i am tracking exercises. i have a workout table with
id
exercise_id (foreign key into exercise table)
now, some exercises like weight training would have the fields:
weight, reps (i just lifted 10 times # 100 lbs.)
and other exercises like running would have the fields: time, distance (i just ran 5 miles and it took 1 hours)
should i store these all in the same table and just have some records have 2 fields filled in and the other fields blank or should this be broken down into multiple tables.
at the end of the day, i want to query for all exercises in a day (which will include both types of exercises) so i will have to have some "switch" somewhere to differentiate the different types of exercises
what is the best database design for this situation
There are a few different patterns for modelling object oriented inheritance in database tables. The most simple being Single table inheritance, which will probably work great in this case.
Implementing it is mostly according to your own suggestion to have some fields filled in and the others blank.
One way to do it is to have an "exercise" table with a "type" field that names another table where the exercise-specific details are, and a foreign key into that table.
if you plan on keeping it only 2 types, just have exercise_id, value1, value2, type
you can filter the type of exercise in the where clause and alias the column names in the same statment so that the results don't say value1 and value2, but weight and reps or time and distance
Related
I have a table where I have these fields:
id(primary key, auto increment)
car registration number
car model
garage id
and 31 fields for each day of the mont for each row.
In these fields I have char of 1 or 2 characters representing car status on that date. I need to make a query to get number of each possibility for that day, field of any day could have values: D, I, R, TA, RZ, BV and LR.
I need to count in each row, amount of each value in that row.
Like how many I , how many D and so on. And this for every row in table.
What best approach would be here? Also maybe there is better way then having field in database table for each day because it makes over 30 fields obviously.
There is a better way. You should structure the data so you have another table, with rows such as:
CarId
Date
Status
Then your query would simply be:
select status, count(*)
from CarStatuses
where date >= #month_start and date < month_end
group by status;
For your data model, this is much harder to deal with. You can do something like this:
select status, count(*)
from ((select status_01 as status
from t
) union all
(select status_02
from t
) union all
. . .
(select status_31
from t
)
) s
group by status;
You seem to have to start with most basic tutorials about relational databases and SQL design. Some classic works like "Martin Gruber - Understanding SQL" may help. Or others. ATM you miss the basics.
Few hints.
Documents that you print for user or receive from user do not represent your internal data structures. They are created/parsed for that very purpose machine-to-human interface. Inside your program should structure the data for easy of storing/processing.
You have to add a "dictionary table" for the statuses.
ID / abbreviation / human-readable description
You may have a "business rule" that from "R" status you can transition to either "D" status or to "BV" status, but not to any other. In other words you better draft the possible status transitions "directed graph". You would keep it in extra columns of that dictionary table or in one more specialized helper table. Dictionary of transitions for the dictionary of possible statuses.
Your paper blank combines in the same row both totals and per-day detailisation. That is easy for human to look upon, but for computer that in a sense violates single responsibility principle. Row should either be responsible for primary record or for derived total calculation. You better have two tables - one for primary day by day records and another for per-month total summing up.
Bonus point would be that when you would change values in the primary data table you may ask server to automatically recalculate the corresponding month totals. Read about SQL triggers.
Also your triggers may check if the new state properly transits from the previous day state, as described in the "business rules". They would also maybe have to check there is not gaps between day. If there is a record for "march 03" and there is inserted a new the record for "march 05" then a record for "march 04" should exists, or the server would prohibit adding such a row. Well, maybe not, that is dependent upon you business processes. The general idea is that server should reject storing any data that is not valid and server can know it.
you per-date and per-month tables should have proper UNIQUE CONSTRAINTs prohibiting entering duplicate rows. It also means the former should have DATE-type column and the latter should either have month and year INTEGER-type columns or have a DATE-type column with the day part in it always being "1" - you would want a CHECK CONSTRAINT for it.
If your company has some registry of cars (and probably it does, it is not looking like those car were driven in by random one-time customers driving by) you have to introduce a dictionary table of cars. Integer ID (PK), registration plate, engine factory number, vagon factory number, colour and whatever else.
The per-month totals table would not have many columns per every status. It would instead have a special row for every status! The structure would probably be like that: Month / Year / ID of car in the registry / ID of status in the dictionary / count. All columns would be integer type (some may be SmallInt or BigInt, but that is minor nuancing). All the columns together (without count column) should constitute a UNIQUE CONSTRAINT or even better a "compound" Primary Key. Adding a special dedicated PK column here in the totaling table seems redundant to me.
Consequently, your per-day and per-month tables would not have literal (textual and immediate) data for status and car id. Instead they would have integer IDs referencing proper records in the corresponding cars dictionary and status dictionary tables. That you would code as FOREIGN KEY.
Remember the rule of thumb: it is easy to add/delete a row to any table but quite hard to add/delete a column.
With design like yours, column-oriented, what would happen if next year the boss would introduce some more statuses? you would have to redesign the table, the program in many points and so on.
With the rows-oriented design you would just have to add one row in the statuses dictionary and maybe few rows to transition rules dictionary, and the rest works without any change.
That way you would not
I am currently designing a SQL database to house a large amount of biological data. The main table has over 100 columns, where each row is a particular sampling event and each column is a species name. Values are the number of individuals found of that species for that sampling event.
Often, I would like to aggregate species together based on their taxonomy. For example: suppose Sp1, Sp2, and Sp3 belong to Family1; Sp4, Sp5, and Sp6 belong to Family2; and Family1 and Family2 belong to Class1. How do I structure the database so I can simply query a particular Family or Class, instead of listing 100+ columns each time?
My first thought was to create a second table that lists the attributes of each column from the first table. Such that the primary key in the second table corresponded to the column headers in table 1, and the columns in table 2 are the categories I would want to select by (such as Family, Feeding type, life stage, etc.). However, I'm not sure how to write a query that can join tables in such a way.
I'm a newbie to SQL, and am not sure if I'm going about this in completely the wrong way. How can I structure my data/write queries to accomplish my goal?
Thanks in advance.
No, no, no. Don't make species columns in the table.
Instead, where you have one row now, you want multiple rows. It would have columns such as:
id: auto generated sequential number
sampleId: whatever each row in the current table belongs to
speciesId: reference to the species table
columns of data for that species on that sampling
The species table could then have a hierarchy, the entire hierarchy with genus, family, order, and so on.
I have 5 tables that have the same structure and same columns: id, name, description. So I wonder what is the best way to design or to avoid having 5 tables that have the same columns:
Create a category table that will include my three common
columns and another column "enum" that will differentiate my categories
ex (city, country, continent, etc.)
Create a category table that will include my three common
columns and create the other five tables that will just include an
id.
Note that I would have an assocation table that should include the id of cities, id countries, id continents, etc. so i can display them into a report
Thank you for your advice.
The decision on how many tables to have under these circumstances simply depends.
The most important factor is whether the five things are independent entities or whether they are related. A simple way to understand this is by understanding foreign key relationships: Will other tables have a column that could refer to any of the five (say "geoid")? Or will other tables have a column that generally refers to one of the five ("cityid", "countryid")? The ability to define helpful foreign key constraints often drives the table structure.
There are other considerations. If your data is at the geographic level, then it might represent hierarchies . . . cities are in countries, countries are on continents. Some databases (such as MySQL) do not support hierarchical queries at all. Under these circumstances, you might consider denormalizing the data for querying purposes.
Other considerations can also come into play. If your application is going to be internationalized, then having all the reference tables in a single place is handy -- for providing cultural-specific information (language, currency symbol, and so on). One way of handling this situation is to put all such references in a single table (and perhaps using more sophisticated foreign key relationships).
The column names are not important, just the data in the columns. If City description, country description and continent description are different information then you are already doing this the right way. The only time you would aim to reduce this data would be if you were repeating information but for the titles of the data it's fine.
In fact. You are doing this correctly. Country will have different values from city for every field mentioned. Id is just an id, every table should have one. Name and description wont be the same across country and city.
Also, this way if you want a countrys name you dont have to go through every country, continent and city. You only have 192 or so entries to go through. If you had all of that in one massive table you would have to use it for everything and go through every result every time you want data. You would also have to distinguish between cities, countries and continents in some other way than the separate tables.
Eg:
method 1, with 5 tables:
SELECT * FROM country
does the same as
method 2, 1 table:
SELECT * FROM table WHERE enumvalue = 'country';
If you have tables representing city, country and continent, and they all have exactly the same fields, you have a fundamental problem. In real life, every city is in a country and every country is in at least one continent (more or less) but your data structure does not reflect that. Your city table should look something like this:
id (primary key)
countryId (foreign key to country)
name
other fields
You'll need a similar relationship between countries and continents. However, before you do so, you have to decide what to do about countries like Russia which is in two continents and Palau which isn't really in any.
You may also want to have a provinceStateTerritory table to help you sort out the 38 places in the United States named Springfield. Or, you may want to handle that situation differently.
I am hopping on a project that sits on top of a Sql Server 2008 DB with what seems like an inefficient schema to me. However, I'm not an expert at anything SQL, so I am seeking for guidance.
In general, the schema has tables like this:
ID | A | B
ID is a unique identifier
A contains text, such as animal names. There's very little variety; maybe 3-4 different values in thousands of rows. This could vary with time, but still a small set.
B is one of two options, but stored as text. The set is finite.
My questions are as follows:
Should I create another table for names contained in A, with an ID and a value, and set the ID as the primary key? Or should I just put an index on that column in my table? Right now, to get a list of A's, it does "select distinct(a) from table" which seems inefficient to me.
The table has a multitude of columns for properties of A. It could be like: Color, Age, Weight, etc. I would think that this is better suited in a separate table with: ID, AnimalID, Property, Value. Each property is unique to the animal, so I'm not sure how this schema could enforce this (the current schema implies this as it's a column, so you can only have one value for each property).
Right now the DB is easily readable by a human, but its size is growing fast and I feel like the design is inefficient. There currently is not index at all anywhere. As I said I'm not a pro, but will read more on the subject. The goal is to have a fast system. Thanks for your advice!
This sounds like a database that might represent a veterinary clinic.
If the table you describe represents the various patients (animals) that come to the clinic, then having properties specific to them are probably best on the primary table. But, as you say column "A" contains a species name, it might be worthwhile to link that to a secondary table to save on the redundancy of storing those names:
For example:
Patients
--------
ID Name SpeciesID Color DOB Weight
1 Spot 1 Black/White 2008-01-01 20
Species
-------
ID Species
1 Cocker Spaniel
If your main table should be instead grouped by customer or owner, then you may want to add an Animals table and link it:
Customers
---------
ID Name
1 John Q. Sample
Animals
-------
ID CustomerID SpeciesID Name Color DOB Weight
1 1 1 Spot Black/White 2008-01-01 20
...
As for your original column B, consider converting it to a boolean (BIT) if you only need to store two states. Barring that, consider CHAR to store a fixed number of characters.
Like most things, it depends.
By having the animal names directly in the table, it makes your reporting queries more efficient by removing the need for many joins.
Going with something like 3rd normal form (having an ID/Name table for the animals) makes you database smaller, but requires more joins for reporting.
Either way, make sure to add some indexes.
I am wondering is it more useful and practical (size of DB) to create multiple tables in sql with two columns (one column containing foreign key and one column containing random data) or merge it and create one table containing multiple columns. I am asking this because in my scenario one product holding primary key could have sufficient/applicable data for only one column while other columns would be empty.
example a. one table
productID productname weight no_of_pages
1 book 130 500
2 watch 50 null
3 ring null null
example b. three tables
productID productname
1 book
2 watch
3 ring
productID weight
1 130
2 50
productID no_of_pages
1 500
The multi-table approach is more "normal" (in database terms) because it avoids columns that commonly store NULLs. It's also something of a pain in programming terms because you have to JOIN a bunch of tables to get your original entity back.
I suggest adopting a middle way. Weight seems to be a property of most products, if not all (indeed, a ring has a weight even if small and you'll probably want to know it for shipping purposes), so I'd leave that in the Products table. But number of pages applies only to a book, as do a slew of other unmentioned properties (author, ISBN, etc). In this example, I'd use a Products table and a Books table. The books table would extend the Products table in a fashion similar to class inheritance in object oriented program.
All book-specific properties go into the Books table, and you join only Products and Books to get a complete description of a book.
I think this all depends on how the tables will be used. Maybe your examples are oversimplifying things too much but it seems to me that the first option should be good enough.
You'd really use the second example if you're going to be doing extremely CPU intensive stuff with the first table and will only need the second and third tables when more information about a product is needed.
If you're going to need the information in the second and third tables most times you query the table, then there's no reason to join over every time and you should just keep it in one table.
I would suggest example a, in case there is a defined set of attributes for product, and an example c if you need variable number of attributes (new attributes keep coming every now and then) -
example c
productID productName
1 book
2 watch
3 ring
attrID productID attrType attrValue
1 1 weight 130
2 1 no_of_pages 500
3 2 weight 50
The table structure you have shown in example b is not normalized - there will be separate id columns required in second and third tables, since productId will be an fk and not a pk.
It depends on how many rows you are expecting on your PRODUCTS table. I would say that it would not make sense to normalize your tables to 3N in this case because product name, weight, and no_of_pages each describe the products. If you had repeating data such as manufacturers, it would make more sense to normalize your tables at that point.
Without knowing the background (data model), there is no way to tell which variant is more "correct". both are fine in certain scenarios.
You want three tables, full stop. That's best because there's no chance of watches winding up with pages (no pun intended) and some books without. If you normalize, the server works for you. If you don't, you do the work instead, just not as well. Up to you.
I am asking this because in my scenario one product holding primary key could have sufficient/applicable data for only one column while other columns would be empty.
That's always true of nullable columns. Here's the rule: a nullable column has an optional relationship to the key. A nullable column can always be, and usually should be, in a separate table where it can be non-null.