I am working on creating an application with multiple parent accounts each of which has different multiple users. Each account consists of a set of data of similar type but needs t be maintained separately. eg. inventory of each organization which their respective users can view.
What is the best practice:
1: Create different database tables for each organization
2: Create a common table and have an extra column for the organization it belongs to.
As mentioned, do a one table for organization, one for equipment, one for persons and so on. It is step 1 - separate table for separate entity.
After that connect them with relationships: primary key in main entity to foreign key in sub entity. Other words every row in equipment table would have column with id of organization it belongs to. And so on.
There are many other circumstances, including subdividing entities to such called normal forms, you can study it if it needed, to reduce data consistency supply costs. But it could also negatively affect performance.
Anyway: same class entities commonly should be stored in one table.
The best practice in OLTP (transaction processing) is to create a common table and to implement a subtyping in some way, for example "have extra tables with columns for the organization subtype". In OLAP (analytical processing) warehousing it is still a good practice but the mapping of subtypes can be implemented differently. In OLAP datamarts the solution "one table per organization" can be a good practice.
You may have a look on the book "Programming with databases" which covers these topics: subtype/subclass mapping, OLTP vs OLAP, denormalization etc.
Related
I'm finding the best way to convert an eer diagram to the corresponding relational diagram. I have a generalization entity with some specializations which have separate relationships with other entities. The generalization entity has in turn a n-to-m relationsip with an entity. The following drawing clarifies the situation:
Eer diagram with specialization and n-to-m relationship.
As the two specialized entities have separate relationships, I should convert them to two separate tables. Meanwhile, I should create a table modeling the n-to-m relationship which relates the entity 'User' to the entity 'Newsletter' (or better, its specializations). How to cope with this problem? I've not found any useful information.
The only possible solution I thought to was to create two separate tables modeling the n-to-m relationship, one linked to 'User' and 'Programming newsletter' tables, one linked to 'User' and 'Travel newsletter' tables. But I'm looking for opinions for that.
I see no problem. I would implement your diagram using the following tables:
User (nickname PK, name, address)
Newsletter (name PK, supervisor, type)
Subscription (user_nickname PK/FK, newsletter_name PK/FK)
Programming_Newsletter (newsletter_name PK/FK, type FK, language)
Travel_Newsletter (newsletter_name PK/FK, type FK, means_of_transport)
I probably wouldn't use user nicknames / newsletter names as keys since I prefer stable compact identifiers, but that's another topic.
I think there are a couple of ways to go about this.
The simplest one, would be to break the assumption "As the two specialized entities have separate relationships, I should convert them to two separate tables". If you keep your specialisations together in a single table, you can use STI (Single table inheritance) for your generalisation. This approach has a drawback though, which is that your table will have many NULL values for those relationships that do not belong to the concrete specialisation.
The other approach, would be to use CTI (Class Table Inheritance). This approach assumes that there will be a specific table for each specialisation of your generalisation. This would get around the NULL problems, but it can potentially introduce a performance problem due to the fact that your code will need to eagerly join from the generalisation table to the specialisation on almost every single query you make to retrieve them.
I don't quite see the issue in the n-to-m relationship between User and Newsletter. You should be able to have a regular intermediate table that creates the association between the two, since there are no further attributes that complement that relationship.
I am designing a product that is mainly to be used by small organizations. The idea is for every member of the organization to have their own accounts (known as subaccounts). At the same time, there needs to be data that can be accessed by anyone with that organization. I am trying to decide between two courses of action.
Separate Table for Organizations
In this design, there would be a organizations table and a users table. The users would be connected to organizations via foreign key, and the shared data would use the foreign id of the organization.
User Conglomerate
Here an additional field in the users table would point to another row in the table (the parent) that represents the primary account for the organization and is linked to all the shared data.
Which approach would be superior in this situation?
Both approaches seem reasonable and workable, but I would lean towards having a separate table for organizations as ultimately the idea of an 'organization' is different to that of an 'user'. You may need to have different attributes for an organization than you would a user (e.g. you may need to have more than one 'superuser' for an organization at some stage), and so having this data in a separate table would make it (a) easier to code against (b) more extensible and future-proof (c) more efficient and normalized in storage.
I was studying about relationships in RDBMS.I have understood the basic concept behind mapping relation ship,but I am not able to spot them.
The three possibilities :
one to many(Most common) requires a PK - FK relationsip.Two tables involved
many to many(less common) requires a junction table.Three tables Involved
one to one(very rare). One table involved.
When I begin a project,I am not able to separate the first two conditions and I am not clear in my head.
Examples when I study help for a brief moment,but not when I need to put these principles in to practice.
This is the place where most begineers falter.
How can I spot these relationships.Is there a simpler way?
Don't look at relationships from a technical perspective. Use analogies and real-life examples when trying to envision relationships in your head.
For example, let's say we have a library database.
A library must have books.
M:M
Each Book may have been written by multiple Authors and each Author may have written multiple Books. Thus it is a many-to-many relationship which will reflect into 3 tables in the database.
1:M
Each Book must also have a Publisher, but a Book may only have one Publisher and a Publisher can publish many Books. Thus it is a one-to-many relationship and it reflects with the PublisherId being referenced in the Books table.
A simple analogy like this one explains relationships to their core. When you try to look at them through a technical lens you're only making it harder on yourself. What's actually difficult is applying real world data scenarios when constructing your database.
I think the reason you are not getting the answers that you need is because of the way you are framing the question. Instead of asking “How do I spot the correct type of relationship between entities”, think about “How do my functional needs dictate what relationship to implement”. Database design doesn’t drive the function; it’s the functional needs that drive the relationships you need to implement.
When designing a database structure, you need to identify all the entities. Entities are all the facts that you want to store: lists of things like book titles, invoices, countries, dog species, etc. Then to identify your relationships, you have to consider the types of questions you will want to ask your database. It takes a bit of forward thinking sometimes… just because nobody is asking the question now doesn’t mean that it might not ever be asked. So you can’t ask the universe “what is the relationship between these lists of facts?” because there is no definitive answer. You define the universe… I only want to know answers to these types of questions; therefore I need to use this type of relationship.
Let’s examine an example relation between two common entities: a table of customers and a table of store locations. There is no “correct” way to relate these entities without first defining what you need to know about them. Let’s say you work for a retailer and you want to give a customer a default store designation so they can see products on the website that their local store has in stock. This only requires a one-to-many relationship between a store and the customer. Designing the relationship this way ensures that one store can have many customers as their default and each customer can only have one default store. To implement this relationship is as easy as adding a DefaultStore field to your Customer table as a foreign key that links to the primary key of the Store table.
The same two entities above might have alternate requirements for the relationship definition in a different context. Let’s say that I need to be able to give the customer the opportunity to select a list of favorite stores so that they can query about in stock information about all of them at once. This requires a many-to-many relationship because you want one customer to be able to relate to many stores and each store can also relate to many customers. To implement a many-to-many relationship requires a little more overhead because you will have to create a separate table to define the relationship links, but you get this additional functionality. You might call your relationship table something like CustomerStoreFavorites and would have as its primary key as the combined primary keys from each of the entities: (CustomerID, StoreID). You could also add attributes to the relationship, like possibly a LastOrderDate field to specify the last date that the customer ordered something from a particular store.
You could technically define both types of relationships for the same two entities. As an example: maybe you need to give the customer the option to select a default store, but you also need to be able to record the last date that a customer ordered something from a particular store. You could implement the DefaultStore field on the Customer table with the foreign key to the Store table and also create a relationship table to track all the stores that a customer has ordered from.
If you had some weird situation where every customer had their own store, then you wouldn’t even need to create two tables for your entities because you can fit all the attributes for both the customer and the store into one table.
In short, the way you determine which type of relationship to implement is to ask yourself what questions you will need to ask the database. The way you design it will restrict the relational data you can collect as well as the queries you can ask. If I design a one-to-many relationship from the store to the customer, I won’t be able to ask questions about all the stores that each customer has ordered from unless I can get to that information though other relationships. For example, I could create an entity called "purchases" which has a one-to-many relationship to the customer and store. If each purchase is defined to relate to one customer and one store, now I can query “what stores has this customer ordered from?” In fact with this structure I am able to capture and report on a much richer source of information about all of the customer's purchases at any store. So you also need to consider the context of all the other relationships in your database to decide which relationship to implement between two particular entities.
There is no magic formula, so it just takes practice, experience, and a little creativity. ER Diagrams are a great way to get your design out of your head and onto paper so that you can analyze your design and ensure that you can get the right types of questions answered. There are also a lot of books and resources to learn about database architecture. One good book I learned a lot from was “Database System Concepts” by Abraham Silberschatz and Henry Korth.
Say you have two tables A and B. Consider an entry from A and think of how many entries from B it could possibly be related with at most: only one, or more? Then consider an entry from B and think of how many entries in A it could be related with.
Some examples:
Table A: Mothers, Table B: Children. Each child has only one mother but a mother may have one or more children. Mothers and Children have a one-to-many relationship.
Table A: Doctors, Table B: Patients. Each patient may be visiting one or more doctors and each doctor treats one or more patients. So they have a many-to-many relationship.
An example of one to one:
LicencePlate to Vehicle. One licence plate belongs to one vehicle and one vehicle has one licence plate.
I am trying to lay out the concept for a Relational DB and I ran into some conceptual Problems:
If I have multiple discrete Entities that are "nested" in each other/have a hierarchy e.g.:
Bosses can have multiple Employees. These employees have different Projects they do and One Project has again multiple sections.
So
B1-Bn:
E1-En
P1-Pn
Section1 -SectionN
How would that be best mapped in a database?
Or in other words, how is this hierarchy best mapped in a relational db?
Now I have Costumers that interact with these Employees.
They are met by the bosses
Then they decide which employee will work for them.
Then they are assigned Projects, with one or more sections.
How would that be best mapped.
the Relations 1-n, m-n, 1-1: Can they be used for e.g.:
This is a Foreignkey because of the 1-n relationship.
This is a ManytoManyField because of the m-n relationship.
And is there a excellent online tool to better understand/visualize that.
Thanks so much for your time!
You may want to follow a course on relational database design; this subject takes more than a few days to explain or master. But you are on the right track.
The first thing you may be seeing is a hierarchy, but before you know it there will be relationships that aren't hierarchical, so a network is formed.
This is why relational databases do not work with hierarchies.
You identify different types of entities and have one table for each type.
For each entity type you identify the properties of such entities - each property will be a column of the table.
If a property does not have an atomic value, but a structured value, these structured values must be regarded as an entity, and must be given its own table, and the property will be a foreign key referring that table.
In this way, you will form a network of tables linked by foreign keys. This is called an entity-relationship diagram. Many designers advocate creating such a diagram first, without mapping the entity types to tables directly. They allow many-to-many relationships between entity types in the diagram. A foreign key between tables on the other hand is always many-to-1 or 1-to-1. So these designers have an "implementation" step in which they introduce an additional table for each many-to-many relationship. Personally I don't use many-to-many relationships in my diagrams to begin with.
What is normalization in MySQL and in which case and how we need to use it?
I try to attempt to explain normalization in layman terms here. First off, it is something that applies to relational database (Oracle, Access, MySQL) so it is not only for MySQL.
Normalisation is about making sure each table has the only minimal fields and to get rid of dependencies. Imagine you have an employee record, and each employee belongs to a department. If you store the department as a field along with the other data of the employee, you have a problem - what happens if a department is removed? You have to update all the department fields, and there's opportunity for error. And what if some employees does not have a department (newly assigned, perhaps?). Now there will be null values.
So the normalisation, in brief, is to avoid having fields that would be null, and making sure that the all the fields in the table only belong to one domain of data being described. For example, in the employee table, the fields could be id, name, social security number, but those three fields have nothing to do with the department. Only employee id describes which department the employee belongs to. So this implies that which department an employee is in should be in another table.
Here's a simple normalization process.
EMPLOYEE ( < employee_id >, name, social_security, department_name)
This is not normalized, as explained. A normalized form could look like
EMPLOYEE ( < employee_id >, name, social_security)
Here, the Employee table is only responsible for one set of data. So where do we store which department the employee belongs to? In another table
EMPLOYEE_DEPARTMENT ( < employee_id >, department_name )
This is not optimal. What if the department name changes? (it happens in the US government all the time). Hence it is better to do this
EMPLOYEE_DEPARTMENT ( < employee_id >, department_id )
DEPARTMENT ( < department_id >, department_name )
There are first normal form, second normal form and third normal form. But unless you are studying a DB course, I usually just go for the most normalized form I could understand.
Normalization is not for MYSql only. Its a general database concept.
Normalization is the process of
efficiently organizing data in a
database. There are two goals of the
normalization process: eliminating
redundant data (for example, storing
the same data in more than one table)
and ensuring data dependencies make
sense (only storing related data in a
table). Both of these are worthy goals
as they reduce the amount of space a
database consumes and ensure that data
is logically stored.
Normal forms in SQL are given below.
First Normal form (1NF): A relation is
said to be in 1NF if it has only
single valued attributes, neither
repeating nor arrays are permitted.
Second Normal Form (2NF): A relation
is said to be in 2NF if it is in 1NF
and every non key attribute is fully
functional dependent on the primary
key.
Third Normal Form (3NF): We say that a
relation is in 3NF if it is in 2NF and
has no transitive dependencies.
Boyce-Codd Normal Form (BCNF): A
relation is said to be in BCNF if and
only if every determinant in the
relation is a candidate key.
Fourth Normal Form (4NF): A relation
is said to be in 4NF if it is in BCNF
and contains no multivalued dependency.
Fifth Normal Form (5NF): A relation is
said to be in 5NF if and only if every
join dependency in relation is implied
by the candidate keys of relation.
Domain-Key Normal Form (DKNF): We say
that a relation is in DKNF if it is
free of all modification anomalies.
Insertion, Deletion, and update
anomalies come under modification
anomalies
Seel also
Database Normalization Basics
It's a technique for ensuring that your data remains consistent, by eliminating duplication. So a database in which the same information is stored in more than one table is not normalized.
See the Wikipedia article on Database normalization.
(It's a general technique for relational databases, not specific to MySQL.)
While creating a database schema for your application, you need to make sure that you avoid any information being stored in more than one column across different tables.
As every table in your DB, identifies a significant entity in your application, a unique identifier is a must-have columns for them.
Now, while deciding the storage schema, various kinds of relationships are being identified between these entities (tables), viz-a-viz, one-to-one, one-to-many, many-to-many.
For a one-to-one relationship (eg. A
Student has a unique rank in the
class), same table could be used to
store columns (from both tables).
For a one-to-many relationship (eg.
A semester can have multiple
courses), a foreign key is being
created in a parent table.
For a many-to-many relationship (eg.
A Prof. attends to many students and
vice-versa), a third table needs to
be created (with primary key from
both tables as a composite key), and
related data of the both tables will
be stored.
Once you attend to all these scenarios, your db-schema will be normalized to 4NF.
In the field of relational database
design, normalization is a systematic
way of ensuring that a database
structure is suitable for
general-purpose querying and free of
certain undesirable
characteristics—insertion, update, and
deletion anomalies—that could lead to
a loss of data integrity.[1] E.F.
Codd, the inventor of the relational
model, introduced the concept of
normalization and what we now know as
the first normal form in 1970.[2] Codd
went on to define the second and third
normal forms in 1971,[3] and Codd and
Raymond F. Boyce defined the
Boyce-Codd normal form in 1974.[4]
Higher normal forms were defined by
other theorists in subsequent years,
the most recent being the sixth normal
form introduced by Chris Date, Hugh
Darwen, and Nikos Lorentzos in
2002.[5]
Informally, a relational database
table (the computerized representation
of a relation) is often described as
"normalized" if it is in the third
normal form (3NF).[6] Most 3NF tables
are free of insertion, update, and
deletion anomalies, i.e. in most cases
3NF tables adhere to BCNF, 4NF, and
5NF (but typically not 6NF).
A standard piece of database design
guidance is that the designer should
create a fully normalized design;
selective denormalization can
subsequently be performed for
performance reasons.[7] However, some
modeling disciplines, such as the
dimensional modeling approach to data
warehouse design, explicitly recommend
non-normalized designs, i.e. designs
that in large part do not adhere to
3NF.[8]
Edit: Source: http://en.wikipedia.org/wiki/Database_normalization