MySQL – Get the Largest Count of Consecutive Values

MySQLmysql-5.7

I have this table that records win and lose. Let us say this is my table

create table test(
  col1 int not null
)Engine=InnoDB;

it has 10 rows :

0,1,1,1,0,1,1,0,0,1

1=Win and 0=Lose. I want to get max count of the consecutive win and lose. For this example, the max count for consecutive win is 3 and for lose is 2. How can I get my desired result? I'm not sure where to start with this one. Thanks in advance.

EDIT

create table t1 (
 colid int not null auto_increment,
 col1 int,

 primary key(colid)
);

insert into t1(col1) values (0);
insert into t1(col1) values (1);
insert into t1(col1) values (1);
insert into t1(col1) values (1);
insert into t1(col1) values (0);
insert into t1(col1) values (1);
insert into t1(col1) values (1);  
insert into t1(col1) values (0);
insert into t1(col1) values (0);
insert into t1(col1) values (1);


select 
a.col1,
max(a.rn)
from (

        select 
        x.col1,
        if (@prev = col1 ,@current := @current + 1,@current := 1 ) rn, @prev := col1
      from t1 x , (select @prev := - 1 , @current := 1) v  
      order by x.colid
      ) a
group by a.col1

this one works the way I see the results.. Is there anything I should consider? I only have knowledge on basic joins. I haven't fully understand the query as of now..

Best Answer

create table t1 (
col1 int 
);

insert into t1 values (0);
insert into t1 values (1);
insert into t1 values (1);
insert into t1 values (1);
insert into t1 values (0);
insert into t1 values (1);
insert into t1 values (1);  
insert into t1 values (0);
insert into t1 values (0);
insert into t1 values (1);

select t.col1,
   max(t.rn)
  from (
select t1.col1,
if (@prev = col1 ,@current := @current + 1,@current := 1 ) rn,
   @prev := col1
 from t1,(select @prev := - 1 ,
              @current := 1) v  
 ) t
 group by t.col1;

DB fiddle

Related Solutions

Mysql – Drop auto increment hack w/o alter table

I tried something similar just now

Here is MySQL for My PC

mysql> select * from information_schema.global_variables where variable_name='datadir' or variable_name like 'versio%';
+-------------------------+------------------------------+
| VARIABLE_NAME           | VARIABLE_VALUE               |
+-------------------------+------------------------------+
| VERSION_COMMENT         | MySQL Community Server (GPL) |
| VERSION                 | 5.5.12-log                   |
| VERSION_COMPILE_MACHINE | x86                          |
| DATADIR                 | C:\MySQL_5.5.12\data\        |
| VERSION_COMPILE_OS      | Win64                        |
+-------------------------+------------------------------+
5 rows in set (0.00 sec)

I will run this using MyISAM

Step 01) create a table called 'rolando'
Step 02) insert 'dominique' and 'diamond'
Step 03) copy the table structure to 'pamela'
Step 04) alter 'pamela' to not have auto_increment
Step 05) In DOS, copy rolando.MYD to pamela.MYD
Step 06) run REPAIR TABLE pamela; (Rebuild pamela.MYI)
Step 07) run SELECT COUNT(1) FROM pamela;
Step 08) run SHOW CREATE TABLE pamela\G
Step 09) run SELECT * FROM pamela;
Step 10) insert 'carlik' into pamela
Step 11) run SELECT * FROM pamela;

Let's see if these steps are kosher.

Here are Steps 1-4

mysql> drop table if exists rolando;
Query OK, 0 rows affected (0.02 sec)

mysql> drop table if exists pamela;
Query OK, 0 rows affected (0.00 sec)

mysql> create table rolando
    -> (
    ->     name varchar(20),
    ->     id int not null auto_increment,
    ->     primary key (id)
    -> ) ENGINE=MyISAM;
Query OK, 0 rows affected (0.05 sec)

mysql> insert into rolando (name) values ('dominique'),('diamond');
Query OK, 2 rows affected (0.00 sec)
Records: 2  Duplicates: 0  Warnings: 0

mysql> select * from rolando;
+-----------+----+
| name      | id |
+-----------+----+
| dominique |  1 |
| diamond   |  2 |
+-----------+----+
2 rows in set (0.00 sec)

mysql> create table pamela like rolando;
Query OK, 0 rows affected (0.05 sec)

mysql> show create table rolando\G
*************************** 1. row ***************************
       Table: rolando
Create Table: CREATE TABLE `rolando` (
  `name` varchar(20) DEFAULT NULL,
  `id` int(11) NOT NULL AUTO_INCREMENT,
  PRIMARY KEY (`id`)
) ENGINE=MyISAM AUTO_INCREMENT=3 DEFAULT CHARSET=latin1
1 row in set (0.00 sec)

mysql> show create table pamela\G
*************************** 1. row ***************************
       Table: pamela
Create Table: CREATE TABLE `pamela` (
  `name` varchar(20) DEFAULT NULL,
  `id` int(11) NOT NULL AUTO_INCREMENT,
  PRIMARY KEY (`id`)
) ENGINE=MyISAM DEFAULT CHARSET=latin1
1 row in set (0.02 sec)

mysql> alter table pamela modify id int(11) unsigned not null;
Query OK, 0 rows affected (0.11 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> show create table pamela\G
*************************** 1. row ***************************
       Table: pamela
Create Table: CREATE TABLE `pamela` (
  `name` varchar(20) DEFAULT NULL,
  `id` int(11) unsigned NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=MyISAM DEFAULT CHARSET=latin1
1 row in set (0.00 sec)

mysql> select count(1) from pamela;
+----------+
| count(1) |
+----------+
|        0 |
+----------+
1 row in set (0.01 sec)

mysql>

Here is Step 6

C:\>copy C:\MySQL_5.5.12\data\test\rolando.MYD C:\MySQL_5.5.12\data\test\pamela.MYD
        1 file(s) copied.

C:\>

Here are the rest of the Steps starting at Step 7

mysql> repair table pamela;
+-------------+--------+----------+------------------------------------+
| Table       | Op     | Msg_type | Msg_text                           |
+-------------+--------+----------+------------------------------------+
| test.pamela | repair | warning  | Number of rows changed from 0 to 2 |
| test.pamela | repair | status   | OK                                 |
+-------------+--------+----------+------------------------------------+
2 rows in set (0.03 sec)

mysql> select count(1) from pamela;
+----------+
| count(1) |
+----------+
|        2 |
+----------+
1 row in set (0.00 sec)

mysql> insert into pamela (name,id) values ('carlik',3);
Query OK, 1 row affected (0.00 sec)

mysql> select * from pamela;
+-----------+----+
| name      | id |
+-----------+----+
| dominique |  1 |
| diamond   |  2 |
| carlik    |  3 |
+-----------+----+
3 rows in set (0.00 sec)

mysql>

Dangerous game, isn't it ???

Guess what? Stuff like this is actually published in "High Performance MySQL : Optimization, Backups, Replication, and more", Pages 146-148 under the Subheading Speeding Up ALTER TABLE. Page 147 Paragraph 1 says:

The technique we are about to demonstrate is unsupported, undocumented, and may not work. Use it at your risk. We advise you to back up you data first!

I also had an earlier post when someone ask a similar question : Can I rename the values in a MySQL ENUM column in one query?

You got guts, @atxdba !!!

Mysql – Count consecutive null rows from a joined table

This is essentially a gaps-and-islands problem. And when I have my SQL Server hat on, I often solve this kind of problem with two ROW_NUMBER() calls. Sadly, MySQL, unlike many other major SQL products, does not support ROW_NUMBER(), nor any other ranking function. To make up for that, however, you can use variable assignment in SELECTs, which MySQL does support (unlike many other major SQL products).

Below is a solution followed by an explanation:

SELECT
  member_id,
  member_name,
  event_id,
  COUNT(*) AS consecutive_times_missed,
  MIN(event_date) AS first_date_missed,
  MAX(event_date) AS last_date_missed
FROM (
  SELECT
    member_id,
    member_name,
    event_id,
    event_date,
    is_missed,
    @occ_ranking := (event_id = @last_event) * (member_id = @last_member) * @occ_ranking + 1,
    @att_ranking := (event_id = @last_event) * (member_id = @last_member)
                                             * (is_missed = @last_missed) * @att_ranking + 1,
    @occ_ranking - @att_ranking AS grp,
    @last_member := member_id,
    @last_event  := event_id,
    @last_missed := is_missed
  FROM (
    SELECT
      m.member_id,
      m.member_name,
      e.event_id,
      e.event_date,
      (a.attendance_date IS NULL) AS is_missed
    FROM       members     m
    INNER JOIN event_dates e ON m.member_join_date <= e.event_date
    LEFT  JOIN attendance  a ON m.member_id = a.member_id
                            AND e.event_id = a.event_id
                            AND e.event_date = a.attendance_date,
    (
      SELECT
        @occ_ranking := 0,
        @att_ranking := 0,
        @last_member := 0,
        @last_event  := 0,
        @last_missed := 0
    ) v
    ORDER BY
      m.member_id,
      e.event_date
  ) s
) s
WHERE
  is_missed = 1
GROUP BY
  member_id,
  member_name,
  event_id,
  grp
HAVING
  COUNT(*) >= 3
;

Basically, you start with joining members and event_dates to get all the event occurrences the members could have attended based on their membership dates. Then you throw in the attendance table (via a left join) to flag the missed occurrences. Here's an example of what you get by this time:

member_id  event_id  event_date  is_missed
---------  --------  ----------  ---------
1          1         2012-07-10  0
2          1         2012-07-10  1
1          1         2012-07-14  0
2          1         2012-07-14  1
…          …         …           …

At this point, the resulting set needs to be sorted by member_id, event_id, because that is crucial to the subsequent rankings calculation.

Two different rankings are produced for every row. One is a ranking within the row's partition of (member_id, event_id) (it is reset as soon as a new event or a new member is encountered). The other is a ranking within the specific group of consecutive event occurrences, either attended or missed, that the row belongs to (this ranking, in addition to being reset upon coming across a new member or event, also gets reset whenever the other group is encountered). And so you get something like this:

member_id  event_id  event_date  is_missed  ranking1  ranking2
---------  --------  ----------  ---------  --------  --------
…          …         …           …          …         …
1          1         2012-07-27  0          4         4
1          1         2012-07-28  0          5         5
1          1         2012-07-29  1          6         1
2          1         2012-07-10  1          1         1
2          1         2012-07-14  1          2         2
2          1         2012-07-25  1          3         3
2          1         2012-07-27  0          4         1
…          …         …           …          …         …

As you may have noticed, the difference between the two ranking numbers is constant throughout the particular group of consecutive event occurrences of the same kind ("attended" or "missed") and is also unique for that group within its partition. Therefore, every such group can be identified by member_id, event_id and the just mentioned difference.

And it now remains simply to filter the events leaving just the missed ones, group the rows and get the necessary aggregated data, like the number of rows and, possibly, as in the query above, the dates of the first and the last event occurrence in the group. The number of rows is also used in an additional filter condition to omit groups with fewer rows than required.

Best Answer

Related Solutions

Mysql – Drop auto increment hack w/o alter table

Mysql – Count consecutive null rows from a joined table

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