345253248,1),( 1344934912,1),( 1345890048,1),( 1345272448,1), (1345829504,1),( 1345798400,1),( 1345203200,1),( 1344741120,1),
( 1345175552,1),( 1344824192,1),( 1344926336,1),( 1345571712,1),( 1344931584,1),( 1345211776,1),( 1345059456,1),( 1345516288,1),( 1345441920,1),( 1346009472,1)

query

select t_0.*,
           (coalesce(t_3.average_number_of_votes_per_previous_period_days, 0) - coalesce(t_4.average_number_of_votes_per_previous_period_days, 0)) * 100.0
    from 
        (select t.*,
           (coalesce(t_1.count, 0) - coalesce(t_2.count, 0)) * 100.0 as "percentage increase in count in %"
    from  
    (
      SELECT sum(1) AS ordr,
      t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"

      FROM 
        (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
        FROM sampleData
        GROUP BY DAY) t1
        INNER JOIN 
        (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
        FROM sampleData
        GROUP BY DAY) t2 
        on t1.day >= t2.day                                                                                                                                
        GROUP BY t1.day, t1.count
        ORDER BY t1.day
        )t 
      left outer join
         (
          SELECT sum(1) AS ordr,
            t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"
          FROM 
            (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
            FROM sampleData
            GROUP BY DAY) t1
          INNER JOIN 
            (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
            FROM sampleData
            GROUP BY DAY) t2 
          on t1.day >= t2.day                                                                                                                                
          GROUP BY t1.day, t1.count
          ORDER BY t1.day
          )t_1
       on t.ordr = t_1.ordr + 1 left outer join
         (
          SELECT sum(1) AS ordr,
            t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"
          FROM 
              (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
              FROM sampleData
              GROUP BY DAY) t1
            INNER JOIN 
              (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
              FROM sampleData
              GROUP BY DAY) t2 
            on t1.day >= t2.day                                                                                                                                
            GROUP BY t1.day, t1.count
            ORDER BY t1.day
            ) t_2
        on t.ordr = t_2.ordr + 2)t_0 
    left outer join
         (select t.*,
           (coalesce(t_1.count, 0) - coalesce(t_2.count, 0)) * 100.0 as "percentage increase in count in %"
    from  
    (
      SELECT sum(1) AS ordr,
      t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"

      FROM 
        (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
        FROM sampleData
        GROUP BY DAY) t1
        INNER JOIN 
        (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
        FROM sampleData
        GROUP BY DAY) t2 
        on t1.day >= t2.day                                                                                                                                
        GROUP BY t1.day, t1.count
        ORDER BY t1.day
        )t 
      left outer join
         (
          SELECT sum(1) AS ordr,
            t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"
          FROM 
            (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
            FROM sampleData
            GROUP BY DAY) t1
          INNER JOIN 
            (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
            FROM sampleData
            GROUP BY DAY) t2 
          on t1.day >= t2.day                                                                                                                                
          GROUP BY t1.day, t1.count
          ORDER BY t1.day
          )t_1
       on t.ordr = t_1.ordr + 1 left outer join
         (
          SELECT sum(1) AS ordr,
            t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"
          FROM 
              (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
              FROM sampleData
              GROUP BY DAY) t1
            INNER JOIN 
              (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
              FROM sampleData
              GROUP BY DAY) t2 
            on t1.day >= t2.day                                                                                                                                
            GROUP BY t1.day, t1.count
            ORDER BY t1.day
            ) t_2
        on t.ordr = t_2.ordr + 2) t_3
         on t.ordr = t_3.ordr + 1 
    left outer join
         (select t.*,
           (coalesce(t_1.count, 0) - coalesce(t_2.count, 0)) * 100.0 as "percentage increase in count in %"
    from  
    (
      SELECT sum(1) AS ordr,
      t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"

      FROM 
        (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
        FROM sampleData
        GROUP BY DAY) t1
        INNER JOIN 
        (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
        FROM sampleData
        GROUP BY DAY) t2 
        on t1.day >= t2.day                                                                                                                                
        GROUP BY t1.day, t1.count
        ORDER BY t1.day
        )t 
      left outer join
         (
          SELECT sum(1) AS ordr,
            t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"
          FROM 
            (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
            FROM sampleData
            GROUP BY DAY) t1
          INNER JOIN 
            (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
            FROM sampleData
            GROUP BY DAY) t2 
          on t1.day >= t2.day                                                                                                                                
          GROUP BY t1.day, t1.count
          ORDER BY t1.day
          )t_1
       on t.ordr = t_1.ordr + 1 left outer join
         (
          SELECT sum(1) AS ordr,
            t1.id,t1.day, t1.count, SUM(t2.count) as aggregate, (SUM(t2.count)-t1.count)/(sum(1)-1) as "average_number_of_votes_per_previous_period_days"
          FROM 
              (SELECT  id, date(FROM_UNIXTIME( timecode))  AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
              FROM sampleData
              GROUP BY DAY) t1
            INNER JOIN 
              (SELECT date(FROM_UNIXTIME( timecode) ) AS day,(FROM_UNIXTIME( timecode)) AS original, COUNT(1)  as 'count'
              FROM sampleData
              GROUP BY DAY) t2 
            on t1.day >= t2.day                                                                                                                                
            GROUP BY t1.day, t1.count
            ORDER BY t1.day
            ) t_2
        on t.ordr = t_2.ordr + 2) t_4
        on t_0.ordr = t_4.ordr + 2

Answer 1

I've plugged your query in this fiddle, and I now see the problem. Your query is over 8000 characters long (8423 to be exact), and I'm not showing that message on the result panel. Basically, this is a display bug in SQL Fiddle that I've not noticed before (so, thanks for bringing this to my attention!).

In the mean time, you could try cutting out some of the characters to make it fit within the 8000 character limit.