I'm trying to make a attendance management system for my college project.
I'm planning to createaone table for each month.
Each table will have
OCT(Roll_no int ,Name varchar, (dates...) bool)
Here dates will be from 1 to 30 and store boolean for present or absent.
Is this a good way to do it?
Is there a way to dynamically add a column for each day when the data was filled.
Also, how can I populate data according to current day.
Edit : I'm planning to make a UI which will have only two options (Present, absent) corresponding to each fetched roll no.
So, roll nos. and names are already going to be in the table. I'll just add status (present or absent) corresponding to each row in table for each date.
I would use Firebase. Make a node with a list of users. Then inside the uses make a attendance node with time-stamps for attended days. That way it's easier to parse. You also would leave room for the ability to bind data from other tables to users as well as the ability to add additional properties to each user.
Or do the SQL equivalent which would be make a table list of users (names and user properties) with associated keys (Primary keys in the user table with Foreign keys in the attendance table) that contained an attendance column that would hold an array of time-stamps representing attended days.
Either way, your UI would then only have to process timestamps and be able to parse through them with dates.
Though maybe add additional columns as years go so it wouldnt be so much of a bulk download.
Edit: In your case you'd want the SQL columns to be by month letting you select whichever month you'd like. For your UI, on injecting new attendance you'd simply add a column to the table if it does not already exist and then continue with the submission. On search/view you'd handle null results (say there were 2 months where no one attended at all. You'd catch any exceptions and continue with your display.)
Ex:
User
Primary Key - Name
1 - Joe
2 - Don
3 - Rob
Attendance
Foreign Key - Dates Array (Oct 2017)
1 - 1508198400, 1508284800, 1508371200
2 - 1508284800
3 - 1508198400, 1508371200
I'd agree with Gordon. This is not a good way to store the data. (It might be a good way to present it). If you have a table with the following columns, you will be able to store the data you want:
role_no (int)
Name (varchar)
Date (Date)
Present (bool)
If you want to then pull out the data for a particular month, you could just add this into your WHERE clause:
WHERE DATEPART(mm, [Date]) = 10 -- for October, or pass in a parameter
Dynamically adding columns is going to be a pain in the neck and is also quite messy
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 have a table "holidays" which represents people's holidays. It contains a FK to a person table, a from date column and a to date column. I want to add a constraint so that no person can have an over lapping holiday with themselves. So if Billy has a skiing holiday from 15th Jan - 20thJan, he can't have another vacation on the 18th Jan? But it's fine for him to do it on the 21st Jan?
Is this possible to do at database level via a constraint?
DB2 or Oracle can suffice?
Thanks
In DB2 you could use Temporal Tables and Time Travel Queries - check out the doumentation
Using Business Time with Business Period Temporal Tables will allow to define an index which enforces that periods do not overlap
CREATE UNIQUE INDEX I_vacation ON vacation (person, BUSINESS_TIME WITHOUT OVERLAPS)
Not directly. Constraints (at least in Oracle, I can't speak for other databases) work on one row at a time, they don't look at other rows - EXCEPT the UNIQUE constraint which looks across rows.
So - two solutions. One is, instead of storing ranges, to store one row per holiday DAY. (By the way, I believe what you call "holiday" is called "vacation", at least in America; "holiday" is reserved for common holidays, the same for all people, such as New Year or Christmas, etc.) In this arrangement, add a UNIQUE constraint on (person_id, vacation_day). Then re-work your input and reporting apps to translate from ranges to individual days, and respectively from individual days back to ranges.
The other solution, if you must store ranges, is to create a materialized view with refresh on commit (preferably fast refresh if the conditions permit), which shows person_id and vacation_day, one row per day - and put a UNIQUE constraint on the materialized view.
You can create a stored procedure wich take datestart and dateend of current row and use them parameter of this procedure. This procedure return 1 if exist in table a bad range and otherwise 0. Then you create your constraint check when this result procedure =0
I have a table that I created with a unique key and each other column representing one day of December 2014 (eg named D20141226 for data from 26/12/2014). So the table consists of 32 columns (key + 31 days). These daily columns are indicating that a customer had a transaction on that specific day or no transaction is indicated by a 0.
Now I want to execute the same query on a daily basis, producing a list of unique keys that had a transaction on that specific day. I used this easy script:
CREATE TABLE C01012015 AS
SELECT DISTINCT CALLING_ISDN AS A_PARTY
FROM CDRICC_012015
WHERE CALL_STA_TIME ::date = '2015-01-01'
Now my question is, how can I add the content of the new daily table to the existing table with the 31 days, making it effectively a table with 32 days of data (and then continue to do so on a daily basis to store up to 360 days of data)?
Please note that new customer are doing transactions every day hence there will unique keys in the daily table that aren't in the big table holding all the previous days.
It would be ideal if those new rows would automatically get a 0 instead of a NULL but I can work around it if it gets a NULL value (not sure how to make sure it gets a 0 instead).
I thought that a FULL OUTER JOIN would be the solution but that would mean that I have to list all variables in the select statement, which becomes quite large as I add one more column each day. Is there a more elegant way to do this?
Or is SQL just not suited to this and a programming language like eg R would be much better at this?
If you have the option to change your schema completely, you should unpivot your table so that your columns are something like CUSTOMER_ID INTEGER, D DATE, DID_TRANSACTION BOOLEAN. There's a post on the Enzee Community website that suggests using a user-defined table function (UDTF) to do this. If you change your schema in this way, a simple insert will work just fine and there will be no need to add columns dynamically.
If you can't change your schema that much but you're still able to add columns, you could add a column for every day of the year up front with a default value of FALSE (assuming it's a boolean column representing whether the customer had a transaction or not on that day). You probably want to script this.
ALTER TABLE table_with_daily_columns MODIFY COLUMN (D20140101 BOOLEAN DEFAULT FALSE);
ALTER TABLE table_with_daily_columns MODIFY COLUMN (D20140102 BOOLEAN DEFAULT FALSE);
-- etc
ALTER TABLE table_with_daily_columns ADD COLUMN (D20150101 BOOLEAN DEFAULT FALSE);
GROOM TABLE table_with_daily_columns;
When you alter a table like this, Netezza creates a new table and an internal view that does a UNION of the new table and the old. You need to GROOM the table to merge the tables back into a single one for improved performance.
If you really must keep one column per day, then you'll have to use the method you described to pivot the data from your daily transaction table. Set the default value for each of your columns to 0 or FALSE as described above, then:
INSERT INTO table_with_daily_columns
SELECT
cust_id,
TRUE as D20150101
FROM C01012015;
I have a fact table that has 4 date columns CreatedDate, LoginDate, ActiveDate and EngagedDate. I have a dimension table called DimDate whose primary key can be used as foreign key for all the 4 date columns in fact table. So the model looks like this.
But the problem is, when I want to do sub-filtering for the measures based on the date column. For ex: Count all users who were created in the last month and are engaged in this month. This is not possible to do with this design, coz when I filter the measure with create date , I can’t further filter for a different time window for engaged date. Since all the connected to same dimension, they are not working independently.
However, If I create a separate date dimension table for each of the columns, and join them like this then it works.
But this looks very cumbersome when I have 20 different date columns in fact table in real world scenario, where I have to create 20 different dimensions and connect them one by one. Is there any other way I can achieve my scenario w/o creating multiple duplicated date dimensions?
This concept is called a role-playing dimension. You don't have to add the table to the DSV or the actual dimensions one time for each date. Instead add the date once, then go to the dimension usage tab. Click Add Cube Dimension, and then choose the date dim. Right-click and rename it. Then update the relationship to use the correct fields.
There's a good article on MSSQLTips.com that covers this topic.
I have a database with a column that I want to query the amount of times it has changed over a period of time. For example, I have the username, user's level, and date. How do I query this database to see the number of times the user's level has changed over x amount of years?
(I've looked in other posts on stackoverflow, and they're telling me to use triggers. But in my situation, I want to query the database for the number of changes that has been made. If my question can't be answered, please tell me what other columns might I need to look into to figure this out. Am I supposed to use Lag for this? )
A database will not inherently capture this information for you. Two suggestions would be to either store your data as a time series so instead of updating the value you add a new row to a table as the new current value and expire the old value. The other alternative would be to just add a new column for tracking the number of updates to the column you care about. This could be done in code or in a trigger.
Have you ever heard of the LOG term ?
You have to create a new table, in wich you will store your wanted changes.
I can imagine this solution for the table:
id - int, primary key, auto increment
table - the table name where the info has been changed
table_id - the information unique id from the table where changes
have been made
year - integer
month - integer
day - integer
knowin this, you can count everything
In case you are already keeping track of the level history by adding a new row with a different level and date every time a user changes level:
SELECT username, COUNT(date) - 1 AS changes
FROM table_name
WHERE date >= '2011-01-01'
GROUP BY username
That will give you the number of changes since Jan 1, 2011. Note that I'm subtracting 1 from the COUNT. That's because a user with a single row on your table has never changed levels, that row represents the user's initial level.