I'm making a fitness logbook where indoor rowers can log there results.
To make it interesting and motivating I'm implementing an achievement system.
I like to have an achievement that if someone rows more than 90 times within 24 weeks they get that achievement.
Does anybody have some hints in how i can implement this in MYSQL.
The mysql-table for the logbook is pretty straightforward: id, userid, date (timestamp),etc (rest is omitted because it doesn't really matter)
The jist is that the first rowdate and the last one can't exceed the 24 weeks.
I assume from your application that you want the most recent 24 weeks.
In mysql, you do this as:
select lb.userid
from logbook lb
where datediff(now(), lb.date) >= 7*24
group by userid
having count(*) >= 90
If you need it for an arbitrary 24-week period, can you modify the question?
Just do a sql query to count the number of rows a user has between now and 24 weeks ago. This is a pretty straight forward query to run.
Look at using something with datediff in mysql to get the difference between now and 24 weeks ago.
After you have a script set up to do this, set up a cron job to run either every day or every week and do some automation on this.
I think you should create a table achievers which you populate with the achievers of each day.
You can set a recurrent(daily, right before midnight) event in which you run a query like this:
delete from achievers;
insert into achievers (
select userid
from logbook
where date < currenttimestamp and date > currenttimestamp - 24weeks
group by userid
having count(*) >= 90
)
For events in mysql: http://dev.mysql.com/doc/refman/5.1/en/events-overview.html
This query will give you the list of users total activity in 24 weeks
select * from table groupby userid where `date` BETWEEN DATE_SUB( CURDATE( ) ,INTERVAL 168 DAY ) AND CURDATE( ) having count(id) >= 90
Related
I've just started a job and my boss wants me to learn mySQL so please bear with me, i've been learning for only 2 days and i'm not that good at it yet.
So i've been given 3 tables and several tasks to do.
The tables are:
mobile_log_messages_sms
mobile_providers
service_instances
And in them i've got to:
Find out how many messages there were in the last 25 days and how
much income did they make
Then i need to group them by day (so per day, exclude hours) and
provider name.
Also i need to ignore all the messages that have an empty string
under the service column
Also i need to ignore the messages that made 0 income and count only
those that have the column service_enabled = 1
And then i need to sort it descending, by date.
in the tables
mobile_log_messages_sms:
message_id - used to count the messages
price - using for price obviously, exlude those with 0
time - date in yyyy/mm/dd hh:mm:ss format
service - exclude all those that have an empty string (or null)
mobile_providers
provider_name - to use to group with
service_instances
enabled - only use if value is 1
I've started with:
SELECT message_id, price, time
FROM mobile_log_messages_sms
WHERE time BETWEEN '2017-02-26 00:00:00'
AND time AND '2017-03-22 00:00:00'
But i need to change the date format and then use the JOIN commands but i don't know how, and i know i need to add more to it, but i'm stumped even at the start. Also the starting just lists the messages but i need to count the total sum of the income (price) per day.
Can anyone point me in the right direction at least since i'm still a noob? Many thanks in advance and sorry if i worded something badly, english is not my first language.
Find out how many messages there were in the last 25 days and how much income did they make
1.
SELECT COUNT(message_id), SUM(price)
FROM mobile_log_messages_sms
WHERE CAST(time AS DATE) BETWEEN DATE_SUB(CURRENT_DATE,INTERVAL 25 DAY)
AND CURRENT_DATE;
2.
SELECT COUNT(message_id), SUM(price)
FROM mobile_log_messages_sms
WHERE CAST(time AS DATE) BETWEEN DATE_SUB(CURRENT_DATE,INTERVAL 25 DAY)
AND CURRENT_DATE
GROUP BY CAST(time AS DATE);
3.
SELECT COUNT(message_id), SUM(price)
FROM mobile_log_messages_sms
WHERE CAST(time AS DATE) BETWEEN DATE_SUB(CURRENT_DATE,INTERVAL 25 DAY)
AND CURRENT_DATE AND service IS NULL
GROUP BY CAST(time AS DATE);
rest can't done with join so make sure that at least one column should be common in tables.
I had a sql query I would run that would get a rolling sum (or moving window) data set. I would run this query for every 7 days, increase the interval number by 7 (28 in example below) until I reached the start of the data. It would give me the data split by week so I can loop through it on the view to create a weekly graph.
SELECT *
FROM `table`
WHERE `row_date` >= DATE_SUB(NOW(), INTERVAL 28 DAY)
AND `row_date` <= DATE_SUB(NOW(), INTERVAL 28 DAY)
This is of course very slow once you have several weeks worth of data. I wanted to replace it with a single query. I came up with this.
SELECT *
CONCAT(YEAR(row_date), '/', WEEK(row_date)) as week_date
FROM `table`
GROUP BY week_date
ORDER BY row_date DESC
It appeared mostly accurate, except I noticed the current week and the last week of 2015 was much lower than usual. That's because this query gets a week starting on Sunday (or Monday?) meaning that it resets weekly.
Here's a data set of employees that you can use to demonstrate the behavior.
CREATE TABLE employees (
id INT NOT NULL,
first_name VARCHAR(14) NOT NULL,
last_name VARCHAR(16) NOT NULL,
row_date DATE NOT NULL,
PRIMARY KEY (id)
);
INSERT INTO `employees` VALUES
(1,'Bezalel','Simmel','2016-12-25'),
(2,'Bezalel','Simmel','2016-12-31'),
(3,'Bezalel','Simmel','2017-01-01'),
(4,'Bezalel','Simmel','2017-01-05')
This data will return the last 3 rows on the same data point on the old query (last 7 days) assuming you run it today 2017-01-06, but only the last 2 rows on the same data point on the new query (Sunday to Saturday).
For more information on what I mean by rolling or moving window, see this English stack exchange link.
https://english.stackexchange.com/questions/362791/word-for-graph-that-counts-backwards-vs-graph-that-counts-forwards
How can I write a query in MySQL that will bring me rolling data, where the last data point is the last 7 days of data, the previous point is the previous 7 days, and so on?
I've had to interpret your question a lot so this answer might be unsuitable. It sounds like you are trying to get a graph showing data historically grouped into 7-day periods. Your current attempt does this by grouping on calendar week instead of by 7-day period leading to inconsistent size of periods.
So using a modification of your dataset on sql fiddle ( http://sqlfiddle.com/#!9/90f1f2 ) I have come up with this
SELECT
-- Figure out how many periods of 7 days ago this record applies to
FLOOR( DATEDIFF( CURRENT_DATE , row_date ) / 7 ) AS weeks_ago,
-- Count the number of ids in this group
COUNT( DISTINCT id ) AS number_in_week,
-- Because this is grouped, make sure to have some consistency on what we select instead of leaving it to chance
MIN( row_date ) AS min_date_in_week_in_dataset
FROM `sample_data`
-- Groups by weeks ago because that's what you are interested in
GROUP BY weeks_ago
ORDER BY
min_date_in_week_in_dataset DESC;
I have a huge table in MySql (more than 80 million tuples) for 30 days, on which I want to run group by query. I've already given the index to the column where I want to run group by
I would like to know whether processing each day (total 30) will be faster or processing just once for all the 30 days.
I'm using Python script for playing with the DB
EDIT :
This the the query for 1 day (run 30 times, each time with next date):
q1 = Select date(time) Date,count(user_name) from users group by Date where date(time) = '2014-03-02';
and this is for all the 30 days (run just once):
q2 = Select date(time) Date, count(user_name) from users group by Date
So, it all boils down to:
Whether q1 is more efficient (run 30 times) or q2 (run once)
Obviously each day will be faster..
One day data is less than whole data and needs less space to perform group by operation on less data as group by is perform after fetching the one day data..
Thanks
first of all sorry for that title, but I have no idea how to describe it:
I'm saving sessions in my table and I would like to get the count of sessions per hour to know how many sessions were active over the day. The sessions are specified by two timestamps: start and end.
Hopefully you can help me.
Here we go:
http://sqlfiddle.com/#!2/bfb62/2/0
While I'm still not sure how you'd like to compare the start and end dates, looks like using COUNT, YEAR, MONTH, DAY, and HOUR, you could come up with your desired results.
Possibly something similar to this:
SELECT COUNT(ID), YEAR(Start), HOUR(Start), DAY(Start), MONTH(Start)
FROM Sessions
GROUP BY YEAR(Start), HOUR(Start), DAY(Start), MONTH(Start)
And the SQL Fiddle.
What you want to do is rather hard in MySQL. You can, however, get an approximation without too much difficulty. The following counts up users who start and stop within one day:
select date(start), hour,
sum(case when hours.hour between hour(start) and hours.hour then 1 else 0
end) as GoodEstimate
from sessions s cross join
(select 0 as hour union all
select 1 union all
. . .
select 23
) hours
group by date(start), hour
When a user spans multiple days, the query is harder. Here is one approach, that assumes that there exists a user who starts during every hour:
select thehour, count(*)
from (select distinct date(start), hour(start),
(cast(date(start) as datetime) + interval hour(start) hour as thehour
from sessions
) dh left outer join
sessions s
on s.start <= thehour + interval 1 hour and
s.end >= thehour
group by thehour
Note: these are untested so might have syntax errors.
OK, this is another problem where the index table comes to the rescue.
An index table is something that everyone should have in their toolkit, preferably in the master database. It is a table with a single id int primary key indexed column containing sequential numbers from 0 to n where n is a number big enough to do what you need, 100,000 is good, 1,000,000 is better. You only need to create this table once but once you do you will find it has all kinds of applications.
For your problem you need to consider each hour and, if I understand your problem you need to count every session that started before the end of the hour and hasn't ended before that hour starts.
Here is the SQL fiddle for the solution.
What it does is use a known sequential number from the indextable (only 0 to 100 for this fiddle - just over 4 days - you can see why you need a big n) to link with your data at the top and bottom of the hour.
I have a table that is getting hundreds of requests per minute. The issue that I'm having is that I need a way to select only the rows that have been inserted in the past 5 minutes. I am trying this:
SELECT count(id) as count, field1, field2
FROM table
WHERE timestamp > DATE_SUB(NOW(), INTERVAL 5 MINUTE)
ORDER BY timestamp DESC
My issue is that it returns 70k+ results and counting. I am not sure what it is that I am doing wrong, but I would love to get some help on this. In addition, if there were a way to group them by minute to have it look like:
| count | field1 | field2 |
----------------------------
I'd love the help and direction on this, so please let me know your thoughts.
You don't really need DATE_ADD/DATE_SUB, date arithmetic is much simpler:
SELECT COUNT(id), DATE_FORMAT(`timestamp`, '%Y-%m-%d %H:%i')
FROM `table`
WHERE `timestamp` >= CURRENT_TIMESTAMP - INTERVAL 5 MINUTE
GROUP BY 2
ORDER BY 2
The following seems like it would work which is mighty close to what you had:
SELECT
MINUTE(date_field) as `minute`,
count(id) as count
FROM table
WHERE date_field > date_sub(now(), interval 5 minute)
GROUP BY MINUTE(date_field)
ORDER BY MINUTE(date_field);
Note the added column to show the minute and the GROUP BY clause that gathers up the results into the corresponding minute. Imagine that you had 5 little buckets labeled with the last 5 minutes. Now imagine you tossed each row that was 4 minutes old into it's own bucket. count() will then count the number of entries found in each bucket. That's a quick visualization on how GROUP BY works. http://www.tizag.com/mysqlTutorial/mysqlgroupby.php seems to be a decent writeup on GROUP BY if you need more info.
If you run that and the number of entries in each minute seems too high, you'll want to do some troubleshooting. Try replacing COUNT(id) with MAX(date_field) and MIN(date_field) so you can get an idea what kind of dates it is capturing. If MIN() and MAX() are inside the range, you may have more data written to your database than you realize.
You might also double check that you don't have dates in the future as they would all be > now(). The MIN()/MAX() checks mentioned above should identify that too if it's a problem.