I read up on behaviours and thought it might suit my simple requirements but i don't know how to get started in terms of creating a custom behaviour.
Scenario:
I have a master table called Companies. This table has a "hasMany" relationship to detail tables BusinessDescriptions and Addresses. Of course, these detail tables are linked to the Companies table by a foreign key.
Despite the "hasMany" relationship, only one record in these detail tables can be valid on any particular day. Hence in the detail tables for BusinessDescriptions and Addresses, I have fields "Startdate" and "Enddate" which tell you what time period the records are valid for.
Example use: Company X will have a new address from 01.01.2015. Hence when inserting the new address, its old address record which is valid from Startdate 01.01.2014 to Enddate 31.12.9999, needs to have its Enddate changed to 31.12.2014, to make way for the new record that starts from 01.01.2015.
All this "auto-delimitation/adjustment" of start/end dates of existing records, I wish to put into a behaviour, however tutorials on getting a custom behavior up and running are hard to find.
Can anyone point out to me how to start, or maybe show me skeletal structure of creating a behaviour for this?
I don't see a need for a Behavior on this one. Behaviors are for when you need to utilize logic across multiple Models - in this case, it seems you only need it on one model.
You might just use the beforeFind() callback in your Company model. It in, you can append the conditions for the date(s) you want to restrict by.
If you really want to make a behavior, you could put that beforeFind() into one, and utilize it any time you want said model to restrict based on the current date...etc.
On a side note, why not just retrieve the most recent address for that company? Order by the date DESC, and limit 1 ?
Related
I am currently working on setting up a database domain model, where in terms of normalization I will be challenged due to transitive dependency. However, for this particular model it is a choice, that we choose to add such transitive dependency for a reason, and I am wondering how you would go about dealing with such cases in the aspect of normalization?
Let me show what I mean:
I have a table called UserSubscription that have the following attributes:
id {dbgenerated}
created
user
price
currency
subscriptionid
The values for:
price
currency
Depend on the subscriptionid, which points to a second table Subscription (in which the subscriptionid is a FK reference to this tables PK). One might say why, would I even consider including duplicate values from the Subscription table into the UserSubscription table? Well the reason is that the Subscription might change at any point in time, and for reference we want to store the original value of the subscription in the UserSubscription so that even if it changes we still have the values that the user signed up for originally.
I know from the perspective of normalization, that this transitive dependency I create should be fixed, and ideally I would move the values back into the subscription table, and just not allow the values to be modified, and instead create a new subscription whenever it is necessary.
But ideally I do not want to create new subscriptions every time something needs to change in those that exist, simply because it is expected these change often - following say market competition values. At the same time for every new subscription created any user will have more to choose from.
This also means that if we no longer want to use a subscription, we would need to: Remove it, and Create a new one. This can be fixed by simply Updating, since we will no longer need the old one anyways.
The above is a school project, I just wonder whether it would ever be "ok" in terms of normalization to choose such approach, when I choose to do so by choice, and to reduce the tasks associated with removing and creating new subscriptions when I expect these would change frequently.
why don't you instead create a M:N table (mapping table) USER_SUBSCRIPTION where you will have the relationships between USER and SUBSCRIPTION ? You can store all values there historically, and don't have to remove/create anything with the change.. it the user decides to opt-out, you only update the flag_active, flag_deleted, flag_dtime_end, whatever works for you...
Here is a simple model for demonstration:
USER
id_user PK
name
... other details
SUBSCRIPTION
id_subscription PK
name
details
flag_active (TRUE|FALSE or 1|0 values)
... other details
USER_SUBSCRIPTION
id_user FK
id_subscription FK
dtime_start -- when the subscription started
dtime_end -- when the subscription ended
flag_valid (T|F or 1|0) -- optional, will give you a quick headsup about active subscriptions ... but this is sort of redundant, for you can get it from the dtime_start vs dtime_end .. up to you
This will give you a very generic (and therefore flexibile / scalable) model to work with users' subscriptions ... no duplications, all handled by FK/PK referential constraints, ... etc
I am working on a data warehouse solution, and I am trying to build a dimensional model from tables held in a SQL Server database. Some of the tables include but aren't limited to Customer, Customer Payments, Customer Address, etc.
All these tables in the DB have some fields that are repeated multiple times across each table i.e. Record update date, record creatuin date, active flag, closed flag and a few others. These tables all relate to the Customer in some way, but the tables can be updated independently.
I am in the process of building out a dimension(s) on the back of these tables, but I am struggling to see how best to deal with these repeated fields in an elegant way, as they are all used.
I'll appreciate any guidance from people who have experience with scenarios like this, as I ammjust starting out
If more details are needed, I am happy to provide
Thanks
Before you even consider how to include them, ask if those metadata fields even need to be in your dimensional model? If no one will use the Customer Payment Update Date (vs Created Date or Payment Date), don't bring it into your model. If the customer model includes the current address, you won't need the CustomerAddress.Active flag included as well. You don't need every OLTP field in your model.
Make notes about how you talk about the fields in conversation. How do you identify the current customer address? Check the CurrentAddress flag (CustomerAddress.IsActive). When was the Customer's payment? Check the Customer Payment Date (CustomerPayment.PaymentDate or possibly CustomerPayment.CreatedDate). Try to describe them in common language terms. This will provide the best success in making your model discoverable by your users and intuitive to use.
Naming the columns in the model and source as similar as possible will also help with maintenance and troubleshooting.
Also, make sure you delineate the entities properly. A customer payment would likely be in a separate dimension from the customer. The current address may be in customer, but if there is any value to historical address details, it may make sense to put it into its own dimension, with the Active flag as well.
I'm trying to work out a sensible approach for designing a database where I need to store a wide range of continuously changing information about pets. The categories of data can be broken down into, for example, behaviour, illness etc. Data will be submitted on a regular basis relating to these categories, so i need to find a good way to design the db to efficiently accommodate this. A simple approach would just to store multiple records for each pet within each relevant table - e.g the behaviour table would store the behaviour data and would simply have a timestamp for each record along with the identifier for that pet. When querying the db, it would be straightforward to query the one table with the pet id, using the timestamps to output the correct history of submissions. Is there a more sensible way around this or does that make sense?
I would use a combination of lookup tables with a strong use of foreign keys. I think what you are suggesting is very common. For example, get me all the reported illnesses for a particluar pet during this data range would look something like:
Select *
from table_illness
where table_illness.pet_id = <value>
and date between table_illness.start_date and table_illness.finish_date
You could do that for any of the tables. The lookup tables will be a link between, for example, table_illness.illness_type and illness_types.illness_type. The illness_types table is where you would store the details on the types of illnesses.
When designing a database you should build your tables to mimic real-life objects or concepts. So in that sense the design you suggest makes sense. Each pet should have its own record in a pet table which doesn't change. Changing information should then be placed into the appropriate table which has the pet's id. The time stamp method you suggest is probably what I would do -- unless of course this is for a vet or something. Then I'd create an appointment table with the date and connect the illness or behavior to the appointment as well.
(Sorry about the vagueness of the title; I can't think how to really say what I'm looking for without writing a book.)
So in our app, we allow users to change key pieces of data. I'm keeping records of who changed what when in a log schema, but now the problem presents itself: how do I best represent that data in a view for reporting?
An example will help: a customer's data (say, billing address) changed on 4/4/09. Let's say that today, 10/19/09, I want to see all of their 2009 orders, before and after the change. I also want each order to display the billing address that was current as of the date of the order.
So I have 4 tables:
Orders (with order data)
Customers (with current customer data)
CustomerOrders (linking the two)
CustomerChange (which holds the date of the change, who made the change (employee id), what the old billing address was, and what they changed it to)
How do I best structure a view to be used by reporting so that the proper address is returned? Or am I better served by creating a reporting database and denormalizing the data there, which is what the reports group is requesting?
There is no need for a separate DB if this is the only thing you are going to do. You could just create a de-normalized table/cube...and populate and retrieve from it. If your data is voluminous apply proper indexes on this table.
Personally I would design this so you don't need the change table for the report. It is a bad practice to store an order without all the data as of the date of the order stored in a table. You lookup the address from the address table and store it with the order (same for partnumbers and company names and anything that changes over time.) You never get information on an order by joining to customer, address, part numbers, price tables etc.
Audit tables are more for fixing bad changes or looking up who made them than for reporting.
I am currently in the process of looking at a restructure our contact management database and I wanted to hear peoples opinions on solving the problem of a number of contact types having shared attributes.
Basically we have 6 contact types which include Person, Company and Position # Company.
In the current structure all of these have an address however in the address table you must store their type in order to join to the contact.
This consistent requirement to join on contact type gets frustrating after a while.
Today I stumbled across a post discussing "Table Inheritance" (http://www.sqlteam.com/article/implementing-table-inheritance-in-sql-server).
Basically you have a parent table and a number of sub tables (in this case each contact type). From there you enforce integrity so that a sub table must have a master equivalent where it's type is defined.
The way I see it, by this method I would no longer need to store the type in tables like address, as the id is unique across all types.
I just wanted to know if anybody had any feelings on this method, whether it is a good way to go, or perhaps alternatives?
I'm using SQL Server 05 & 08 should that make any difference.
Thanks
Ed
I designed a database just like the link you provided suggests. The case was to store the data for many different technical reports. The number of report types is undefined and will probably grow to about 40 different types.
I created one master report table, that has an autoincrement primary key. That table contains all common information like customer, testsite, equipmentid, date etc.
Then I have one table for each report type that contains the spesific information relating to that report type. That table have the same primary key as the master and references the master as well.
My idea for splitting this into different tables with a 1:1 relation (which normally would be a no-no) was to avoid getting one single table with a huge number of columns, that gets very difficult to maintain as your constantly adding columns.
My design with table inheritance gave me segmented data and expandability without beeing difficult to maintain. The only thing I had to do was to write special a special save method to handle writing to two tables automatically. So far I'm very happy with the design and haven't really found any drawbacks, except for a little more complicated save method.
Google on "gen-spec relational modeling". You'll find a lot of articles discussing exactly this pattern. Some of them focus on table design, while others focus on an object oriented approach.
Table inheritance pops up in a few of them.
I know this won't help much now, but initially it may have been better to have an Entity table rather than 6 different contact types. Then each Entity could have as many addresses as necessary and there would be no need for type in the join.
You'll still have the problem that if you want the sub-type fields and you have only the master contact, you'll have to know what table to go looking at - or else join to all of them. But otherwise this is a workable solution to a common problem.
Another possibility (fairly similar in structure, but different in how you think of it) is to simply put all your contacts into one table. Then for the more specific fields (birthday say for people and department for position#company) create separate tables that are associated with that contact.
Contact Table
--------------
Name
Phone Number
Address Table
-------------
Street / state, etc
ContactId
ContactBirthday Table
--------------
Birthday
ContactId
Departments Table
-----------------
Department
ContactId
It requires a different way of thinking of things though - instead of thinking of people vs. companies, you think of the various functional requirements for the task at hand - if you want to send out birthday cards, get all the contacts that have birthdays associated with them, etc..
I'm going to go out on a limb here and suggest you should rethink your normalization strategy (as you seem to be lucky enough to be able to rethink your schema quite fundamentally). If you typically store an address for each contact, then your contact table should have the address fields in it. Alternatively if the address is stored per company then the address should be stored in the company table and your contacts linked to that company.
If your contacts only have one address, or one (or even 3, just not 'many') instance of the other fields, think about rationalizing them into a single table. In my experience having a few null fields is a far better alternative than needing left joins to data you aren't sure exists.
Fortunately for anyone who vehemently disagrees with me you did ask for opinions! :) IMHO you should only normalize when you really need to. Where you are rethinking schemas, denormalization should be considered at every opportunity.
When you have a 7th type, you'll have to create another table.
I'm going to try this approach. Yes, you have to create new tables when you have a new type, but since this table will probably have different columns, you'll end up doing this anyway if you don't use this scheme.
If the tables that inherit the master don't differentiate much from one another, I'd recommend you try another approach.
May I suggest that we just add a Type table. Ie a person has an address, name etc then the student, teacher as each use case presents its self we have a PersonType table that has an entry from the person table to n types and the subsequent new tables teacher, alien, singer as the system eveolves...