I'm at a bit of a loss as to how design this particular database. It has the following features:
Expected 3 million+ rows corresponding to 'users';
Each 'user' has associated with them ~10,000 unique boolean states;
These states are sparse in nature, and additional states will be added in the future, and likely shouldn't be stored in an ordered list;
The states will be updated frequently, at a rate of about 20 in the span of 2 hours, every 24 hours, on average per active 'user';
The obvious design is to have a lookup table between the users and the states, but I'm concerned this will not be fast enough, when looking up states per user, with an expected 5 billion+ rows in the lookup table.
Any advice is appreciated.
I would create a relation between 2 tables
--------------------------------------------------
| ID | username |
--------------------------------------------------
| 1 | bl-ro |
--------------------------------------------------
| 2 | darkmukke |
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and then a relation for the bools
--------------------------------------------------
| ID | fk_user | bool |
--------------------------------------------------
| 1 | 1 | true |
--------------------------------------------------
| 2 | 1 | false |
--------------------------------------------------
Related
I'm trying to design a database that allows for filtering according to if a specific resource fills certain categories. I've gotten to the point where I can input data that seems to be how it should be filled out but I'm not sure how I should pull it out again.
The main resource table looks like this:
Table1 - resources
| resourceID | AutoNum |
| title | short text |
| author | short text |
| publish date | date |
| type | short text |
Table2 - Department Categories
| ID | AutoNum |
| 1 | Yes/No |
| 2 | Yes/No |
| fID| Number |
Table3 - Categories
| ID | AutoNum |
| cat | Yes/No |
| dog | Yes/No |
| bird | Yes/No |
| fID | Number |
I have built a form where you can fill in items to the resource ID, and at the same time check off the Yes/No boxes in tables 2 & 3.
I'm trying to use the primary key ID from table 1 and copy it into the table 2 & 3 with referential integrity to cascade deletes, updates. Which I think is the right way to do this.
Currently, I've learnt that I can implement a search function for the columns in table 1, this seems to work fine. However I am stuck with applying the relevant columns in table 2 and 3 as filters.
apply search>
[X] - Cats
Should only return records from table 1 where in table 3 the relevant column has a tick in the Yes/No box.
I hope I have explained this properly, very new to Access and databases so if you need clarity, don't mind offering.
I have to add a new table according to some new requirements, the model currently consists of two tables: DETAIL and SUMMARY.
The relation is that every detail has associated one summary, so now I need to add a new table called SUMMARY_ESP, which has the a FK ( SUMMARY) and two more columns, something like this:
ID | SUMMARY_ID | ESP_ID | PRIORITY_ESP | PTY_ID | PRIORITY_PTY
1 | 123 | 34 | 1 | 122 | 1
2 | 123 | 35 | 2 | 111 | 2
3 | 123 | 30 | 3 | null | null
4 | 1111 | 34 | 4 | null | null
Other tables info:
DETAIL TABLE
ID_DET | AMOUNT | DATE | ID_SUMMARY | EXTERNAL_ID
1 | 1000 | 14/05/2018 | 1111 | 4
2 | 2000 | 18/07/2016 | 1111 | 4
3 | 1200 | 11/07/2017 | 123 | 1
4 | 1300 | 21/09/2018 | 123 | 2
SUMMARY TABLE
ID_SUMMARY | PRIORITY| PROFILE | CLASS | AREA
123 | 1 | 1 | 5 | 3
1111 | 2 | 1 | 5 | 3
33 | 3 | 2 | 5 | 9
4 | 4 | 8 | 5 | 10
So according to this, SUMMARY_ID , ESP_ID and PTY_ID are unique, the thing is at some point to know the what is the ESP_ID of certain detail, but since the relation is with SUMMARY table, I have no idea which one was when it was added, so I was asked to create a new column to the DETAIL table called EXTERNAL_ID, so I can know what is the code from the SUMMARY_ESP.
So if the row is the first one, it can be either 24 or 122 in the new column according to some previous logic, but I'm worried about the implications this might have in the future, because somehow I might be duplicating information, also I would need to make some weird logic in order to get the priority depending on whether it's ESP_ID or PTY_ID.
The new table along with SUMMARY are somehow parameters table, their values do not change that often and only the PRIORITY column would change, DETAIL instead is more transactional, and it has insert and update everyday according to some business logic.
I was thinking of adding the ID of the new table as a FK to the DETAIL table, but at the end would be the same, because it'll be hard to maintain and update would be harder, also it's like a circular dependency, so I'm kind of stuck with this , so any kind of help would be really helpful, below the complete model, with the current idea.
Also I can't add those new columns to the table SUMMARY, because there could be more than one associated to the same code in that table and since it's the PK I cant add two rows with the same code.
The relation is that every detail has associated one summary
You need to represent that relationship in your database layout : if you have a 1-N relationship between SUMMARY and DETAIL, you want to create another column in DETAIL that holds the primary key of the SUMMARY record that it is related to.
With this relation in place, you can start from a DETAIL row, relate a row from SUMMARY and identifiy all SUMMARY_ESP records that are linked to it.
Now if you need to uniquely relate a DETAIL record to a SUMMARY_ESP record, then you want to either add a foreign key to SUMMARY_ESP in DETAIL, or the other way around (add a foreign key to DETAIL in SUMMARY_ESP), depending on the way your data flows.
Let's assume we have application with pages, posts and events. With each part of this application we want to have comments. Now let's take a look into tables for our DB.
1. One comment table, object and object_id as foreign key
Page/Post/Event has many comments, foreign key object, object_id
comments table
+-------------+-------------+-------------+-------------+
| id | object | object_id | text |
=========================================================
| 1 | Page | 1 | Comment 1 |
+-------------+-------------+-------------+-------------+
| 2 | Post | 1 | Comment 2 |
+-------------+-------------+-------------+-------------+
| 3 | Event | 1 | Comment 3 |
+-------------+-------------+-------------+-------------+
2. Multiple comments tables
Page (Post, Event) has many page comments, foreign key page_id
page_comments table
+-------------+-------------+-------------+
| id | page_id | text |
===========================================
| 1 | 1 | Comment 1 |
+-------------+-------------+-------------+
post_comments table
+-------------+-------------+-------------+
| id | post_id | text |
===========================================
| 1 | 1 | Comment 2 |
+-------------+-------------+-------------+
event_comments table
+-------------+-------------+-------------+
| id | event_id | text |
===========================================
| 1 | 1 | Comment 3 |
+-------------+-------------+-------------+
I have used specific example, but this can apply to any other 1:N tables or even with M:N (tags), but for simple showcase, this should be good.
We should discuss
Performance concerns
Design pros and cons
Initial thoughts
case 1 means less tables in DB, easier to read, reusable application code
case 1 is better when doing query on all comments (would have to use union at case 2)
case 2 is better in regards of normalization (3NF)
case 2 is easier to backup (dump) parts of the system, e.g. pages itself with their comments
case 2 should be better with performance because less rows => faster
I need to regularly import large (hundreds of thousands of lines) tsv files into multiple related SQL Server 2008 R2 tables.
The input file looks something like this (it's actually even more complex and the data is of a different nature, but what I have here is analogous):
January_1_Lunch.tsv
+-------+----------+-------------+---------+
| Diner | Beverage | Food | Dessert |
+-------+----------+-------------+---------+
| Nancy | coffee | salad_steak | pie |
| Joe | milk | soup_steak | cake |
| Pat | coffee | soup_tofu | pie |
+-------+----------+-------------+---------+
Notice that one column contains a character-delimited list that needs preprocessing to split it up.
The schema is highly normalized -- each record has multiple many-to-many foreign key relationships. Nothing too unusual here...
Meals
+----+-----------------+
| id | name |
+----+-----------------+
| 1 | January_1_Lunch |
+----+-----------------+
Beverages
+----+--------+
| id | name |
+----+--------+
| 1 | coffee |
| 2 | milk |
+----+--------+
Food
+----+-------+
| id | name |
+----+-------+
| 1 | salad |
| 2 | soup |
| 3 | steak |
| 4 | tofu |
+----+-------+
Desserts
+----+------+
| id | name |
+----+------+
| 1 | pie |
| 2 | cake |
+----+------+
Each input column is ultimately destined for a separate table.
This might seem an unnecessarily complex schema -- why not just have a single table that matches the input? But consider that a diner may come into the restaurant and order only a drink or a dessert, in which case there would be many null rows. Considering that this DB will ultimately store hundreds of millions of records, that seems like a poor use of storage. I also want to be able to generate reports for just beverages, just desserts, etc., and I figure those will perform much better with separate tables.
The orders are tracked in relationship tables like this:
BeverageOrders
+--------+---------+------------+
| mealId | dinerId | beverageId |
+--------+---------+------------+
| 1 | 1 | 1 |
| 1 | 2 | 2 |
| 1 | 3 | 1 |
+--------+---------+------------+
FoodOrders
+--------+---------+--------+
| mealId | dinerId | foodId |
+--------+---------+--------+
| 1 | 1 | 1 |
| 1 | 1 | 3 |
| 1 | 2 | 2 |
| 1 | 2 | 3 |
| 1 | 3 | 2 |
| 1 | 3 | 4 |
+--------+---------+--------+
DessertOrders
+--------+---------+-----------+
| mealId | dinerId | dessertId |
+--------+---------+-----------+
| 1 | 1 | 1 |
| 1 | 2 | 2 |
| 1 | 3 | 1 |
+--------+---------+-----------+
Note that there are more records for Food because the input contained those nasty little lists that were split into multiple records. This is another reason it helps to have separate tables.
So the question is, what's the most efficient way to get the data from the file into the schema you see above?
Approaches I've considered:
Parse the tsv file line-by-line, performing the inserts as I go. Whether using an ORM or not, this seems like a lot of trips to the database and would be very slow.
Parse the tsv file to data structures in memory, or multiple files on disk, that correspond to the schema. Then use SqlBulkCopy to import each one. While it's fewer transactions, it seems more expensive than simply performing lots of inserts, due to having to either cache a lot of data or perform many writes to disk.
Per How do I bulk insert two datatables that have an Identity relationship and Best practices for inserting/updating large amount of data in SQL Server 2008, import the tsv file into a staging table, then merge into the schema, using DB functions to do the preprocessing. This seems like the best option, but I'd think the validation and preprocessing could be done more efficiently in C# or really anything else.
Are there any other possibilities out there?
The schema is still under development so I can revise it if that ends up being the sticking point.
You can import you file in the table of the following structure: Diner, Beverage, Food, Dessert, ID (identity, primary key NOT CLUSTERED - for performance issues).
After this simply add the following columns: Dinner_ID, Beverage_ID, Dessert_ID and fill them according to your separate tables (it's simple to group each of the columns and to add the missing data to lookup tables as Beverages, Desserts, Meals and, after this, to fix the imported table with the IDs for existent and newly added records).
The situation with Food table is more complex because of ability to combine the foods, but the same trick can be used: you can also add the data to your lookup table and, among this, store the combinations of foods in the additional temp table (with the unique ID) and separation on the single dishes.
When the parcing will be finished, you will have 3 temp tables:
table with all your imported data and IDs for all text columns
table with distinct food lists (with IDs)
table with IDs of food per food combination
From the above tables you can perform the insertion of the parsed values to either structure as you want.
In this case only 1 insert (bulk) will be done to the DB from the code side. All other data manipulations will be performed in the DB.
for example i have table users, which have 3 fields:
id - login - password
---------------------
1 | john | *****
2 | jack | *****
3 | jane | *****
now i want that each user could have his own settings.
So, do i need to create three different tables, like
user_N_settings:
id | key | value
-------------------------
1 | save_data | True
or i should create one big table for all users instead?
users_settings:
id | key | value | user_id
---------------------------------------------
1 | save_data | True | 2
2 | some_opt | False | 3
One table for all users. A table per user would be very wrong.
One table. If all the setting values are of the same type then it may make sense to create one row per setting. If the attributes are all very different then create one column per setting.