I'm designing my db and am trying to figure out the best way to avoid conditional joins in the future. I've read articles that show the conditional joins and it is definitely something I want to avoid if possible.
I have a CHECK table, and CHECK will store some data (amount, date, etc). I also have 3 'other' tables, VENDOR, VENDOR_DEPT, VENDOR_ACCOUNT of which VENDOR_ACCOUNT has a fk to VENDOR_DEPT, and VENDOR_DEPT has an fk to VENDOR.
My issue is this: how do I design my model so that CHECK can be either assigned to VENDOR, VENDOR_DEPT or VENDOR_ACCOUNT without having vend_id, vendacct_id and venddept_id in my CHECK table or having a VENDOR_CHECK table that has columns check_id ,vendor_level, join_id.... (hopefully you get the picture)
Is there a cleaner way? BTW, I'm using MYSQL but I'd like the solution to work on other platforms as well.
Since I'm at the model design phase, I'm open to all suggestions including redesigning these tables of course :)
You are trying to implement a "one-of" relationship in SQL. This type of relationship can be a bit challenging. I suppose the "relational" way to solve it is to say that you really have a CHECK_ENTITY, and this entity can be one of the three types. That seems unnecessarily cumbersome, however.
One suggestion is to have the three different columns in the table. My guess is that you will often want to be using vend_id for reporting purposes. Simply populate the appropriate ones for a given CHECK.
Yes, your data is then denormalized, because vend_id would be both in the CHECK table and in the VEND_ACCT table. If accounts and departments change, then this captures the relationship at the time of the CHECK, which may be what you want.
An alternative option is to have a dummy account that means "the entire vendor". Then just use this value to mean the entire vendor. Similarly, you would need accounts for each department.
This approach requires some discipline. It is tempting to set up a vendor hierarchy, with any possible depth, with a link back the parent (accounts --> departments --> vendors, so why not generalize it?). SQL is even worse at hierarchical queries than at one-of relationships. By "worse", I mean that the methods for handling such queries are very database-dependent.
Related
We had an MS Access guru at our company who left for another position. Before she left she gave me a quick introduction on how to create queries from a sql server. I am really struggling with this and as I have no one to turn to at our company I was hoping you guys could help.
Hope you can help!
Thanks!
Well, keep in mind that when you build a query, it DOES NOT necessary mean that a enforced relationship exists here. (it might).
Further more, if you imported the tables, then again its doubtful that relations are defined in Access unless you use the relationships window to "enforce" such relationships.
However, when building a query? We will often join on two fields. When you build a query in the query builder, you are free to "make up" any kind of join you want.
Say I was given two different spreadsheets. One had some people, and another had a list of hotels.
Ok, so say we want to generate a list of all people in the same city as the hotels.
You might join between table "People" and say Hotels with city.
however, WHAT happens if there is more then one state with the same City name?
Well, then just join on City AND State!!!
So you get this:
So I not have some related tables here. I just feel like and want to, and need to join the two tables of data.
As such, we never cared or setup or "had" some relationship defined, but all we care about is creating and building a working query.
So, don't confuse the simple act of building some query with that of having setup a corrrect relatonships between tables.
For a working application? Yes, you most certainly will setup relatonships.
So, if you setup relatonships correctly, then you not be able to say add a customer "invoice" reocrd without FIRST having a customer record. You don't have to do this, but it is a very good idea for a working applicaton.
However, when dealing with imported data? You often may not have an pre-defined relationships.
Now, of course in "most" cases, a query that involves multiple tables will in near all cases "follow" what you defined as relationships in the relationships window but it not necessary a requirement at all.
As noted, when building a working application? Then yes, of course you want to setup the relatonships BEFORE you start adding data.
But for general data processing, and creating queries against say different tables of data you are slicing and dicing and working with?
You are free to cook up and draw lines between the tables in the query builder, and as such, often such quires will have zero to do with the relationships you defined, or in fact even when you don't have any relationships defined at all.
That above People and the list of hotels is a great example. I mean, it rather cool that I simple joined on both City and State, and did not have to write one line of data processing code for my desired results
(a list of people in cities that live in the same city as my hotel list).
So don't confuse what we call "referential integrity" and defined relationships. We define these relationships so it becomes impossible for you the developer to add a customer invoice without first having added the customer. And it also means that you, your code, or even a editing the tables directly will not allow this to occur.
However, when dealing with just reporting, or importing data to work on? Well, then often we will not have any relationships defined, but that sure does not stop us from firing up the query builder and drawing join lines between tables.
Between two given Tables you can have one relationship involving two (of more) fields or two (or more) relationships each involving one field. Both cases are possible and have different implications.
The first case, as the first commenter pointed out, is typically used when you have a compound key in the master Table of the relationship.
The second case is typically used when you have two candidate keys in the master table, each of which is used as a master field in each of the two independent relationships.
In Ms-access the case of two independent relationships may be identified because it implies two table-boxes for the same table in the relationships pane.
What is the most performance-efficient way to allow end-users to add custom properties to a core table used by an application.
For example, core table FRIENDS has columns ID, FIRST_NAME, LAST_NAME, and BIRTHDAY.
User 1 wants to also track additional properties FAVORITE_COLOR and LUCKY_NUMBER, but User 2 wants to also track different additional properties ZODIAC_SIGN, MARRIAGE_ANNIVERSRY_DATE, and GOLF_HANDICAP.
I have implemented two approaches for testing:
First approach: Add a new table FRIENDS_CUSTOM_PROPERTIES having an FK pointer back to FRIENDS and two columns for value pairs (KEY and VALUE such as FAVORITE_COLOR, YELLOW). This approach potentially requires many queries on FRIENDS_CUSTOM_PROPERTIES to retrieve all the properties for a given friend.
Second approach: Add extension columns right on the FRIENDS table itself of varying data types for CUSTOM_1, CUSTOM_2, ... CUSTOM_64, etc. If a user needed more custom properties than there were columns, my design would "spill over" to approach 1. This approach is more brute force but easily results in many NULL column values on many rows.
I can make both work but am unsure the best approach to determine which is better (or if there is already a clear best practice one way or another).
Thanks.
Approach number one is called entity-attribute-value as Rick James noted in the comments. It can do the job, but you sacrifice lots of useful features of SQL, like data types and constraints. See EAV FAIL for some of my writing on this.
You wrote something about running "many queries" but there's no advantage to doing that. You should plan on fetching the set of custom properties for a user in one query, and saving it to a map object in your client application.
The latter approach number two is incomplete. You would also need to store some kind of metadata so you know that for user 1, CUSTOM_1 means "Favorite Color" and CUSTOM_2 means "Lucky Number" and so on. Where do you plan to store the meaning of each column per user?
At least with the EAV design, each attribute comes with a key, so you know exactly what it means. And EAV allows for an unlimited number of properties, because each property gets a new row.
Ultimately, any design that allow for "user-defined properties" conflicts with principles of relational databases. Your columns no longer have any concept of a type. Read a book like SQL and Relation Theory to understand more about this.
I'm a software developer. I love to code, but I hate databases... Currently, I'm creating a website on which a user will be allowed to mark an entity as liked (like in FB), tag it and comment.
I get stuck on database tables design for handling this functionality. Solution is trivial, if we can do this only for one type of thing (eg. photos). But I need to enable this for 5 different things (for now, but I also assume that this number can grow, as the whole service grows).
I found some similar questions here, but none of them have a satisfying answer, so I'm asking this question again.
The question is, how to properly, efficiently and elastically design the database, so that it can store comments for different tables, likes for different tables and tags for them. Some design pattern as answer will be best ;)
Detailed description:
I have a table User with some user data, and 3 more tables: Photo with photographs, Articles with articles, Places with places. I want to enable any logged user to:
comment on any of those 3 tables
mark any of them as liked
tag any of them with some tag
I also want to count the number of likes for every element and the number of times that particular tag was used.
1st approach:
a) For tags, I will create a table Tag [TagId, tagName, tagCounter], then I will create many-to-many relationships tables for: Photo_has_tags, Place_has_tag, Article_has_tag.
b) The same counts for comments.
c) I will create a table LikedPhotos [idUser, idPhoto], LikedArticles[idUser, idArticle], LikedPlace [idUser, idPlace]. Number of likes will be calculated by queries (which, I assume is bad). And...
I really don't like this design for the last part, it smells badly for me ;)
2nd approach:
I will create a table ElementType [idType, TypeName == some table name] which will be populated by the administrator (me) with the names of tables that can be liked, commented or tagged. Then I will create tables:
a) LikedElement [idLike, idUser, idElementType, idLikedElement] and the same for Comments and Tags with the proper columns for each. Now, when I want to make a photo liked I will insert:
typeId = SELECT id FROM ElementType WHERE TypeName == 'Photo'
INSERT (user id, typeId, photoId)
and for places:
typeId = SELECT id FROM ElementType WHERE TypeName == 'Place'
INSERT (user id, typeId, placeId)
and so on... I think that the second approach is better, but I also feel like something is missing in this design as well...
At last, I also wonder which the best place to store counter for how many times the element was liked is. I can think of only two ways:
in element (Photo/Article/Place) table
by select count().
I hope that my explanation of the issue is more thorough now.
The most extensible solution is to have just one "base" table (connected to "likes", tags and comments), and "inherit" all other tables from it. Adding a new kind of entity involves just adding a new "inherited" table - it then automatically plugs into the whole like/tag/comment machinery.
Entity-relationship term for this is "category" (see the ERwin Methods Guide, section: "Subtype Relationships"). The category symbol is:
Assuming a user can like multiple entities, a same tag can be used for more than one entity but a comment is entity-specific, your model could look like this:
BTW, there are roughly 3 ways to implement the "ER category":
All types in one table.
All concrete types in separate tables.
All concrete and abstract types in separate tables.
Unless you have very stringent performance requirements, the third approach is probably the best (meaning the physical tables match 1:1 the entities in the diagram above).
Since you "hate" databases, why are you trying to implement one? Instead, solicit help from someone who loves and breathes this stuff.
Otherwise, learn to love your database. A well designed database simplifies programming, engineering the site, and smooths its continuing operation. Even an experienced d/b designer will not have complete and perfect foresight: some schema changes down the road will be needed as usage patterns emerge or requirements change.
If this is a one man project, program the database interface into simple operations using stored procedures: add_user, update_user, add_comment, add_like, upload_photo, list_comments, etc. Do not embed the schema into even one line of code. In this manner, the database schema can be changed without affecting any code: only the stored procedures should know about the schema.
You may have to refactor the schema several times. This is normal. Don't worry about getting it perfect the first time. Just make it functional enough to prototype an initial design. If you have the luxury of time, use it some, and then delete the schema and do it again. It is always better the second time.
This is a general idea
please don´t pay much attention to the field names styling, but more to the relation and structure
This pseudocode will get all the comments of photo with ID 5
SELECT * FROM actions
WHERE actions.id_Stuff = 5
AND actions.typeStuff="photo"
AND actions.typeAction = "comment"
This pseudocode will get all the likes or users who liked photo with ID 5
(you may use count() to just get the amount of likes)
SELECT * FROM actions
WHERE actions.id_Stuff = 5
AND actions.typeStuff="photo"
AND actions.typeAction = "like"
as far as i understand. several tables are required. There is a many to many relation between them.
Table which stores the user data such as name, surname, birth date with a identity field.
Table which stores data types. these types may be photos, shares, links. each type must has a unique table. therefore, there is a relation between their individual tables and this table.
each different data type has its table. for example, status updates, photos, links.
the last table is for many to many relation storing an id, user id, data type and data id.
Look at the access patterns you are going to need. Do any of them seem to made particularly difficult or inefficient my one design choice or the other?
If not favour the one that requires the fewer tables
In this case:
Add Comment: you either pick a particular many/many table or insert into a common table with a known specific identifier for what is being liked, I think client code will be slightly simpler in your second case.
Find comments for item: here it seems using a common table is slightly easier - we just have a single query parameterised by type of entity
Find comments by a person about one kind of thing: simple query in either case
Find all comments by a person about all things: this seems little gnarly either way.
I think your "discriminated" approach, option 2, yields simpler queries in some cases and doesn't seem much worse in the others so I'd go with it.
Consider using table per entity for comments and etc. More tables - better sharding and scaling. It's not a problem to control many similar tables for all frameworks I know.
One day you'll need to optimize reads from such structure. You can easily create agragating tables over base ones and lose a bit on writes.
One big table with dictionary may become uncontrollable one day.
Definitely go with the second approach where you have one table and store the element type for each row, it will give you a lot more flexibility. Basically when something can logically be done with fewer tables it is almost always better to go with fewer tables. One advantage that comes to my mind right now about your particular case, consider you want to delete all liked elements of a certain user, with your first approach you need to issue one query for each element type but with the second approach it can be done with only one query or consider when you want to add a new element type, with the first approach it involves creating a new table for each new type but with the second approach you shouldn't do anything...
I have a site where some pages (we call them gateway pages) are based loosely on certain departments in the organization. Each department has classes associated with it. Unfortunately some of my pages are not associated with a specific department, but do display information about several classes from a department so I can't just query the database strictly on department alone.
Would it be smarter to create a table called gateway_classes with a fk from the gateway table in each class or form a query to somehow filter out exactly what I need from my existing tables using an array of classes to be pulled during the query?
Here's my tables:
departments_classes | classes_vendors | departments | vendors | classes | products | gateway
Any guidance is greatly appreciated.
More Info: There are roughly 350 classes and 18 departments and 12 gateway pages...
Your indexing table idea sounds like it'd work just fine. The only downside to that is that you've got to maintain it separately, and you want to make sure that the data you hold in that table isn't being duplicated in any of your existing tables.
If you don't want to maintain that data differently than you're currently doing so, you can use CF's arrays (or structs) to hold that correlation data (which you'd have to pull from the db in a separate query) and then loop over it as you construct the query that pulls the classes for a given page.
Either way would work okay, it's more a matter of how you prefer to do it, and what you think would be easiest to build, test, and maintain.
One thing about efficiency - make sure you not only link your tables via Foreign Keys (which helps to maintain data integrity), but also put in (nonclustered) indices, which helps the efficiency of the joins and lookups your queries will be doing.
I've seen dramatic speed improvements in my queries (CFQUERYs operating against MS SQL) with the simple act of putting in indices.
In MS SQL, you do so like this:
CREATE NONCLUSTERED INDEX yourIndexName ON yourTableName(yourFieldName)
I hope this helps!
Your problem sounds similar to a common scenario for determining user rights. A User may belong to some Group that has Rights associated with it or the User may be assigned Rights individually. In your case, the User is the Gateway, the Group is the Department, and the Rights are the Classes. A Gateway can then be linked to any number of Departments and/or Classes.
Using this model, you just need to add the gateway_classes table as you describe along with a gateway_departments table.
You could then use UNION to merge the "gateway classes" query with the "gateway departments" query (or perhaps something more elegant) but I think this schema will do want you need without introducing any redundant information.
I have my own theories on the best way to do this, but I think its a common topic and I'd be interested in the different methods people use. Here goes
Whats the best way to deal with many-to-many join tables, particularly as far as naming them goes, what to do when you need to add extra information to the relationship, and what to do whene there are multiple relationships between two tables?
Lets say you have two tables, Users and Events and need to store the attendees. So you create EventAttendees table. Then a requirement comes up to store the organisers. Should you
create an EventOrganisers table, so each new relationship is modelled with a join table
or
rename EventAttendees to UserEventRelationship (or some other name, like User2Event or UserEventMap or UserToEvent), and an IsAttending column and a IsOrganiser column i.e. You have a single table which you store all relationship info between two attendees
or
a bit of both (really?)
or
something else entirely?
Thoughts?
The easy answer to a generic question like this is, as always, "It all depends on the details".
But in general, I try to create fewer tables when this can be done without abusing the data definitions unduly. So in your example, I would probably add an isOrganizer column to the table, or maybe an attendeeType to allow for easy future expansion from audience/organizer to audience/organizer/speaker/caterer or whatever may be needed. Creating an extra table with essentially identical columns, where the table name is in effect a flag identifying the "attendee type", seems to me the wrong way to go both from a pristine design perspective and also from a practical point of view.
A single table is more flexible. With one table and a type field, if we want to know just the organizers -- like when we're sending invitations to a planning meaning -- fine, we write "select userid from userevent where eventid=? and attendeetype='O'". If we want to know everyone who will be there -- like when we're printing name cards for the lunch tables -- we just don't include the attendeetype test.
But suppose we have two tables. Then if we want just the organizers, okay, that's easy, join on the organizer table. But if we want both organizers and audience, then we have to do a union, which makes for more complicated queries and is usually slow. And if you're thinking, What's the big deal doing a union?, note that there may be more to the query. Perhaps a person can have multiple phone numbers and we care about this, so the query is not just joining user and eventAttendee but also phone. Maybe we want to know if they've attended previous conferences because we give special deals to "alumni", so we have to join in eventAttendee a second time, etc etc. A ten-table join with a union can get very messy and confusing to read.