I have the following issue:
I am planning a database with trains. Each train has carriages which divides into compartment and non-compartment. Both of these types has three classes: 1,2,3, and all of them has different amount of places in compartment or in a row.
I could create the following table:
| type | class | seats in a row | rows | seats in a compartment | compartments |
| non-c| 1 | 3 | 18 | NULL | NULL |
| non-c| 2 | 4 | 22 | NULL | NULL |
| non-c| 3 | 5 | 25 | NULL | NULL |
| comp | 1 | NULL | NULL | 6 | 9 |
| comp | 2 | NULL | NULL | 8 | 10 |
| comp | 3 | NULL | NULL | 10 | 11 |
That is, I would set NULL when a property is not connected with a particular type (example number of places in a compartment for a non-compartment car), but in my opinion it is not good looking solution. Do you have any other ideas? Maybe two tables: non-compartment attributes and compartment attributes? However I think that better solution exists.
Like you said, break your design into tables that correspond to logical entities (normalization), that way you will have more scope to accommodate change and less redundant info.
Proposed design
Tables
Tbl_train(Id, other_train_info) -Stores only tran info
Tbl_Carriage(Id, trainid, carriagetypeid, other_carriage_info) - stores carriage info related to a train
Tbl_carriagetype_master(Id, type_desc, class, .. Etc) - stores all the static compartmental info
Related
I'm working on my senior High School Project and am reaching out to the community for help! (As my teacher doesn't know the answer to my question).
I have a simple "Products" table as shown below:
I also have a "Orders" table shown below:
Is there a way I can create a field in the "Orders" table named "Total Cost", and make that automaticly calculate the total cost from all the products selected?
Firstly, I would advise against storing calculated values, and would also strongly advise against using calculated fields in tables. In general, calculations should be performed by queries.
I would also strongly advise against the use of multivalued fields, as your images appear to show.
In general, when following the rules of database normalisation, most sales databases are structured in a very similar manner, containing with the following main tables (amongst others):
Products (aka Stock Items)
Customers
Order Header
Order Line (aka Order Detail)
A good example for you to learn from would be the classic Northwind sample database provided free of charge as a template for MS Access.
With the above structure, observe that each table serves a purpose with each record storing information pertaining to a single entity (whether it be a single product, single customer, single order, or single order line).
For example, you might have something like:
Products
Primary Key: Prd_ID
+--------+-----------+-----------+
| Prd_ID | Prd_Desc | Prd_Price |
+--------+-----------+-----------+
| 1 | Americano | $8.00 |
| 2 | Mocha | $6.00 |
| 3 | Latte | $5.00 |
+--------+-----------+-----------+
Customers
Primary Key: Cus_ID
+--------+--------------+
| Cus_ID | Cus_Name |
+--------+--------------+
| 1 | Joe Bloggs |
| 2 | Robert Smith |
| 3 | Lee Mac |
+--------+--------------+
Order Header
Primary Key: Ord_ID
Foreign Keys: Ord_Cust
+--------+----------+------------+
| Ord_ID | Ord_Cust | Ord_Date |
+--------+----------+------------+
| 1 | 1 | 2020-02-16 |
| 2 | 1 | 2020-01-15 |
| 3 | 2 | 2020-02-15 |
+--------+----------+------------+
Order Line
Primary Key: Orl_Order + Orl_Line
Foreign Keys: Orl_Order, Orl_Prod
+-----------+----------+----------+---------+
| Orl_Order | Orl_Line | Orl_Prod | Orl_Qty |
+-----------+----------+----------+---------+
| 1 | 1 | 1 | 2 |
| 1 | 2 | 3 | 1 |
| 2 | 1 | 2 | 1 |
| 3 | 1 | 1 | 4 |
| 3 | 2 | 3 | 2 |
+-----------+----------+----------+---------+
You might also opt to store the product description & price on the order line records, so that these are retained at the point of sale, as the information in the Products table is likely to change over time.
The project I'm working on is an application that lets you design data entry forms, and automagically generates a schema in an underlying PostgreSQL database
to persist them as well as the browsing and editing UI.
The use case I've encountered this with is a store back-office database, but the app itself intends to be somewhat universal. The administrator creates the following entry forms with the given fields:
Customers
name (text box)
Items
name (text box)
stock (number field)
Order
customer (combo box selecting a customer)
order lines (a grid showing order lines)
OrderLine
item (combo box selecting an item)
count (number field)
When all this is done, the resulting database schema will be equivalent to this:
create table Customers(id serial primary key,
name varchar);
create table Items(id serial primary key,
name varchar,
stock integer);
create table Orders(id serial primary key);
create table OrderLines(id serial primary key,
count integer);
create table Links(id serial primary key,
fk1 integer references Customers.id,
fk2 integer references Items.id,
fk3 integer references Orders.id,
fk4 integer references OrderLines.id);
Links being a special table that stores all the relationships between entities; every row has (usually) two of the foreign keys set to a value, and the rest set to NULL. Whenever a new entry form is added to the application instance, a new foreign key referencing the table for this form is added to Links.
So, suppose our shop stocks some widgets, gizmos, and thingeys. A customer named Adam orders two widgets and three gizmos, and Betty orders four gizmos and five thingeys. The database will contain the following data:
Customers
/----+-------\
| ID | NAME |
| 1 | Adam |
| 2 | Betty |
\----+-------/
Items
/----+---------+-------\
| ID | NAME | STOCK |
| 1 | widget | 123 |
| 2 | gizmo | 456 |
| 3 | thingey | 789 |
\----+---------+-------/
Orders
/----\
| ID |
| 1 |
| 2 |
\----/
OrderLines
/----+-------\
| ID | COUNT |
| 1 | 2 |
| 2 | 3 |
| 3 | 4 |
| 4 | 5 |
\----+-------/
Links
/----+------+------+------+------\
| ID | FK1 | FK2 | FK3 | FK4 |
| 1 | 1 | NULL | 1 | NULL |
| 2 | 2 | NULL | 2 | NULL |
| 3 | NULL | NULL | 1 | 1 |
| 4 | NULL | NULL | 1 | 2 |
| 5 | NULL | NULL | 2 | 3 |
| 6 | NULL | NULL | 2 | 4 |
| 7 | NULL | 1 | NULL | 1 |
| 8 | NULL | 2 | NULL | 2 |
| 9 | NULL | 2 | NULL | 3 |
| 10 | NULL | 3 | NULL | 4 |
\----+------+------+------+------/
(The tables also contain a bunch of timestamps for auditing and soft deletion but I don't think they're relevant here, they just make writing the SQL by the administrator that much messier. The management app is also used to implement a bunch of different use cases, but they're generally primarily data entry, master-detail views, and either scalar fields or selection boxes.)
When I've had to write a join through this thing I'd grumbled about it to my coworker, who replied "well using separate tables for each relationship is one way to do it, this is another..." Leaving aside the obvious-to-me ugliness of the above and the practical issues, I also have a nagging feeling this has to be a violation of some normal form, but it's been a while since college and I'm struggling to figure out which of the criteria apply here.
Is there something stronger "well that's just your opinion" I can use when critiquing this design?
I am new to working with databases and I want to make sure I understand the best way to add or remove data from a database without making a mess of any related data.
Here is a scenario I am working with:
I have a Tags table, with an Identity ID column. The Tags can be selected via the web application to categorize stories that are submitted by a user. When the database was first seeded; like tags were seeded in order together. As you can see all the Campuses (cities) were 1-4, the Colleges (subjects) are 5-7, and Populations are 8-11.
If this database is live in production and the client wants to add a new Campus (City) tag, what is the best way to do this?
All the other city tags are sort of organized at the top, it seems like the only option is to insert any new tags at to bottom of the table, where they will end up taking whatever the next ID available is. I suppose this is fine because the Display category column will allow us to know which categories these new tags actually belong to.
Is this typical? Is there better ways to set up the database or handle this situation such that everything remains more organized?
Thank you
+----+------------------+---------------+-----------------+--------------+--------+----------+
| ID | DisplayName | DisplayDetail | DisplayCategory | DisplayOrder | Active | ParentID |
+----+------------------+---------------+-----------------+--------------+--------+----------+
| 1 | Albany | NULL | 1 | 0 | 1 | NULL |
| 2 | Buffalo | NULL | 1 | 1 | 1 | NULL |
| 3 | New York City | NULL | 1 | 2 | 1 | NULL |
| 4 | Syracuse | NULL | 1 | 3 | 1 | NULL |
| 5 | Business | NULL | 2 | 0 | 1 | NULL |
| 6 | Dentistry | NULL | 2 | 1 | 1 | NULL |
| 7 | Law | NULL | 2 | 2 | 1 | NULL |
| 8 | Student-Athletes | NULL | 3 | 0 | 1 | NULL |
| 9 | Alumni | NULL | 3 | 1 | 1 | NULL |
| 10 | Faculty | NULL | 3 | 2 | 1 | NULL |
| 11 | Staff | NULL | 3 | 3 | 1 | NULL |
+----+------------------+---------------+-----------------+--------------+--------+----------+
The terms "top" and "bottom" which you use aren't really applicable. "Albany" isn't at the "Top" of the table - it's merely at the top of the specific view you see when you query the table without specifying a meaningful sort order. It defaults to a sort order based on the Id or an internal ROWID parameter, which isn't the logical way to show this data.
Data in the table isn't inherently ordered. If you want to view your tags organized by their category, simply order your query by DisplayCategory (and probably by DisplayOrder afterwards), and you'll see your data properly organized. You can even create a persistent View that sorts it that way for your convenience.
I have a database table that has a companion many-to-many self-join table alongside it. The primary table is part and the other table is alternate_part (basically, alternate parts are identical to their main part with different #s). Every record in the alternate_part table is also in the part table. To illustrate:
`part`
| part_id | part_number | description |
|---------|-------------|-------------|
| 1 | 00001 | wheel |
| 2 | 00002 | tire |
| 3 | 00003 | window |
| 4 | 00004 | seat |
| 5 | 00005 | wheel |
| 6 | 00006 | tire |
| 7 | 00007 | window |
| 8 | 00008 | seat |
| 9 | 00009 | wheel |
| 10 | 00010 | tire |
| 11 | 00011 | window |
| 12 | 00012 | seat |
`alternate_part`
| main_part_id | alt_part_id |
|--------------|-------------|
| 1 | 5 | // Wheel
| 5 | 1 | // |
| 5 | 9 | // |
| 9 | 5 | // |
| 2 | 6 | // Tire
| 6 | 2 | // |
| ... | ... | // |
I am trying to produce a simple SQL query that will give me a list of all alternates for a main part. The tricky part is: some alternates are only listed as alternates of alternates, it is not guaranteed that every viable alternate for a part is listed as a direct alternate. e.g., if 'Part 3' is an alternate of 'Part 2' which is an alternate of 'Part 1', then Part 3 is an alternate of Part 1 (even if the alternate_part table doesn't list a direct link). The reverse is also true (Part 1 is an alternate of Part 3).
Basically, right now I'm pulling alternates and iterating through them
SELECT p.*, ap.*
FROM part p
INNER JOIN alternate_part ap ON p.part_id = ap.main_part_id
And then going back and doing the same again on those alternates. But, I think there's got to be a better way.
The SQL query I'm looking for will basically give me:
| part_id | alt_part_id |
|---------|-------------|
| 1 | 5 |
| 1 | 9 |
For part_id = 1, even when 1 & 9 are not explicitly linked in the alternates table.
Note: I have no control whatever over the structure of the DB, it is a distributed software solution.
Note 2: It is an Oracle platform, if that affects syntax.
You have to create hierarchical tree , probably you have to use connect by prior , nocycle query
something like this
select distinct p.part_id,p.part_number,p.description,c.main_part_id
from part p
left join (
select main_part_id,connect_by_root(main_part_id) real_part_id
from alternate_part
connect by NOCYCLE prior main_part_id = alternate_part_id
) c
on p.part_id = c.real_part_id and p.part_id != c.main_part_id
order by p.part_id
You can read full documentation about Hierarchical queries at http://docs.oracle.com/cd/B28359_01/server.111/b28286/queries003.htm
Sorry for the title, perhaps it's not very clear.
I have some SQL queries in a script that depend on each other.
The script uses a temporary table in which the data is inserted (the #temp_data table).
This is the expected output:
___________________________________
| speed1 | speed2 | distance |
| 1 | NULL | 10 |
| 3 | NULL | 40 |
| 5 | NULL | 90 |
| NULL | 1 | 10 |
| NULL | 3 | 40 |
| NULL | 5 | 90 |
Here is the query structure (I didn't include the actual query since it's too big):
-- First group
queryForSpeed1
queryToUpdateDistanceBasedOnSpeed1
-- Second group
queryForSpeed2
queryToUpdateDistanceBasedOnSpeed2
If I run the first group of queries (queryForSpeed1 and queryToUpdateDistanceBasedOnSpeed1) separately from the second group then I get the expected output: only the speed1 and distance columns contain data:
___________________________________
| speed1 | speed2 | distance |
| 1 | NULL | 10 |
| 3 | NULL | 40 |
| 5 | NULL | 90 |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
The same happens when I run the second group:
___________________________________
| speed1 | speed2 | distance |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
| NULL | 1 | 10 |
| NULL | 2 | 40 |
| NULL | 3 | 90 |
BUT, when I run both groups: all the distances are NULL:
___________________________________
| speed1 | speed2 | distance |
| 1 | NULL | NULL |
| 3 | NULL | NULL |
| 5 | NULL | NULL |
| NULL | 1 | NULL |
| NULL | 2 | NULL |
| NULL | 3 | NULL |
I believe this is somehow related to transaction management and temporary tables, although I wasn't able to find anything relevant to solve the problem on Google.
From what I've read, SQL Server keeps a transaction log where it stores every update, insert and whatever... when it arrives at the end of the script it actually does all those insertions and updates.
So the update I did for the distance column finds all the speeds as being NULL because the data wasn't yet inserted in the temporary table from the previous updates, but at the end of the query the speeds are inserted in the table so that's why they are visible.
I played a bit with the GO statement to execute my script in batches, but no luck so far...
What am I doing wrong? Can someone point me in the right direction, please?
EDIT
Here is the actual query.
The problem is not related to transactions, but rather to the way you conduct updates to #temp_speed_profile. The second pass through #temp_speed_profile retrieves all six records. Speed_new is null in first record of Voyage_Id, consequently #distance becomes null. As you retain the value of #distance in next turn, it remains null.
Problem goes away when using different temporary tables because second pass works on second set of data only.
A note on cursors - when defining one make sure to add local and fast_forward. Local because it is limiting cursors' scope, and fast_forward to optimize fetches.
It is almost certainly caused by the way you have written your queries.
To confirm, just rewrite your queries using #temp_data1 and #temp_data2, rather than a single table #temp_data.