I have a table called Station with many fields,
one of the fields is - StationPrice.
I want to hold more information about the payment process such as - currency, paymentStatus and etc (somewhere like 10 fields).
My question is if I need to expand the current table - Station with the new fields or to have a field called - StationPriceId that will be a foreign key to another table called StationPrices which will store all the information about the price related to that station.
The answer to your question is 1 of the most popular answers in DB world - it depends. It might look nicer if this info is split into 2 different tables, however you need to understand that if you split it then you'll need to 2 inserts instead of 1, the same with updated and deletes. Moreover you'll need to JOIN this table every time you'll need this data. I would go with single table first and then moved it to the separate column when the specific need come up.
From other side of view, if this data will be rarely accessed and JOIN/DELETE/INSERT overhead will be minimal then it is OK to move it.
My question is if I need to expand the current table - Station with the new fields or to have a field called - StationPriceId that will be a foreign key to another table called StationPrices which will store all the information about the price related to that station.
Yes it is better to use two tables, Based on information you had provided - it is better to use a separate table.
You might want to maintain a price change history
Hence if you maintain a separate table, you can make earlier price as Active = false and enter a new price for the particular station
Related
I am developing an application for making quotations. First you make cost break down (or calculation) and upon that result you add item to quotation. The problem is that i have many product, so each category of a product will have its own cost break down form with different parameters to be filled in. If I will have only one table for cost breakdown, then it will be huge (a lot of fields in table). I have a feeling that this is not the right approach. So I came up with diagram below:
Is this solution even possible, or I must have "N" (if I have N-tables) different FK for each cost break down table? Do you have any better solutions?
I have another question if my linking table "Quotation_QtnDetail" is necessary?
It would be possible to store a reference to a particular value in one of these tables by having a CalculationType column indicating which table the record is in, along with a generic reference ID column (containing the ID of the relevant record). For example, if you were storing a CalcId of 123 and a CalculationType of 2, this would point to the record with ID 123 in the Calc2 table.
The downside to doing this is you're going to lose the ability to validate your data using FK constraints, and it will also make joins to your calculation tables a bit more complicated.
Regarding the Quotation_QtnDetail table, unless a QtnDetail record could ever be linked to multiple Quotation records, there is no need for this extra linking table. Instead, just link it directly by adding a QtnId column to the QtnDetail table. Similarly, you may also be able to remove the Calc_QtnItm table if an item is only ever linked to a single calculation record.
I want to design a changelog for a few tables. Lets call it table restaurant. Every time a user modifies the list of restaurants the change should be logged.
Idea 1
My first idea was to create 2 tables. One which contains all the restaurants RESTAURANT_VALUE (restaurantId*, restaurantValueId*, address, phone, ..., username, insertDate). Every time a change is made it creates a new entry. Then a table RESTAURANT (restaurantId*, restaurantValueId) which will link to the current valid restaurantValueId. So one table that holds the current and the previous version.
Idea 2
It starts with 2 tables as well. One of them contains all current restaurants. e.g. RESTAURANT_CURRENT. And a second table which contains all changes RESTAURANT_HISTORY. Therefore both need to have the exactly same columns. Every time a change occurs the values of the 'current' table are copied into the history table, and the new version in the 'current'.
My opinion
Idea 1 doesn't care if columns will ever be added or not, therefore maintenance and adding of columns would be easy. However, I think as the database grows... wouldn't it slow down? Idea 2 has the advantage that the table with the values will never have any 'old' stuff and not get crowded.
Theoretically I think Idea 1 should be the one done
What do you think. Would you go for Idea 1 or another one? Are there any other important practical thoughts I am not aware of?
The approach strongly depends on your needs. Why would you want a history table?
If it's just for auditing purposes, then make a separate restaurant_history table (idea 2) to keep the history aside. If you want to present the history in the application, then go for signle restaurants table with one of below options:
seq_no - record version number incrementing with each update. If you need current data, you must search for highest seq_no for given restaurant_id(s), so optionally use also current marker, allowing straighforward current = true
valid_from, valid_to - where valid_to is NULL for current record
Sometimes there is need to query efficiently which attributes exactly changed. to do this easily you can consider a history table on attribute level: (restaurant_id, attribute, old_value, new_value, change_date, user).
I am currently going to be designing an app in vb.net to work with an access back-end database. I have been trying to think of ways to reduce down data redundancy
and I have an example scenario below:
Lets imagine, for an example purpose, I have a customers table and need to highlight all customers in WI and send them a letter. The customers table would
contain all the customers and properties associated with customers (Name, Address, Etc) so we would query for where the state is "WI" in the table. Then we would
take the results of that data, and append it into a table with a "completion" indicator (So from 'CUSTOMERS' to say 'WI_LETTERS' table).
Lets assume some processing needs to be done so when its completed, mark a field in that table as 'complete', then allow the letters to be printed with
a mail merge. (SELECT FROM 'WI_LETTERS' WHERE INDICATOR = COMPLETE).
That item is now completed and done. But lets say, that every odd year (2013) we also send a notice to everyone in the table with a state of "WI". We now query the
customers table when the year is odd and the customer's state is "WI". Then append that data into a table called 'notices' with a completion indicator
and it is marked complete.
This seems to keep the data "task-based" as the data is based solely around the task at hand. However, isn't this considered redundant data? This setup means there
can be one transaction type to many accounts (even multiple times to the same account year after year), but shouldn't it be one account to many transactions?
How is the design of this made better?
You certainly don't want to start creating new tables for each individual task you perform. You may want to create several different tables for different types of tasks if the information you need to track (and hence the columns in those tables) will be quite different between the different types of tasks, but those tables should be used for all tasks of that particular type. You can maintain a field in those tables to identify the individual task to which each record applies (e.g., [campaign_id] for Marketing campaign mailouts, or [mail_batch_id], or similar).
You definitely don't want to start creating new tables like [WI_letters] that are segregated by State (or any client attribute). You already have the customers' State in the [Customers] table so the only customer-related attribute you need in your [Letters] table is the [CustomerID]. If you frequently want to see a list of Letters for Customers in Wisconsin then you can always create a saved Query (often called a View in other database systems) named [WI_Letters] that looks like
SELECT * FROM Letters INNER JOIN Customers ON Customers.CustomerID=Letters.CustomerID
WHERE Customers.State="WI"
I am trying to design a sqlite database that will store notes. Each of these notes will have common fields like title, due date, details, priority, and completed.
In addition though, I would like to add data for more specialized notes like price for shopping list items and author/publisher data for books.
I also want to have a few general purpose fields that users can fill with whatever text data they want.
How can I design my database table in this case?
I could just have a field for each piece of data for every note, but that would waste a lot of fields and I'd like to have other options and suggestions.
There are several standard approaches you could use for solving this situation.
You could create separate tables for each kind of note, copying over the common columns in each case. this would be easy but it would make it difficult to query over all notes.
You could create one large table with many columns and some kind of type field which would let you know which type of note it is (and therefore which subset of columns to use)
CREATE TABLE NOTE ( ID int PRIMARY KEY, NOTE_TYPE int, DUEDATE datetime, ...more common fields, price NUMBER NULL, author VARCHAR(100) NULL,.. more specific fields)
you could break your tables up into a inheritance relationship something like this:
CREATE TABLE NOTE ( ID int PRIMARY KEY, NOTE_TYPE int, DUEDATE datetime, ...more common fields);
CREATE TABLE SHOPPINGLITITEM (ID int PRIMARY KEY, NOTE_ID int FORIENKEY NOTE.ID, price number ... more shopping list item fields)
Option 1 would be easy to implement but would involve lots of mostly redundant table definitions.
Option 2 would be easy to create and easy to write queries on but would be space inefficient
And option 3 would be more space efficient and less redundant but would possibly have slower queries because of all the foreign keys.
This is the typical set of trade-offs for modeling these kinds of relationships in SQL, any of these solutions could be appropriate for use case depending non your performance requirements.
You could create something like a custom_field table. It gets pretty messy once you start to normalize.
So you have your note table with it's common fields.
Now add:
dynamic_note_field
id label
1 publisher
2 color
3 size
dynamic_note_field_data
id dynamic_note_field_id value
1 1 Penguin
2 1 Marvel
3 2 Red
Finally, you can relate instances of your data with the fields they use through
note_dynamic_note_field_data
note_id dynamic_note_field_data_id
1 1
1 3
2 2
So now we've said: note_id 1 has two additional fields. The first one has a value "Penguin" and represents a publisher. The second one has a value of "Red" and represents a color.
So what's the point of normalizing it this far?
You're not wasting space adding fields to every item (you relate a note with it's additional dynamic field via the m2m table).
You're not storing redundant labels (you may continue to store redundant data however as the same publisher is likely to appear many times... this aspect is extremely subjective. If you want rich data about your publishers you typically want to take the step of turning them into their own entity rather than an ad-hoc string. Be careful when making this leap because it adds an extra level of hairiness to the db. Evaluate the use case accordingly.
The dynamic_note_field acts as your data definition. If you're interested in answering a question such as "what are the additional fields I've created" this lets you do it easily without searching all of your dynamic_note_field_data. Eventually, you might add extra info to this table such as a type field. I like to create this separation off the bat, but that might be a violation of the YAGNI principle in your case.
Disadvantages:
It's not too bad to search for all notes that have a publisher, where that publisher is "Penguin".
What's tricky is something like "Find any note with a value of 'Penguin' in any field". You don't know up front which field's your searching. At this point you're better off with a separate index that's generated alongside your normalized db data which acts as the point of truth. Again, the nice thing about normalization is that you maintain the data in a very lossless, non-destructive state.
For data you want to store but does not have to be searchable, another option is to serialize it to/from JSON and store it in a TEXT column. This gives you arbitrary structure, but you cannot readily query against those values.
Yet another option is to dump SQLite and go with an object database. I seem to recall there are one or two working for Android. I have not tried any of these, however.
Just create a small table which contains the common fields of all your notes.
Then a table for each class of special notes you have, that that contains all the extra fiels plus a reference on your first table.
For each note you will enter, you create a row in your main table (that contains the common fields) and a row in your extra table that contains the extra fields, and a reference to the row in your main table.
Then you will just have to make a join in you request.
With this solution :
1)you have a safe design (can't access fields that are not part of your note)
2)your db will be optimized
I am designing a system for a client, where he is able to create data forms for various products he sales him self.
The number of fields he will be using will not be more than 600-700 (worst case scenario). As it looks like he will probably be in the range of 400 - 500 (max).
I had 2 methods in mind for creating the database (using meta data):
a) Create a table for each product, which will hold only fields necessary for this product, which will result to hundreds of tables but with only the neccessary fields for each product
or
b) use one single table with all availabe form fields (any range from current 300 to max 700), resulting in one table that will have MANY fields, of which only about 10% will be used for each product entry (a product should usualy not use more than 50-80 fields)
Which solution is best? keeping in mind that table maintenance (creation, updates and changes) to the table(s) will be done using meta data, so I will not need to do changes to the table(s) manually.
Thank you!
/**** UPDATE *****/
Just an update, even after this long time (and allot of additional experience gathered) I needed to mention that not normalizing your database is a terrible idea. What is more, a not normalized database almost always (just always from my experience) indicates a flawed application design as well.
i would have 3 tables:
product
id
name
whatever else you need
field
id
field name
anything else you might need
product_field
id
product_id
field_id
field value
Your key deciding factor is whether normalization is required. Even though you are only adding data using an application, you'll still need to cater for anomalies, e.g. what happens if someone's phone number changes, and they insert multiple rows over the lifetime of the application? Which row contains the correct phone number?
As an example, you may find that you'll have repeating groups in your data, like one person with several phone numbers; rather than have three columns called "Phone1", "Phone2", "Phone3", you'd break that data into its own table.
There are other issues in normalisation, such as transitive or non-key dependencies. These concepts will hopefully lead you to a database table design without modification anomalies, as you should hope for!
Pulegiums solution is a good way to go.
You do not want to go with the one-table-for-each-product solution, because the structure of your database should not have to change when you insert or delete a product. Only the rows of one or many tables should be inserted or deleted, not the tables themselves.
While it's possible that it may be necessary, having that many fields for something as simple as a product list sounds to me like you probably have a flawed design.
You need to analyze your potential table structures to ensure that each field contains no more than one piece of information (e.g., "2 hammers, 500 nails" in a single field is bad) and that each piece of information has no more than one field where it belongs (e.g., having phone1, phone2, phone3 fields is bad). Either of these situations indicates that you should move that information out into a separate, related table with a foreign key connecting it back to the original table. As pulegium has demonstrated, this technique can quickly break things down to three tables with only about a dozen fields total.