MySQL用户保留和日常

Question

I'm trying to figure out how to write my SQL query to get users day to day and retention. consider having the following row table round_statistics on each play round i have date of the round, now i would like to: 1. know how many users play two days in a row meaning played on Sunday and Monday, Monday and Tuesday, but Sunday and Tuesday doesn't count as two days in a row. 2. users retention 1-7

retention 7 is : % of users that have the chance to play the last 7 days (meaning they are registered at least 7 days) and had some activity (record) after 7 days.

retention 6-1 are the same only for 6-1 days.

Please help me to find out my game retention :) you will get a free coins to play it.... Thanks.

The table structure is: user_id,round_time

for example if i played 3 times today:

user id | round_time
1000,   | '2013-08-10 14:02:53' 
1000,   | '2013-08-10 14:03:25' 
1000,   | '2013-08-10 14:04:47'

the result structure is:

date        |  2013-08-10 |   2013-07-10 
day to day  |  10         |   100         
retention 7 |  15         |   125         
retention 6 |  20         |   210         
retention 5 |  30         |   320         
retention 4 |  40         |   430         
retention 3 |  50         |   540         
retention 2 |  60         |   650         
retention 1 |  120        |   1620   

Answer 1

My sql don't has analytic functions , neither CTE and pivot table features, for this reasons it is not direct to do your required query (and nobody answer your question).

For this data:

create table t ( uid int, rt date);
insert into t values 
(99,    '2013-08-7 14:02:53' ),     <- gap
(99,    '2013-08-9 14:02:53' ),     <-
(99,    '2013-08-10 14:03:25' ),
(1000,    '2013-08-7 14:02:53' ),
(1000,    '2013-08-8 14:03:25' ),
(1000,    '2013-08-9 14:03:25' ),
(1000,   '2013-08-10 14:04:47');

This is an approach before pivot retentions, for a given date ( '2013-08-10 00:00:00' , '%Y-%m-%d') :

select count( distinct uid ) as n, d, dt from
(
  select uid,
         '2013-08-10 00:00:00' as d,
         G.dt      
  from 
    t
  inner join
    ( select 7 as dt union all 
      select 6 union all select 5 union all
      select 4 union all select 3 union all
      select 2 union all select 1 union all select 0) G
  on DATE_FORMAT( t.rt, '%Y-%m-%d') between
        DATE_FORMAT( date_add( '2013-08-10 00:00:00', Interval -1 * G.dt DAY) , 
                    '%Y-%m-%d')
     and
        DATE_FORMAT(  '2013-08-10 00:00:00' , '%Y-%m-%d')
  where DATE_FORMAT(rt , '%Y-%m-%d') <= DATE_FORMAT(  '2013-08-10 00:00:00' , 
                                                      '%Y-%m-%d')
  group by uid, G.dt
  having  count( distinct DATE_FORMAT( T.rt, '%Y-%m-%d') )  = G.dt + 1
) TT
group by dt

Your pre-cooked data ( DT = 0 means today visits, DT = 1 means 2 consecutive days, ...):

| N |                   D | DT |
--------------------------------
| 2 | 2013-08-10 00:00:00 |  0 |
| 2 | 2013-08-10 00:00:00 |  1 |
| 1 | 2013-08-10 00:00:00 |  2 |
| 1 | 2013-08-10 00:00:00 |  3 |

Here it is ( for same data ):

select count( distinct uid ) as n, d, dt from
(
  select uid,
         z.zt as d,
         G.dt      
  from 
    t
  cross join
     ( select distinct DATE_FORMAT( t.rt, '%Y-%m-%d') as zt from t) z
  inner join
    ( select 7 as dt union all 
      select 6 union all select 5 union all
      select 4 union all select 3 union all
      select 2 union all select 1 union all select 0) G
  on DATE_FORMAT( t.rt, '%Y-%m-%d') between
        DATE_FORMAT( date_add( z.zt, Interval -1 * G.dt DAY) , 
                    '%Y-%m-%d')
     and
        z.zt
  where z.zt <= z.zt
  group by uid, G.dt, z.zt
  having  count( distinct DATE_FORMAT( T.rt, '%Y-%m-%d') )  = G.dt + 1
) TT
group by d,dt
order by d,dt

Results at sqlfiddle: http://sqlfiddle.com/#!2/c26ec/10/0

| N |          D | DT | GROUP_CONCAT( UID) |
--------------------------------------------
| 2 | 2013-08-07 |  0 |            1000,99 |
| 1 | 2013-08-08 |  0 |               1000 |
| 1 | 2013-08-08 |  1 |               1000 |
| 2 | 2013-08-09 |  0 |            1000,99 |
| 1 | 2013-08-09 |  1 |               1000 |
| 1 | 2013-08-09 |  2 |               1000 |
| 2 | 2013-08-10 |  0 |            1000,99 |
| 2 | 2013-08-10 |  1 |            99,1000 |
| 1 | 2013-08-10 |  2 |               1000 |
| 1 | 2013-08-10 |  3 |               1000 |