I am trying to learn Microsoft MVC 2, and have in that case found a small project I wanted to deploy it on.
My idea was to simulate a restaurant where you can order a table.
Basics:
A user can only reserve a full table,
so I don't have the trouble of
merging people on different tables.
A person can order a table for a
certain amount of hours.
My question was how I could make the data model the smartest way. I thought of just having a my database like this:
Table
{
Id,
TableName
}
Reservations
{
Id
TableId
ReservedFrom
ReservedTo
UserId
}
User
{
UserId
UserName
...
}
By doing it this way I would have to program a lot of the logic in e.g. the business layer, to support which tables are occupied at what time, instead of having the data model handle it.
Therefore do you guys have a better way to do this?
A database constraint that doesn't allow two reservations for a table to overlap using a function that counts the number of reservations for the table whose start datetime or end datetime is between the datetimes of the row being inserted. The constraint would ensure that the count is 1 (the row just inserted).
Also, you should have your user interface block times where all of the tables available are reserved. Essentially, you'd get all the reservations for the day and for each hour block count the number of reservations that span that block -- if the count is equal to the number of tables, then the UI doesn't allow that block to be chosen. This spans your business/UI layers.
There's no way to know how long a person will take to eat so you cannot assume the ReservedTo time is accurate. I would build up timeslots in a seperate table. That way a simple unique constraint could be used.
TimeSlot { id, StartTime, Duration }
Additionally I would dump the user table and just put in a name.
Reservation { id, tableId, date, timeSlotId, Name }
put the unique constraint on { tableId, date, timeSlotId }
This could be expanded out to allow different durations for different tables but that is outside tke scope of a learning project I think.
Related
Using Java and Oracle.
We need to update changes in Email, UserID of employee to third party.
Actual table is Employee and intermediate table we keep which we will use for comparison of changes before sending to third party.
Following are database designs coming in mind for intermediate table:
Only Single table:
EmployeeiD|Value|Type|UpdateDate
Value is userid or email, type will be 'email' or 'userid'. Update date is kept so to figure out that which of email or userid was different and update to third party.
Multiple Table:
Employee_EmailID
EmpId|EmailID|Updatedate
Employee_UserID
EmpId|UserID|Updatedate
Java flow will be:
Pick employee from actual table.
Pick employee from above intermediate table.
Compare differences. Update difference to third party.
Update above table with updated value and last update date.
Which one is consider as best way, single table approach or multiple table or is there any standard way to implement the same? There are 10,000 Employees in system.
Intermediate table is just storing Delta records i.e Records transferred to third party so that it can be compared next day.
Good database design has separate tables for different concepts. Using the same database column to hold different types of data will lead to code which is harder to understand, prone to data corruption and less performative.
You may think it's only two tables and a few tens of thousands of rows, so does it matter? But that is only your current requirement. What you choose now will set the template for what happens when (say) you need to add telephone numbers to the process.
Now in future if we get 5 more entities to update
Do you mean "entities", like say Customers rather than Employees? Or do you really mean "attributes" as in my example of Employee Telephone Number?
Generally speaking we have a separate table for distinct entities, and all the attributes of that entity are grouped at the same cardinality. To take your example, I would expect an Employee to have one UserID and one Email Address so I would design the table like this:
Employee_audit
EmpId|UserID|EmailID|Updatedate
That is, I have one record which stores the complete state of the Employee record at the Updatedate.
If we add a new entity, Customers then we have a new table. Simple. But a new attribute like Employee Phone Number offers a choice, because an employee can have more than one: work landline, mobile, fax, home, etc. So we could represent this in three ways: a child table with a type column, multiple child tables for each type, or as distinct columns on the Employee record.
For the main Employee table I would choose the separate table (or tables, depending on whether I'm shooting for 6NF). But for an audit table I would choose one record per Employee and pivot the phone numbers like this:
Employee_audit
EmpId|UserID|EmailID|Landline|Mobile|Fax|Home|Updatedate
The one thing I would never do is have a single table with type and value columns. It seems attractive because it means we could track additional entities without any further DDL. But in fact it becomes harder to re-assemble the complete state of an Employee at any given time with each attribute we add. Also it means the auditing process itself is more complicated (because it needs to determine which attributes have changed and whether it needs to audit the change) and more expensive (because changing three attributes on the same record entails inserting three audit records).
I have two models that are related to each other. One model contains users, and the other contains all courses and related timestamp of class start. Now the "related key" between them are the 'user_id' which are in both tables. I manage to get out data when having:
return $this->hasMany(ClassInfo::class,'user_id','user_id');
This works just fine. However, since I use the model in a with clause I need to the only one of the classes that starts a given time if start time crashes with another course for the user. I have tried with both:
return $this->hasMany(ClassInfo::class,'user_id','user_id')->take(1);
return $this->hasMany(ClassInfo::class,'user_id','user_id')->limit(1);
But both just give me empty collections, I don't see why that happends?
Is there any way that I can make it return for example the one with the biggest id value from the Class table (id is auto incremental for each course registered on a user).
Thanks for any tips and guidance!
https://web.stanford.edu/dept/itss/docs/oracle/10g/olap.101/b10333/globdiag.gif
Assume that we have a start schema as above..
My questions is - In real-time how do we populate the colums (unit_price, unit_cost) columns of the fact table..?
Can anyone provide me a start schema tables with real data?
I am having hard time in understanding star schema...
Please help!..
Start schema consists of two types of tables fact tables and dimensions.
The ideal of the star design is that you can split your data in two part.
The static part is described with dimensions and the dynamic part (= transactions) in the fact table.
Each transaction is stored in the fact table as a new record and is connected to the surrounding dimensions, that define the context of the transaction.
The example in link contains two fact tables: SHIPMENTS and PRODUCT_CONDITIONS.
Note that the fact tables in the link are dubbed UNITS_HISTORY_FACT and PRICE_AND_COST_HISTORY_FACT, but I find this not a best choice.
The SHIPMENTS table stores one record for each shipment of a PRODUCT to a CUSTOMER at some TIME, via a defined CHANNEL.
All the above information is defined using the corresponding keys of the respective dimensions.
The fact table also contains MEASURES describing the attributes of the transaction, here the number of UNITS shipped.
The structure of the fact table would be therefore
CUSTOMER_ID
PRODUCT_ID
TIME_ID
CHANNEL_ID
UNITS
The second fact table (bottom) is more interesting, because here you split the product in two parts:
PRODUCT dimension defining the ID, name and other more static attributes
PRODUCT_CONDITION this is fact table, designed with the expectation the price and cost of the product will change over time.
With each change of the price or cost insert a new record in the fact table and connect it to the PRODUCT and TIME (of change).
The structure of the fact table would be therefore
PRODUCT_ID
TIME_ID
UNIT_PRICE
UNIT_COST
Final note the the design of the TIME dimension.
The best practice to connect the fact table with the dimension tables is to use meaningless ID (surrogate keys), but for TIME dimension you should be careful. For big (time partitioned) fact table is often used the natural key (DATE format) to be able to deploy the partitioning features. See more details in How I Defined a Time Dimension Using a Surrogate Key and other resources in web.
I have an app that houses product data via a Product model and table. Each product has specific state availability (multiple states) that I will need to filter and/or search by in the future. I am hoping to find someone who can tell me the most efficient way to store this data. As I see it, I have two options.
The first is to simply create 50 columns in my table, titled with each state name and containing a boolean value. I can then simply filter by = "avail in California" if product.ca. While this certainly works, it seems a bit cumbersome, especially when searching for multiple state availability.
The second option would be to simply have one column("states") that stores an array of available states and then filter by = "avail in California" if product.states.include? "CA". This seems like a better solution for two reasons. The first, it just allows for a cleaner DB table. Second, and more important, I can allow my user to search by simply saving the user's input as a variable(user_input) and then = "avail in California" if product.states.include? user_input. This solution does call for a little more work up front however when saving the product in the DB, since I won't be able to simply check off a boolean value.
I think option two makes the most sense, but am hoping for some advice as to why or why not. I have found a few similar questions, but they do not seem to explain which solution would be better, just how to accomplish each.
What should I do?
You should normalize unless you have a really good reason not to, and I don't see one in your overview.
To normalize, you should have the following tables:
product table, one record per product
state table, one record per state
product_state table, one entry for every product that is in a state
The product_state schema looks like this:
(product_state_id PK, product_id FK, state_id FK)
UNIQUE INDEX(product_id,state_id);
This allows you to have a product in zero or more states.
I assume that since you’re selling products, you will be charging taxes. There are different taxes by state, county, city. There are country taxes in some countries too.
So you need to abstract these entities into a common parent, usually called GeopoliticalArea, so that you can point a single foreign key (from, say, a tax rates table) at any subtype.
create table geopolitical_area (
id bigint primary key,
type text not null
);
create table country (
id bigint primary key references geopolitical_area(id),
name text not null unique
);
-- represents states/provinces:
create table region (
id bigint primary key references geopolitical_area(id),
name text not null,
country_id bigint references country(id),
unique (name, country_id)
);
insert into geopolitical_area values
(1, 'Country'),
(2, 'Region');
insert into country values
(1, 'United States of America');
insert into region values
(2, 'Alabama', 1);
The Overview:
I have a table "category" that is for the most part used to categorise products and currently looks like this:
CREATE TABLE [dbo].[Category]
(
CategoryId int IDENTITY(1,1) NOT NULL,
CategoryNode hierarchyid NOT NULL UNIQUE,
CategoryString AS CategoryNode.ToString() PERSISTED,
CategoryLevel AS CategoryNode.GetLevel() PERSISTED,
CategoryTitle varchar(50) NOT NULL,
IsActive bit NOT NULL DEFAULT 1
)
This table is heavily queried to display the category hierarchy on a shopping website (typically every page view) and can have a substantial number of items.
I'm using the Entity Framework in my data layer.
The Question:
I have a need to add what could potentially be a fairly large "description" which could come in the form of the entire contents of a web-page and I'm wondering whether I should store this in a related table rather than adding it to the existing category table given that the entity framework will drag the "description" column out of the database 100% of the time when 99.5% of the time I'll only want the CategoryTitle and CategoryId.
Typically I wouldn't worry about the overhead of the Entity Framework, but in the case I think it might be important to take it into consideration. I could work around this with a view or a complex type from a stored proc, but this means a lot of refactoring that I'd prefer to avoid.
I'm just interested to know if anyone has any thoughts, suggestions or a desire to slap my wrists in relation to this scenario...
EDIT:
I should add that the reason I'm hesitating to set up a secondary table is because I don't like the idea of adding an additional table that has a 1 to 1 relationship with the Category table - it seems somewhat pointless. But I'm also not a DBA so I'm not sure whether this is an acceptable practice or not.
You could put your column in the table and then create an index covering all other columns. That way the index will be used when you do all lookups you do with your current schema.
The key word for this construction is Covering Index: http://en.m.wikipedia.org/wiki/Database_index#Covering_index
I would store in a different table for the simple reason to not increase the size of a record in Category table. An increase in record size due to such a VARCHAR column will reduce the number of records that can fit a given disk page (typically of size 4KB), thereby increasing the number of pages to fetch to main memory to search, increasing the number of disk accesses, affecting the query execution times.
I would store this in a different table (i.e. vertically partition the category table into most frequently accessed columns and not-so-frequently used columns), and define a OneToOne relationship at the application layer with the entity that contains the not-so-frequently used column, as a member in the main Category entity, set the fetch type to LAZY.