I'm stuck trying to model a many to many relationship. Here's a representative sample of my issue using an e-commerce model:
+------------+-------------+----------+------------+
| date | customer_id | order_id | address_id |
+------------+-------------+----------+------------+
| 12/1/2019 | 1 | 1 | 1 |
| 12/15/2019 | 2 | 1 | 1 |
| 12/15/2019 | 2 | 2 | 2 |
| 1/1/2020 | 2 | 3 | 1 |
| 1/1/2020 | 1 | 2 | 3 |
| 1/1/2020 | 1 | 3 | 2 |
| 1/2/2020 | 1 | 4 | 1 |
+------------+-------------+----------+------------+
A customer can place many orders.
A customer can ship to multiple addresses.
Addresses can have multiple customers.
How would I model a "household" junction/bridging table? In my data above, customer_id 1 and 2 could possibly be a family or business entity. What if I wanted to know on a given date, how many orders that household/entity placed, how many customers that household represented and how many locations did they ship to?
I think this is the start of how I build this model, but stuck on writing the bridging query.
orders addresses
+-------------+----------+ +-------------+------------+
| customer_id | order_id | | customer_id | address_id |
+-------------+----------+ +-------------+------------+
| 1 | 1 | | 1 | 1 |
| 1 | 2 | | 1 | 2 |
| 1 | 3 | | 1 | 3 |
| 1 | 4 | | 2 | 1 |
| 2 | 1 | | 2 | 2 |
| 2 | 2 | +-------------+------------+
| 2 | 3 |
+-------------+----------+
In a relational database you want to keep all the similar data in separate tables. This helps you with making joins later. I would recommend:
Related
I'm designing a database for a workout tracker app. Each user should be able to track multiple workouts (routines). A workout can have multiple exercises an exercise can be used in many workouts. Each exercise will have a specific track type (weight and reps, distance and time, only reps).
My tables so far:
| User | |
|------|-------|
| id | name |
| 1 | Ilka |
| 2 | James |
| Exercise | | |
|----------|---------------------|---------------|
| id | name | track_type_id |
| 1 | Barbell Bench Press | 1 |
| 2 | Squats | 1 |
| 3 | Deadlifts | 1 |
| 4 | Rowing Machine | 3 |
| Workout | | |
|---------|---------|-----------------|
| id | user_id | name |
| 1 | 1 | Chest & Triceps |
| 2 | 1 | Legs |
| Workout_Exerice (Junction table) | |
|-----------------|------------------|------------|
| id | exersice_id | workout_id |
| 1 | 1 | 1 |
| 2 | 2 | 1 |
| 3 | 4 | 1 |
| Workout_Sets | | | |
|--------------|---------------------|------|--------|
| id | workout_exersice_id | reps | weight |
| 1 | 1 | 12 | 120 |
| 2 | 1 | 10 | 120 |
| 3 | 1 | 8 | 120 |
| 4 | 2 | 10 | 220 |
| 5 | 3 | null | null |
| TrackType | |
|-----------|-----------------|
| id | name |
| 1 | Weight and Reps |
| 2 | Reps Only |
| 3 | Distance Time |
My issue is how to incorporate the TrackType table for each workout set, my first option was to create columns in the Workout_Sets table for each tracking type (weight and reps, distance and time, only reps) but that means for many rows I will have many nulls. Another option I thought was to use an EAV type table but I'm not sure. Also do you think my design is efficient (Over-normalization)?
I would say that the most efficient way is to have nulls in your table. The alternative would require you to split many of the category's into separate tables. Also a recommendation is that you start factoring a User ID table into your database
Your description states that “Each exercise will have a specific track type” suggesting a one-to-one relationship between Exercise and TrackType, and that the relationship is unchanging. As such, the exercise table should have a TrackType column.
I suspect, however, that your problem description may be lacking specificity, making it difficult to give you sound advice. For instance, if the TrackType can vary for any given exercise, your TrackType column may belong on the Workout_Sets table. If the relationship between TrackType and Exercise/Workout_Sets is many-to-many, then you will need another junction table.
Your question regarding “over-normalization” depends upon many factors that are specific to your solution. In general, I would say no - the degree of normalization appears to be appropriate.
Lets say we have a client table for sports brands like nike and adidas.
+--------------+------------+
| Client Table | |
+--------------+------------+
| Id | ClientName |
| 1 | Nike |
| 2 | Adidas |
+--------------+------------+
We also record customer information and their preferred sport and fitness level. Sports and fitness level are used in dropdown lists.
+--------------+------------+
| Sports Table | |
+--------------+------------+
| Id | Name |
| 1 | Basketball |
| 2 | Volleyball |
+--------------+------------+
+------------------+---------------+
| Fitnesslvl Table | |
+------------------+---------------+
| Id | Fitness Level |
| 1 | Beginner |
| 2 | Intermediate |
| 3 | Advance |
+------------------+---------------+
+----------------+--------------+----------+----------------+
| Customer Table | | | |
+----------------+--------------+----------+----------------+
| Id | CustomerName | SportsId | FitnessLevelId |
| 1 | John | 1 | 1 |
| 2 | Doe | 2 | 3 |
+----------------+--------------+----------+----------------+
Then sports brands want to filter our customer via sports and fitness level. In this example nike wants all sports while adidas only wants customer interested in basketball. Likewise, nike wants customer in all fitness level while adidas only wants advanced fitness level.
+---------------+----------+----------+
| Sports Filter | | |
+---------------+----------+----------+
| Id | ClientId | SportsId |
| 1 | 1 | 1 |
| 2 | 1 | 2 |
| 3 | 2 | 1 |
+---------------+----------+----------+
+-------------------+----------+--------------+
| Fitnesslvl Filter | | |
+-------------------+----------+--------------+
| Id | ClientId | FitnessLvlId |
| 1 | 1 | 1 |
| 2 | 1 | 2 |
| 3 | 1 | 3 |
| 4 | 2 | 3 |
+-------------------+----------+--------------+
How can we handle logging in this case when we want to record failed filters for the sports and fitness level? I'm thinking of two options
Create different table for each failed filter.
-Sports Failed Filter
-FitnessLevel Failed Filter
+----------------------+-------------+----------------+
| Sports Failed Filter | | |
+----------------------+-------------+----------------+
| Id | CustomerId | SportsFilterId |
| 1 | 1 | 2 |
| 2 | 1 | 3 |
+----------------------+-------------+----------------+
However if we have 10 filters, this means we will also have 10 failed filters table. I think this is very difficult to maintain.
Instead of different table for dropdown values like sports and fitness level, we can create lookup table, and a single failedfilter table.
I think the tradeoff is its not simple and there is no strict referential integrity.
Please let me know if you have different solution for this.
EDIT:
This filters are used in a backend application and the filtering logic is there. I dont plan to include this logic in the database as the query will be very complex and hard to maintain.
I have this table discount_user_product structure
discount_id | user_id | product_id
------------+---------+------------
1 | 1 | 1
1 | 1 | 2
1 | 2 | 3
My tables
Users
id | name |
----------+---------+-
1 | Bobby |
2 | Max |
3 | Joj |
Discounts
id | discount | expired_at
----------+----------+------------
1 | 100 |
2 | 50 |
3 | 30 |
Products
id | user_id | title
----------+---------+------------
1 | 1 | Milk
2 | 1 | Chees
3 | 2 | Jeam
I would like to use a better tables structure and decompose discount_user_product to this structure:
discount_user
discount_id | user_id |
------------+---------+-
1 | 1 |
1 | 2 |
user_product
user_id | product_id |
--------+------------+-
1 | 1 |
1 | 2 |
2 | 3 |
Is this will be the right way to make better performance and compliance with the rules of normalizations?
The database I'm working on is DB2 and I have a problem similar to the following scenario:
Table Structure
-------------------------------
| Teacher Seating Arrangement |
-------------------------------
| PK | seat_argmt_id |
| | teacher_id |
-------------------------------
-----------------------------
| Seating Arrangement |
-----------------------------
|PK FK | seat_argmt_id |
|PK | Row_num |
|PK | seat_num |
|PK | child_name |
-----------------------------
Table Data
------------------------------
| Teacher Seating Arrangement|
------------------------------
| seat_argmt_id | teacher_id |
| 1 | 1 |
| 2 | 1 |
| 3 | 1 |
| 4 | 1 |
| 5 | 2 |
------------------------------
---------------------------------------------------
| Seating Arrangement |
---------------------------------------------------
| seat_argmt_id | row_num | seat_num | child_name |
| 1 | 1 | 1 | Abe |
| 1 | 1 | 2 | Bob |
| 1 | 1 | 3 | Cat |
| | | | |
| 2 | 1 | 1 | Abe |
| 2 | 1 | 2 | Bob |
| 2 | 1 | 3 | Cat |
| | | | |
| 3 | 1 | 1 | Abe |
| 3 | 1 | 2 | Cat |
| 3 | 1 | 3 | Bob |
| | | | |
| 4 | 1 | 1 | Abe |
| 4 | 1 | 2 | Bob |
| 4 | 1 | 3 | Cat |
| 4 | 2 | 2 | Dan |
---------------------------------------------------
I want to see where there are duplicate seating arrangements for a teacher. And by duplicates I mean where the row_num, seat_num, and child_name are the same among different seat_argmt_id for one teacher_id. So with the data provided above, only seat id 1 and 2 are what I would want to pull back, as they are duplicates on everything but the seat id. If all the children on the 2nd table are exact (sans the primary & foreign key, which is seat_argmt_id in this case), I want to see that.
My initial thought was to do a count(*) group by row#, seat#, and child. Everything with a count of > 1 would mean it's a dupe and = 1 would mean it's unique. That logic only works if you are comparing single rows though. I need to compare multiple rows. I cannot figure out a way to do it via SQL. The solution I have involves going outside of SQL and works (probably). I'm just wondering if there is a way to do it in DB2.
Does this do what you want?
select d.teacher_id, sa.row_num, sa.seat_num, sa.child_name
from seatingarrangement sa join
data d
on sa.seat_argmt_id = d.seat_argmt_id
group by d.teacher_id, sa.row_num, sa.seat_num, sa.child_name
having count(*) > 1;
EDIT:
If you want to find two arrangements that are the same:
select sa1.seat_argmt_id, sa2.seat_argmt_id
from seatingarrangement sa1 join
seatingarrangement sa2
on sa1.seat_argmt_id < sa2.seat_argmt_id and
sa1.row_num = sa2.row_num and
sa1.seat_num = sa2.seat_num and
sa1.child_name = sa2.child_name
group by sa1.seat_argmt_id, sa2.seat_argmt_id
having count(*) = (select count(*) from seatingarrangement sa where sa.seat_argmt_id = sa1.seat_argmt_id) and
count(*) = (select count(*) from seatingarrangement sa where sa.seat_argmt_id = sa2.seat_argmt_id);
This finds the matches between two arrangements and then verifies that the counts are correct.
Ok, so i have a bit of a complex query i am trying to come up with in my rails application. I have four tables: Clients, Projects, Invoices, Invoice_Line_Items. I am trying to get certain bits of data from all of those tables and display it in a "reports" type view in my application. This is what the structures look like for the four tables:
Clients
| id | name | archive |
----------------------------------------
| 1 | Client 1 | 0 |
| 2 | Client 2 | 0 |
Projects
| id | client_id | name | archive |
------------------------------------------------------
| 1 | 1 | Project 1 | 0 |
| 2 | 1 | Project 2 | 1 |
| 3 | 2 | Project 3 | 0 |
| 4 | 2 | Project 4 | 1 |
Invoices
| id | client_id | project_id | name | archive |
----------------------------------------------------------------------
| 1 | 1 | 1 | Invoice 1 | 0 |
| 2 | 1 | 1 | Invoice 2 | 0 |
| 3 | 1 | 2 | Invoice 3 | 1 |
| 4 | 1 | 2 | Invoice 4 | 1 |
| 5 | 2 | 3 | Invoice 5 | 0 |
| 6 | 2 | 3 | Invoice 6 | 0 |
| 7 | 2 | 4 | Invoice 7 | 1 |
| 8 | 2 | 4 | Invoice 8 | 1 |
Invoice_Line_Items
| id | invoice_id | name | amount_due |
---------------------------------------------------------
| 1 | 1 | Item 1 | 500 |
| 2 | 1 | Item 2 | 500 |
| 3 | 2 | Item 3 | 500 |
| 4 | 2 | Item 4 | 500 |
| 5 | 3 | Item 5 | 500 |
| 6 | 3 | Item 6 | 500 |
| 7 | 4 | Item 7 | 500 |
| 8 | 4 | Item 8 | 500 |
| 9 | 5 | Item 9 | 500 |
| 10 | 5 | Item 10 | 500 |
| 11 | 6 | Item 11 | 500 |
| 12 | 6 | Item 12 | 500 |
| 13 | 7 | Item 13 | 500 |
| 14 | 7 | Item 14 | 500 |
| 15 | 8 | Item 15 | 500 |
| 16 | 8 | Item 16 | 500 |
Ok, hope those diagrams make sense enough. What i am looking for as a result set is this (example data set taken from above example data):
| clients.name | current_projects | archived_projects | total_amount_due | total_amount_paid |
-----------------------------------------------------------------------------------------------------------
| Client 1 | 1 | 1 | 2000 | 2000 |
| Client 2 | 1 | 1 | 2000 | 2000 |
Ok, so here's what's going on there:
Getting all non-archived clients
Getting a count of all non-archived projects
Getting a count of all archived projects
Getting a total_amount_due from the invoice_line_items table that is a sum of all of the non-archived invoices
Getting a total_amount_paid from the invoice_line_items table that is a sum of all of the archived invoices
I am relatively new to Rails and this is a fairly complex query (at least in my head). Please let me know if there is a simpler solution that i am overlooking or if i am just over complicating it. If i need to do multiple queries in my controller that's fine, i was just wanting to see if i could get away with one sql call. I'm pretty sure i can do this pretty easily with some subqueries but i'm not sure how to write those in the controller in Rails.
Thanks for any help or direction you can provide and if this question is just outrageous or whatever just let me know and i'll delete it and go search the Googles more (have tried already to no avail).
Ok, well i ended up figuring out a solution myself. Not quite sure it's the best solution....feels heavy and messing but i just created quite a few objects in the controller to get the sql statements i needed to pull the data from the database. I basically have one object for each column (column, not each row). Let me know if anyone can figure out a better solution.