I am about to deign my first E-Commerce Database.
What i have find out in most E-Commerce websites is that these sites have Category, then SubCategory and then again SubCategory and so on. And the depth of SubCategory is not fixed means One Category have six nested Sub Category while some other have different
Now All the products have attributes associated with it.
Now my question is are these websites keep on adding tables for nested sub categories and keep on adding columns for the attributes in the database
OR
They apply something called as "EAV" model (if i am right) to solve this problem or they keep on adding columns and or tables and also keep on updated the WebPages as on many sites i have found there is now a new category.
(If they use EAV model then the website performance is impacted isnt it..)
Since this is my first ECommerce project please provide some valuable suggestions of yours.
Thanks,
Any help is appreciated.
What you need is a combination of EAV for product features and nested sets for product categories.
While I certainly agree that EAV is almost always a bad choice, one application where EAV is the perfect choice is for handling product attributes in an online catalog.
Think about how websites show product attributes... The attributes of products are always shown as a vertical list with two columns: "Attribute" | "Value". Sometimes these lists show side-by-side comparisons of multiple products. EAV works perfectly for doing this kind of thing. The things that make EAV meaningless and inefficient for most applications are exactly what makes EAV meaningful and efficient for product attributes in an online catalog.
One of the reasons why everyone always says "EAV is EVIL!" is that the attributes in EAV are "meaningless" insofar as the column name (i.e. meaning of the attribute) is table-driven and is therefore not defined by the schema. The whole point of schemas is to give your model meaning so this point is well taken. However in the case of an online product catalog, the meaning of product attributes is really unimportant to the system, itself. The only reason your catalog system cares about product attributes is to dump them in a list or possibly in a product comparison matrix. Therefore EAV is doesn't happen to be evil in this particular case.
For product categories, you want a nested set model, as I described in the answer to this question. Nested sets give you very quick retrieval along with the ability to traverse multiple levels of an unbalanced hierarchy at the expense of some precalculation effort at edit time.
Related
So because I have 4 different product types (books, magazines, gifts, food) I can't just put all products in one "products" table without having a bunch of null values. So I decided to break each product up into their own tables but I know this is just wrong (https://c1.staticflickr.com/1/742/23126857873_438655b10f_b.jpg).
I also tried creating an EAV model for this (https://c2.staticflickr.com/6/5734/23479108770_8ae693053a_b.jpg), but I got stuck as I'm not sure how to link the publishers and authors tables.
I know this question has been asked a lot but I don't understand ANY of the answer's I've seen. I think this is because I'm a very visual learner and this makes it hard to understand what's being talked about when not a lot of information is given.
Your model is on the right track, except that the product name should be sufficient you don't need Gift name, book name etc. What you put in those tables is the information that is specific to the type of product that the other products don't need. The Product table contains all the common fields. I would use productid in the child tables rather than renaming it giftID, magazineID etc. It is easier to remember what things are celled when you are consistent in nameing them.
Now to be practical, you put as much as you can into the product table especially if you are going to do calculations. I prefer the child tables in this specific case to have what is mostly display information. So product contains the product name, the cost, the type of product, the units the product is sold in etc. The stuff that generally is needed to calculate the cost of an order or to have a report of what was ordered. There may be one or two fields that can contain nulls, but it simplifies the calculation type queries so much it might be worth it.
The meat of the descriptive details though would go in the child table for the type of product. These would usually only be referenced when displaying the product in the shopping area and only one at a time, so you can use the product type to let you only join to the one child table you need for display. So while the order cares about the product number and name and cost calculations, it probably doesn't need to go line by line describing the book ISBN number or the megapixels in a camera. But the description page of the product does need those things.
This approach is not purely relational, although it mostly is, but it does group the information by the meanings of the data and how they will be used which will make the database easier to understand and query. I am a big fan of relational tables because database just work better when they hit at least the third normal form but sometimes you can go too far for practicality, so the meaning of the data and the way you are grouping to use the data (and not just for the user interface, but for later reporting as well) is almost always one of my considerations in design.
Breaking each product type into its own table is fine - let the child tables use the same id as the parent Product table, and create views for the child tables that join with Product
Your case is a classic case of types and subtypes. This is often called class/subclass in object modeling and generalization/specialization in ER modeling. It's a well understood pattern. There are known techniques for dealing with this pattern.
Visit the following tabs, and read the description under the info tab (presented as "learn more"). Also look over the questions grouped under these tags.
single-table-inheritance class-table-inheritance shared-primary-key
If you want to rean in more depth use these buzzwords to search for articles on the web.
You've already discovered and discarded single table inheritance on your own. Other answers have pointed you at shared primary key. Class table inheritance involves a single table for generalized data as well as the four specialized tables. Shared primary key is generally used in conjunction with class table inheritance.
I'm trying to refactor some parts of a legacy database schema and am having trouble with coming up with the correct design.
The entities in question are:
samples, papers, studies
papers are associated with many samples
studies are associated with many samples
papers and studies have their own attributes not compatible with each other
samples can be associated with multiple papers and multiple studies
However, this separates out the grouping of papers and studies.
Here's how it looks:
An alternative I thought of was since both papers and studies are just grouping the samples together, I can combine these as one, and have FK from the group into their respective paper/study table.
Here's how it looks:
I'd like to know if the designs look reasonable and if there are any tradeoffs between the two different designs? Also are there alternatives to modelling the relations?
I think the first design is a right one. There are two M:M relations, Paper - Sample and Study - Sample. They are different by domain logic, so there is no sense to combine them in one relation and introduce extra entities for that purpose. First schema is a good normalized one. What is your goal? What problems do you try to resolve?
the schema doesn't have explicit grouping ...
OK, if you do require Group as a separate entity, your design could look like this:
The problem is, Group entity is weak. It is hard to propose any attribute to this entity except for ID. It is not handy to work with this scheme thought. When user edits paper's group, you have to choose, how to handle this situation. Should all other papers\studies 'see' this change too, or you have to create\search edited group and assign it to paper. I think it is wrong way to take if there is no additional business logic related to groups. Usually, when weak entities appear in a design, it means that set of abstractions has been chosen not properly. At the moment, I don't see how to justify Group entity.
I'm in the process of structuring a databasemodel for my new project. For all the entities in my model (which is a cms, and the entities as such f.ex: page, content, menu, template and a bunch of others) they all have in common the same attributes on dates and names.
More specifically each entity contains the following for the dates: IsCreated, IsValidFrom, IsPublished, IsDeleted, IsEdited and IsExpired, and for names: CreatedByNameId, ValidFromByNameId, PublishedByNameId and so on...
I'm going to use EF5 for mapping to objects.
The question is as simple: What is the best way to structure this: Having all the fields in every table (which I am not obliged to...) or to have two separate tables which the other can relate to...?
Thanks in advance /Finn.
First of all - give this a read - http://www.agiledata.org/essays/mappingObjects.html
You really need to think about your queries/access paths. There are many tradeoffs between different implementations.
In reply to your example though,
Given the following setup:
COMMON
ValidFromByNameId
SPECIFIC1
FieldA
SPECIFIC2
FieldB
Querying by the COMMON attributes is easy but you'll have to work some magic when pulling up the subclasses (unless EF5 does it for you)
If the primary questions you're asking are about specific1 and specific2 then perhaps this isn't the right model. having the COMMON table doesn't really buy you much necessary as it will introduce a join to load any Specific1 object. In this case, i'd probably just have duplicate columns.
This answer is intentionally partial as a full answer is better handled by the numerous articles and blogs already out there. Search for "mapping object hierarchies to databases"
I'm trying to design a database for a product aggregator. Each product has information about where it comes from, what it costs, what type of thing it is, price, color, etc. Users need to able to search and filter results based on any of those product categories. I also expect to have a large number of users. My initial thought was having one big table with every product in it with a column for each piece of information and an index on anything I need to be able to search by but I think this might be inefficient with a lot of users pounding on this one table. My other thought was to organize the database to promote a tree-like navigation of tables but because you can search by anything I'm not sure how I would organize the tables.
Any thoughts on some good practices?
One table of products - databases are designed to have lots of users pounding on tables.
(from the comments)
You need to model your data. This comes from looking at the all the data you have, determining what is related to what (a table is called a relation because all the attributes in a row are related to a candidate key). You haven't really given enough information about the scope of what data (unstructured?) you have on these products and how it varies. Are you going to have difficulties because Shoes have brand, model, size and color, but Desks only have brand, model and finish? All this is going to inform your data model. Typically you have one products table, and other things link to it.
Some of those attributes will be foreign keys to lookup tables, others (price) would be simple scalars. Appropriate indexing and you'll be fine. For advanced analytics, consider a dimensionally modeled star-schema, but perhaps not for your live transaction system - depends what your data flow/workflow/transactions are. Or consider some benefits of its principles in your transactional database. Ralph Kimball is source of good information on dimensional modeling.
I dont see any need for the tree structure here. You can do with single table.
if you insist on tree structure with hierarchy here is an example to get you started.
For text based search, and ease of startup & design, I strongly recommend Apache SOLR. The SOLR API is easy to use (especially JSON). Databases do text search poorly, and I would instead recommend that you just make sure that they respond to primary/unique key queries properly, and those are the fields you should index.
One table for the products, and another table for the product category hierarchy (you don't specifically say you have this but "tree-like navigation of tables" makes me think you might).
I can see you might be concerned about over-indexing causing problems if you plan to index almost every column. In that case, it might be best to index on the top 5 or 10 columns you think users are likely to search for, unless it's possible for a user to search on ANY column. In that case you might want to look at building a data warehouse. Maybe you'll want to look into data cubes to see if those will help...?
For hierarchical data, you need a PRODUCT_CATEGORY table looking something like this:
ID
PARENT_ID
NAME
Some sample data:
ID PARENT_ID NAME
1 ROOT
2 1 SOCKS
3 1 HELICOPTER PARTS
4 2 ARGYLE
Some SQL engines (such as Oracle) allow you to write recursive queries to traverse the hierarchy in a single query. In this example, the root of the tree has a PARENT_ID of NULL, but if you don't want this column to be nullable, I've also seen -1 used for the same purposes.
We are working on a mapping application that uses Google Maps API to display points on a map. All points are currently fetched from a MySQL database (holding some 5M + records). Currently all entities are stored in separate tables with attributes representing individual properties.
This presents following problems:
Every time there's a new property we have to make changes in the database, application code and the front-end. This is all fine but some properties have to be added for all entities so that's when it becomes a nightmare to go through 50+ different tables and add new properties.
There's no way to find all entities which share any given property e.g. no way to find all schools/colleges or universities that have a geography dept (without querying schools,uni's and colleges separately).
Removing a property is equally painful.
No standards for defining properties in individual tables. Same property can exist with different name or data type in another table.
No way to link or group points based on their properties (somehow related to point 2).
We are thinking to redesign the whole database but without DBA's help and lack of professional DB design experience we are really struggling.
Another problem we're facing with the new design is that there are lot of shared attributes/properties between entities.
For example:
An entity called "university" has 100+ attributes. Other entities (e.g. hospitals,banks,etc) share quite a few attributes with universities for example atm machines, parking, cafeteria etc etc.
We dont really want to have properties in separate table [and then linking them back to entities w/ foreign keys] as it will require us adding/removing manually. Also generalizing properties will results in groups containing 50+ attributes. Not all records (i.e. entities) require those properties.
So with keeping that in mind here's what we are thinking about the new design:
Have separate tables for each entity containing some basic info e.g. id,name,etc etc.
Have 2 tables attribute type and attribute to store properties information.
Link each entity (or a table if you like) to attribute using a many-to-many relation.
Store addresses in different table called addresses link entities via foreign keys.
We think this will allow us to be more flexible when adding, removing or querying on attributes.
This design, however, will result in increased number of joins when fetching data e.g.to display all "attributes" for a given university we might have a query with 20+ joins to fetch all related attributes in a single row.
We desperately need to know some opinions or possible flaws in this design approach.
Thanks for your time.
In trying to generalize your question without more specific examples, it's hard to truly critique your approach. If you'd like some more in depth analysis, try whipping up an ER diagram.
If your data model is changing so much that you're constantly adding/removing properties and many of these properties overlap, you might be better off using EAV.
Otherwise, if you want to maintain a relational approach but are finding a lot of overlap with properties, you can analyze the entities and look for abstractions that link to them.
Ex) My Db has Puppies, Kittens, and Walruses all with a hasFur and furColor attribute. Remove those attributes from the 3 tables and create a FurryAnimal table that links to each of those 3.
Of course, the simplest answer is to not touch the data model. Instead, create Views on the underlying tables that you can use to address (5), (4) and (2)
1 cannot be an issue. There is one place where your objects are defined. Everything else is generated/derived from that. Just refactor your code until this is the case.
2 is solved by having a metamodel, where you describe which properties are where. This is probably needed for 1 too.
You might want to totally avoid the problem by programming this in Smalltalk with Seaside on a Gemstone object oriented database. Then you can just have objects with collections and don't need so many joins.