I'm creating an Intranet for my company, and we want to have a stock management in it. We sell and rent alarm systems, and we want to have a good overview of what product is still in our offices, what has been rented or sold, at what time, etc.
At the moment I thought about this database design :
Everytime we create a new contract, this contract is about a location or a sale of an item. So we have an Product table (which is the type of product : alarms, alarm watches, etc.), and an Item table, which is the item itself, with it unique serial number. I thought about doing this, because I'll need to have a trace of where a specific item is, if it's at a client house (rented), if it's sold, etc. Products are related to a specific supplier, to whom we can take orders. But here, I have a problem, shouldn't the order table be related to Product ?
The main concern here is the link between Stock, Item, Movement stock. I wanted to create a design where I'd be able to see when a specific Item is pulled out of our stock, and when it enters the stock with the date. That's why I thought about a Movement_stock table. The Type_Movement is either In / Out.
But I'm a bit lost here, I really don't know how to do it nicely. That's why I'm asking for a bit of help.
I have the same need, and here is how I tackled your stock movement issue (which became my issue too).
In order to modelize stock movement (+/-), I have my supplying and my order tables. Supplying act as my +stock, and my orders my -stock.
If we stop to this, we could compute our actual stock which would be transcribed into this SQL query:
SELECT
id,
name,
sup.length - ord.length AS 'stock'
FROM
product
# Computes the number of items arrived
INNER JOIN (
SELECT
productId,
SUM(quantity) AS 'length'
FROM
supplying
WHERE
arrived IS TRUE
GROUP BY
productId
) AS sup ON sup.productId = product.id
# Computes the number of order
INNER JOIN (
SELECT
productId,
SUM(quantity) AS 'length'
FROM
product_order
GROUP BY
productId
) AS ord ON ord.productId = product.id
Which would give something like:
id name stock
=========================
1 ASUS Vivobook 3
2 HP Spectre 10
3 ASUS Zenbook 0
...
While this could save you one table, you will not be able to scale with it, hence the fact that most of the modelization (imho) use an intermediate stock table, mostly for performance concerns.
One of the downside is the data duplication, because you will need to rerun the query above to update your stock (see the updatedAt column).
The good side is client performance. You will deliver faster responses through your API.
I think another downside could be if you are managing high traffic store. You could imagine creating another table that stores the fact that a stock is being recomputed, and make the user wait until the recomputation is finished (push request or long polling) in order to check if every of his/her items are still available (stock >= user demand). But that is another deal...
Anyway even if the stock recomputation query is using anonymous subqueries, it should actually be quite fast enough in most of the relatively medium stores.
Note
You see in the product_order, I duplicated the price and the vat. This is for reliability reasons: to freeze the price at the moment of the purchase, and to be able to recompute the total with a lot of decimals (without loosing cents in the way).
Hope it helps someone passing by.
Edit
In practice, I use it with Laravel, and I use a console command, which will compute my product stock in batch (I also use an optional parameter to compute only for a certain product id), so my stock is always correct (relative to the query above), and I never manually update the stock table.
This is an interesting discussion and one that also could be augmented with stock availability as of a certain date...
This means storing:
Planned Orders for the Product on a certain date
Confirmed Orders as of a certain date
Orders Delivered
Orders Returned (especially if this is a hire product)
Each one of these product movements could be from and to a location
The user queries would then include:
What is my overall stock on hand
What is due to be delivered on a certain date
What will the stock on hand be as of a date overall
What will the stock on hand be as of a date for a location
The inventory design MUST take into account the queries and use cases of the users to determine design and also breaking normalisation rules to provide adequate performance at the right time.
Lots to consider and it all depends on the software use cases.
Related
I am building an order management system for an online store and would like to store information about the Product being ordered.
If I use a Foreign Key relationship to the Product, when someone changes the price, brand, supplier etc. of the Product or deletes it, the Order will be affected as well. I want the order management system to be able to display the state of the Product when it was ordered even if it is altered or deleted from the database afterwards.
I have thought about it long and hard and have come up with ideas such as storing a JSON string representation of the object; creating a duplicate Product whose foreign key I then use for the Order etc. However, I was wondering if there is a best practice or what other people use to handle this kind of situation in commercial software?
PS: I also have other slightly more complex situations, for instance, I would like the data for a User object attached to the Order to change as the User changes but then never get deleted when the User is deleted. An answer to the above question would definitely give me a good starting point.
This price-change problem is commonly handled in RDBMS (SQL) commerce applications by doing two things.
inserting rows into an order_detail table when an order is placed. Each row of that table contains the particulars of the item as sold: item_id, item_count, unit_price, total_price, unit_weight, total_weight, tax_status, and so forth. So, the app captures what actually was sold, and at what price. A later price change doesn't mess up sales records. You really have to do this.
a price table containing item_id, price, start_time, end_time. You retrieve the current price something like this:
SELECT item.item, price.price
FROM item
JOIN price ON item.item = price.item
AND price.start_date <= NOW()
AND (price.end_date > NOW() OR price.end_date IS NULL)
This approach allows you to keep track of historical prices, and also to set up future price changes. But you still copy the price into the order_detail table.
The point is: once you've accepted an order, its details cannot change in the future. You copy the actual customer data (name, shipping address, etc) into a separate order table from your current customer table when you accept the order, and (as mentioned above) the details of each item into an order_detail table.
Your auditors will hate you if you don't do this. Ask me how I know that sometime.
I would recommend creating attributes for the Order model and extracting the data you need one by one into those attributes while you are saving the model and then implementing a historical data table where you store JSONFields or some other version of the Product etc. when it is created or updated; that way people can refer to the historical data table if need be. This would be more efficient usage than storing the full fledged representation of the Product in the Order object as time taken to create the historical data is essentially charged to the admin creating the Product rather than the customer creating the Order. You can even create historical data objects in the background using threads etc. when you get to those advanced levels.
While it is hard answering your question without seeing your models.py at least, I will suggest archiving the results. You can add a boolean field called historical which defaults to False. When an order is made you need to set the previous order's (or orders') historical value to True in your view set or function.
Here, historical=True means the record is being archived. You can filter on this historical column to display what you want when. Sorry this is just a high-level outline.
I have a process wherein I need to keep the history of a database records information, however the user needs to be able to change it at any time they please.
Scenario:
Seller creates an item with price of $5 and name of "foo"
Buyers buys item, an order is created linking to that item id
A while later, seller updates item name to "foobar" and item price to $6
Buyer views order history. The item name should be "foo" and price should be $5 since that's what they bought it at, but they are "foobar" and $6, respectively
This happens because when the seller updates the item, they are updating the same item the order is related to.
I thought of 3 possible solutions to this problem, and I would like to get your thoughts on which one you think is best (maybe from your prior experience), or a better solution I have not yet thought of. This is my first time dealing with this situation, so not sure how best to proceed without needing a refactor later.
My solutions:
Make the item name and price immutable.
Bad UX, cause now user has to delete item and recreate it if they want to make a modification
Requires some kind of deleted_at column in case user wants to delete the item after it has been purchased so that I can still keep it for referencing later to grab history data
Create a second table for history purposes
Not horrible, but requires a second table with a different name, not a big fan of the idea
Would have to run queries potentially twice to check both tables for similar data, as opposed to just querying one table
Create two records in the same table, and mark a boolean flag or some other flag to differentiate from historical/current records
I like this one the best, but not sure if the boolean flag may have any negative performance implications
I've encountered this issue too, particularly in product catalogs where the price changes frequently. Or the price may be on sale or discounted for a specific customer for some reason.
The only solution I've found is to copy the relevant product details to the customer's order record at the time they buy the product. In your example, at least the product name and the product price would be copied.
This might seem like it goes against the philosophy of "don't store redundant data" but it's not redundant—it's a fact that the customer bought the product for some specific price on a specific date, and that is still a useful fact forever, even if the current price for that product changes.
There should still be a link to the original product table, so managers can track how many orders included each product, for example. But the current price in the product table does not affect the record of each customer's order.
You might also need to create a product history table, to keep a record of all the times the price or name was changed. But that's for historical record-keeping only, it wouldn't affect typical queries during shopping or buying activities.
In this design:
Product table always stores the current price.
When a customer buys a product, they copy the current price into their own order record.
When a manager changes a price, the app creates a new record in the ProductHistory table.
The most recent record for each product in the ProductHistory table matches the current price for the same product.
I'm working on the Product Catalog module of an Invoicing application.
When the user creates a new invoice the product name field should be an autocomplete field which shows the most recently used products from the product catalog.
How can I store this "usage recency/frequency" in the database?
I'm thinking about adding a new field recency which would be increased by 1 every time the product was used, and decreased by 1/(count of all products), when an other product is used. Then use this recency field for ordering, but it doesn't seem to me the best solution.
Can you help me what is the best practice for this kind of problem?
Solution for the recency calculation:
Create a new column in the products table, named last_used_on for example. Its data type should be TIMESTAMP (the MySQL representation for the Unix-time).
Advantages:
Timestamps contains both date and time parts.
It makes possible VERY precise calculations and comparisons in regard
to dates and times.
It lets you format the saved values in the date-time format of your
choice.
You can convert from any date-time format into a timestamp.
In regard to your autocomplete fields, it allows you to filter
the products list as you wish. For example, to display all products
used since [date-time]. Or to fetch all products used between
[date-time-1] and [date-time-2]. Or get the products used only on Mondays, at 1:37:12 PM, in the last two years, two months and three
days (so flexible timestamps are).
Resources:
Unix-Time
The DATE, DATETIME, and TIMESTAMP Types
How should unix timestamps be stored in int columns?
How to convert human date to unix timestamp in Mysql?
Solution for the usage rate calculation:
Well, actually, you are not speaking about a frequency calculation, but about a rate - even though one can argue that frequency is a rate, too.
Frequency implies using the time as the reference unit and it's measured in Hertz (Hz = [1/second]). For example, let's say you want to query how many times a product was used in the last year.
A rate, on the other hand, is a comparison, a relation between two related units. Like for example the exchange rate USD/EUR - they are both currencies. If the comparison takes place between two terms of the same type, then the result is a number without measurement units: a percentage. Like: 50 apples / 273 apples = 0.1832 = 18.32%
That said, I suppose you tried to calculate the usage rate: the number of usages of a product in relation with the number of usages of all products. Like, for a product: usage rate of the product = 17 usages of the product / 112 total usages = 0.1517... = 15.17%. And in the autocomplete you'd want to display the products with a usage rate bigger than a given percentage (like 9% for example).
This is easy to implement. In the products table add a column usages of type int or bigint and simply increment its value each time a product is used. And then, when you want to fetch the most used products, just apply a filter like in this sql statement:
SELECT
id,
name,
(usages*100) / (SELECT sum(usages) as total_usages FROM products) as usage_rate
FROM products
GROUP BY id
HAVING usage_rate > 9
ORDER BY usage_rate DESC;
Here's a little study case:
In the end, recency, frequency and rate are three different things.
Good luck.
To allow for future flexibility, I'd suggest the following additional (*) table to store the entire history of product usage by all users:
Name: product_usage
Columns:
id - internal surrogate auto-incrementing primary key
product_id (int) - foreign key to product identifier
user_id (int) - foreign key to user identifier
timestamp (datetime) - date/time the product was used
This would allow the query to be fine tuned as necessary. E.g. you may decide to only order by past usage for the logged in user. Or perhaps total usage within a particular timeframe would be more relevant. Such a table may also have a dual purpose of auditing - e.g. to report on the most popular or unpopular products amongst all users.
(*) assuming something similar doesn't already exist in your database schema
Your problem is related to many other web-scale search applications, such as e.g. showing spell corrections, related searches, or "trending" topics. You recognized correctly that both recency and frequency are important criteria in determining "popular" suggestions. In practice, it is desirable to compromise between the two: Recency alone will suffer from random fluctuations; but you also don't want to use only frequency, since some products might have been purchased a lot in the past, but their popularity is declining (or they might have gone out of stock or replaced by successor models).
A very simple but effective implementation that is typically used in these scenarios is exponential smoothing. First of all, most of the time it suffices to update popularities at fixed intervals (say, once each day). Set a decay parameter α (say, .95) that tells you how much yesterday's orders count compared to today's. Similarly, orders from two days ago will be worth α*α~.9 times as today's, and so on. To estimate this parameter, note that the value decays to one half after log(.5)/log(α) days (about 14 days for α=.95).
The implementation only requires a single additional field per product,
orders_decayed. Then, all you have to do is to update this value each night with the total daily orders:
orders_decayed = α * orders_decayed + (1-α) * orders_today.
You can sort your applicable suggestions according to this value.
To have an individual user experience, you should not rely on a field in the product table, but rather on the history of the user.
The occurrences of the product in past invoices created by the user would be a good starting point. The advantage is that you don't need to add fields or tables for this functionality. You simply rely on data that is already present anyway.
Since it is an auto-complete field, maybe past usage is not really relevant. Display n search results as the user types. If you feel that results are better if you include recency in the calculation of the order, go with it.
Now, implementation may defer depending on how and when product should be displayed. Whether it has to be user specific usage frequency or application specific (overall). But, in both case, I would suggest to have a history table, which later you can use for other analysis.
You could design you history table with atleast below columns:
Id | ProductId | LastUsed (timestamp) | UserId
And, now you can create a view, which will query this table for specific time range (something like product frequency of last week, last month or last year) and will give you highest sold product for specific time range.
Same can be used for User's specific frequency by adding additional condition to filter by Userid.
I'm thinking about adding a new field recency which would be increased
by 1 every time the product was used, and decreased by 1/(count of all
products), when an other product is used. Then use this recency field
for ordering, but it doesn't seem to me the best solution.
Yes, it is not a good practice to add a column for this and update every time. Imagine, this product is most awaiting product and people love to buy it. Now, at a time, 1000 people or may be more requested for this product and for every request you are going to update same row, since to maintain the concurrency database has to lock that specific row and update for each request, which is definitely going to hit your database and application performance instead you can simply insert a new row.
The other possible solution is, you could use your existing invoice table as it will definitely have all product and user specific information and create a view to get frequently used product as I mentioned above.
Please note that, this is an another option to achieve what you are expecting. But, I would personally recommend to have history table instead.
The scenario
When the user creates a new invoice the product name field should be an autocomplete field which shows the most recently used products from the product catalogue.
your suggested solution
How can I store this "usage recency/frequency" in the database?
If it is a web application, don't store it in a Database in your server. Each user has different choices.
Store it in the user's browser as Cookie or Localstorage because it will improve the User Experience.
If you still want to store it in MySQL table,
Do the following
Create a column recency as said in question.
When each time the item used, increase the count by 1 as said in question.
Don't decrease it when other items get used.
To get the recent most used item,
query
SELECT * FROM table WHERE recence = (SELECT MAX(recence) FROM table);
Side note
Go for the database use only if you want to show the recent most used products without depending the user.
As you aren't certain on wich measure to choose, and it's rather user experience related problem, I advice you have a number of measures and provide a user an option to choose one he/she prefers. For example the set of available measures could include most popular product last week, last month, last 3 months, last year, overall total. For the sake of performance I'd prefer to store those statistics in a separate table which is refreshed by a scheduled job running every 3 hours for example.
I have one table in my access DB which contains a list of all devices that has been sold to our customer. We have only one customer and only one type of device. The table contains details like name, serial, warranty detail of device. Now we need to calculate the price for invoice purpose. The thing is that the price should be calculated depending on amount of sold devices and also we don't want to hard code the price instead we would like to use a separate table whit different category of prices and calculating the price based on this table, because of the prices changing frequently and so we should modify the price value only in one table.
We have 3 category of price : if customer bought 100 device then the unit price is 15$ else if 200 devices the unit price would be 10$ else if 300 then price for unit would be 5$. So based on these rules we will need to calculate the price.
So I'm looking for the right approach that would be for this problem.
This is a very open-ended question and is impossible to definitively answer without more information about the architecture of the database.
There are 3 different ways I usually perform a calculation inside my Access databases.
perform a calculation inside a query. For simple things.
perform a calculation inside a module function, that is called by a query. For complicated things.
perform a calculation inside a module vba subroutine, that is called by a button OnClick Event. For extremely complicated things.
You could do a cross join as long as you have a range wide enough to account for all possibilities (i.e. some ridiculous upper boundary like 9999999). Otherwise a subquery would work with the same WHERE clause:
SELECT Prices.Price
FROM Prices
WHERE (Prices.MinQuantity <= Invoice.Quantity) AND
(Prices.MaxQuantity >= Invoice.Quantity)
As Gustav and V-ball point out there are many ways to set this up depending on your needs.
I am currently in the process of rolling a custom order-processing system. My current structure is pretty standard, invoices, purchase orders, and items are all kept in separate tables. Items know which form(s) they are on by keeping track of the form's id, but forms don't know what items are in them (in the database). This was all well and good until I had a new requirement added to the mix: stocking orders.
The way a stocking order works is that sometimes a customer places an order for more units than what is in stock, so we want to place an order with our supplier for enough units to fulfill the order and replenish our stock. However, we often have to build these orders up as the minimums are pretty high, so one stocking order is usually comprised of several customer orders (sometimes for the same item) PLUS a few line items that are NOT connected to an order and are just for stocking purposes.
This presents a problem with my current architecture because I now need to keep track of what comes in from the stocking orders as often suppliers ship partial orders, where items have been allocated, and which incoming items are for stock.
My initial idea was to create a new database table that mostly mimics the items table, but is kind of like an aggregate (but not calculated) table that only keeps track of the items and their corresponding metadata (how many units received, how many for stock, etc) for only the stocking orders. I would have to keep the two tables in synch if something changed from one of them (like a quantity).
Is this overkill, and maybe there's a better way to do it? Database architecture is definitely not my forte, so I was hoping that someone could either tell me that this is an ok way to do things or that there is a better, more correct way to do it.
Thanks so much!
For what it's worth, what I'm using: VB, .NET 4.0, MySQL 5.0
Also, if you want clarification on anything, please ask! I will be closely monitoring this question.
Visit databaseanswers.com. Navigate to "free data models", and look for "Inventory Management". You should find some good examples.
you didnt mention them but you will need tables for:
SUPPLIERS, ORDERS, and INVENTORY
also, the base tables you mention 'knowing about' - these probably need associative style many to many tables which tell you things like which items are on which order, and which suppliers supply which items, lead times, costs etc.
it would be helpful to see your actual schema.
I use a single Documents table, with a DocType field. Client documents (Order, Invoice, ProForma, Delivery, Credit Notes) are mixed with Suppliers documents (PO, Reception).
This makes it quite easy to calculate Client backorders, Supplier backorders, etc...
I am just a bit unhappy because I have different tables for SUPPLIERS and CLIENTS, and therefore the DOCUMENTS table has both a SupplierId field and a ClientId field, which is a bit bad. If I had to redo it I might consider a single Companies table containing both Clients and Suppliers.
I use a PK (DocId) that's autoincrement, and a unique key (DocNum) that's like XYY00000, with
x= doc type
YY= year
00000 = increment.
This is because a doc can be saved but is only at validation time it receives a DocNum.
To track backorders (Supplier or Client), you will need to have a Grouping field in the DocDetails table, so that if you have an Order line 12345, you copy that Link field to every Detail line related to it (invoice, Delivery).
Hope I am not to confusing. The thing works well, after 3 years and over 50,000 docs.
This approach also implies that you will have a stock holding which is allocated for orders - without individual item tracking its a bit tricky to manage this. Consider, customer A orders
3 pink widgets
1 blue widget
But you only have 1 pink widget in stock - you order 3 pink widgets, and 1 blue.
Customer B orders
2 pink widgets
But you've still only got 1 in stock - you order another pink widget
3 pink widgets arrive from the first supplier order. What are you going to do? You can either reserve all of them for customer A's order and wait for the blue and red widget to arrive, or you can fulfill customer B's order.
What if the lead time on a pink widget is 3 days and for a blue widget it's 3 weeks? Do you ship partial orders to your customers? Do you have a limit on the amount of stock you will hold?
Just keeping a new table of backorders is not going to suffice.
This stuff gets scary complicated really quickly. You certainly need to spend a lot more time analysing the problem.