I'm working on a pro开发者_Python百科ject that must store employees' timetables. For example, one employee works Monday through Thursday from 8am to 2pm and from 4pm to 8pm. Another employee may work Tuesday through Saturday from 6am to 3pm.
I'm looking for an algorithm or a method to store these kind of data in a MySQL database. These data will be rarely accessed so it's not important performance questions.
I've thought to store it as a string but I don't know any algorithm to "encode" and "decode" this string.
As many of the comments indicate, it's usually a poor idea to encode all the data into a string that is basically meaningless to the data base. It's usually better to define the data elements and their relations and represent these structures in the data base. The Wikipedia article on data models is a good overview of what's involved (although it's way more general than what you need). The problem you are describing seems simple enough that you could do this with pencil and paper.
One way to start is to write down a lists of logical relationships between concepts in your problem. For instance, the list might look like this (your rules may be different):
- Every employee follows a single schedule.
- Every employee has a first and last name, as well as an employee ID. Different employees may have the same name, but each employee's ID is unique to that employee.
- A schedule has a start and stop day of the week and a start and stop time of day.
- The start and stop time is the same for every day of the schedule.
- Several employees may be on the same schedule.
From this, you can list the nouns used in the rules. These are candidates for entities (columns) in the data base:
- Employee
- Employee ID
- Employee first name
- Employee last name
- Schedule
- Schedule start day
- Schedule start time
- Schedule end day
- Schedule end time
For the rules I listed, schedules seem to exist independently of employees. Since there needs be a way of identifying which schedule an employee follows, it makes sense to add one more entity:
- Schedule ID
If you then look at the verbs in the rules ("follows", "has", etc.), you start to get a handle on the relationships. I would group everything so far into two relationships:
Employees
ID
first_name
last_name
schedule_ID
Schedules
ID
start_day
start_time
end_day
end_time
That seems to be all that's needed by way of data structures. (A reasonable alternative to start_day
and end_day
for the Schedules table would be a boolean field for each day of the week.) The next step is to design the indexes. This is driven by the queries you expect to make. You might expect to look up the following:
- What schedule is employee with ID=xyz following?
- Who is at work on Mondays at noon?
- What days have nobody at work?
Since employees and schedules are uniquely identified by their respective IDs, these should be the primary fields of their respective tables. You also probably want to have consistency rules for the data. (For instance, you don't want an employee on a schedule that isn't defined.) This can be handled by defining a "foreign key" relationship between the Employees.schedule_ID
field and the Schedules.ID
field, which means that Employees.schedule_ID
should be indexed. However, since employees can share the same schedule, it should not be a unique index.
If you need to look up schedules by day of week and time of day, those might also be worth indexing. Finally, if you want to look up employees by name, those fields should perhaps be indexed as well.
Assuming you're using PHP:
Store a timetable in a php array and then use serialize function to transform it in a string;
to get back the array use unserialize.
However this form of memorization is almost never a good idea.
精彩评论