First of all, please excuse my perfectible English, I am French.
I'm coming to ask for some advice on a database design problem.
I have to design a calendar with events. Briefly, an event includes a start date/time, an end date/time, and a description.
The problem is that I have to consider repetitions; it is possible when creating an event to indicate that it starts next week and repeats itself until a specific date or not.
I see two possibilities of design:
create an events table with id, start_datetime, end_datetime and description fields.
When adding a new event, we generate as many rows as there are repeated events.
Advantages: we can make a SELECT * to retrieve all the events, without particular algorithm. In addition, it is possible to modify the descriptions of each occurrence of an event, insofar as they are considered as all different.
Disadvantage (MAJOR!): If we do not put an end date to have an infinite repetition, we will not memorize an infinity of events...
take inspiration from the method described on this thread, that is to say two tables:
events table
id description
1 Single event on 2018-11-23 08:00-09:30
2 Repeated event :
* every monday from 10:00 to 12:00 from Monday 2018-11-26
* every wednesday from 2018-11-28 from 14:00 to 14:45 until 2019-02-27
event_repetitions table
id event_id start_datetime end_datetime interval end_date
1 1 2018-11-23 08:00:00 2018-11-23 09:30:00 NULL NULL
2 2 2018-11-26 10:00:00 2018-11-26 12:00:00 604800 NULL
3 2 2018-11-28 14:00:00 2018-11-28 14:45:00 604800 2019-02-27
Note: interval is the number of seconds between each occurrence, 604800 = 24 (hours) * 3600 (seconds) * 7 (days).
Advantage: In the case of infinite repetitions (case of the event of id 2), we have very few lines to write and performances are increased.
Disadvantages: if we want to modify the description of the event (or other possible fields) for a specific occurrence and not another, we can not without creating a third table, event_descriptions for example:
id event_id user_id datetime description
1 2 1 2018-11-26 10:00:00 Comment from 2018-11-26
2 2 2 2018-12-03 10:00:00 Comment of the second occurrence, i.e. from 2018-12-03
Note: user_id is the logged-in user who wrote the comment.
Another disadvantage is that to get the list of events for a given day, week, or month, the selection query will be more complex and use joins. The event_descriptions table may, when there are hundreds of thousands of events, be very big.
My question is: what would you recommend as a more effective alternative? Maybe the second solution is good? What do you think?
In terms of technologies used, I intend to go on MySQL, the DBMS I know best. Nevertheless, if you think that using for example MongoDB is better in case of very large numbers of lines, do not hesitate to report it.
For information, my application is an API developed with API Platform, so Symfony 4 with Doctrine ORM.
Thank you in advance for your answers.
I allow myself to do a little up, hoping other answers.
Related
Is it possible to set start and stop time of cloudwatch event rules?
Use Case - I want to create a rule which triggers a lambda, but I want it to run at a specific date (every 2 minutes) and disable it at another date (these date interval can span across months).
As far as I know, when we create a rule (rate (2 minutes)), it starts running immediately. I can use this approach and in the lambda I can check if the current date is same as target date and proceed with lambda execution, and disable the rule when current date is greater than end date. Although, it might work but it does not seem the right approach since lambda would be unnecessarily executing until the target date.
Is there any way I can achieve the same thing without the hack?
Yes, you can set it to specific date only. For instance the following rule 0/2 0 28 9 ? 2020 would execute every 2 minutes on 28 Sep 2020 only:
Update
To span across months, I think you need separate rules. For example you could define two rules to span date range 28 Sep to finish 5 Oct: 0/2 0 28-31 9 ? 2020 and 0/2 0 1-5 10 ? 2020.
I'm am new to apex and I'm working on a food ordering application where customers are permitted to change their order details only up to 15 minutes after the order has been placed. How can I implement that ?
Create a validation on date item. Calculate difference between SYSDATE (i.e. "now") and order date. Subtracting two DATE datatype values results in number of days, so multiply it by 24 (to get hours) and by 60 (to get minutes). If that result is more than 15, raise an error.
To provide an alternative to Littlefoot's answer, timestamp arithmetic returns interval literals, if you use SYSTIMESTAMP instead your query could be:
systimestamp - order_date < interval '15' minute
or, even using SYSDATE something like:
order_date > sysdate - interval '15' minute
One note, the 15 minutes seems somewhat arbitrary (a magic number) it relies on the order not starting to be processed within that time limit. It feels more natural to say something like "you can change your order until the kitchen has started cooking it". There's no need for any magic numbers then and considerably less wastage (either of the customers time always waiting 15 minutes or of the kitchen's resources cooking something they may then have to discard).
I'm using the AWS Machine Learning regression to predict the waiting time in a line of a restaurant, in a specific weekday/time.
Today I have around 800k data.
Example Data:
restaurantID (rowID)weekDay (categorical)time (categorical)tablePeople (numeric)waitingTime (numeric - target)1 sun 21:29 2 23
2 fri 20:13 4 43
...
I have two questions:
1)
Should I use time as Categorical or Numeric?
It's better to split into two fields: minutes and seconds?
2)
I would like in the same model to get the predictions for all my restaurants.
Example:
I expected to send the rowID identifier and it returns different predictions, based on each restaurant data (ignoring others data).
I tried, but it's returning the same prediction for any rowID. Why?
Should I have a model for each restaurant?
There are several problems with the way you set-up your model
1) Time in the form you have it should never be categorical. Your model treats times 12:29 and 12:30 as two completely independent attributes. So it will never use facts it learn about 12:29 to predict what's going to happen at 12:30. In your case you either should set time to be numeric. Not sure if amazon ML can convert it for you automatically. If not just multiply hour by 60 and add minutes to it. Another interesting thing to do is to bucketize your time, by selecting which half hour or wider interval. You do it by dividing (h*60+m) by some number depending how many buckets you want. So to try 120 to get 2 hr intervals. Generally the more data you have the smaller intervals you can have. The key is to have a lot of samples in each bucket.
2) You should really think about removing restaurantID from your input data. Having it there will cause the model to over-fit on it. So it will not be able to make predictions about restaurant with id:5 based on the facts it learn from restaurants with id:3 or id:9. Having restaurant id there might be okay if you have a lot of data about each restaurant and you don't care about extrapolating your predictions to the restaurants that are not in the training set.
3) You never send restaurantID to predict data about it. The way it usually works you need to pick what are you trying to predict. In your case probably 'waitingTime' is most useful attribute. So you need to send weekDay, time and number of people and the model will output waiting time.
You should think what is relevant for the prediction to be accurate, and you should use your domain expertise to define the features/attributes you need to have in your data.
For example, time of the day, is not just a number. From my limited understanding in restaurant, I would drop the minutes, and only focus on the hours.
I would certainly create a model for each restaurant, as the popularity of the restaurant or the type of food it is serving is having an impact on the wait time. With Amazon ML it is easy to create many models as you can build the model using the SDK, and even schedule retraining of the models using AWS Lambda (that mean automatically).
I'm not sure what the feature called tablePeople means, but a general recommendation is to have as many as possible relevant features, to get better prediction. For example, month or season is probably important as well.
In contrast with some answers to this post, I think resturantID helps and it actually gives valuable information. If you have a significant amount of data per each restaurant then you can train a model per each restaurant and get a good accuracy, but if you don't have enough data then resturantID is very informative.
1) Just imagine what if you had only two columns in your dataset: restaurantID and waitingTime. Then wouldn't you think the restaurantID from the testing data helps you to find a rough waiting time? In the simplest implementation, your waiting time per each restaurantID would be the average of waitingTime. So definitely restaurantID is a valuable information. Now that you have more features in your dataset, you need to check if restaurantID is as effective as the other features or not.
2) If you decide to keep restaurantID then you must use it as a categorical string. It should be a non-parametric feature in your dataset and maybe that's why you did not get a proper result.
On the issue with day and time I agree with other answers and considering that you are building your model for the restaurant, hourly time may give a more accurate result.
I was having an issue with ms access 2000 in which I try to enter the same field in a query multiple times and it only displays the field once. As in if I entered the field with the number being (for example) 8150 multiple times, it would only display it once.
This image shows the query.
I've already checked everything on ms access 2000 to try to resolve this issue but I've come up with nothing suitable.
I know your data set is simplified, but looking at your data, inputs, etc, it appears your query is pulling from a single table and repeating results -- so there is no join consideration.
I think the issue is your DISTINCTROW in the query, which is removing all duplicate values.
If you remove the "DISTINCTROW," I believe it may give you what you are expecting. In other words, change this:
SELECT DISTINCTROW Ring.[Ring Number], Ring.[Mounting Weight]
FROM Ring
To this:
SELECT Ring.[Ring Number], Ring.[Mounting Weight]
FROM Ring
For what it's worth, there may also be some strategies to simplifying how this query is run in the future (less dependence on dialog box prompts), but I know you probably want to address the issue at a hand first, so let me know if this doesn't do it.
-- EDIT --
The removal of distinct still applies, but I suddenly see the problem. The query is depicting the logic as "OR" of multiple values. Therefore, repeating the value does not mean multiple rows, it just means you've repeated a true condition.
For example, if I have:
Fruit Count
------ ------
Apple 1
Pear 1
Kiwi 3
and I say select where Fruit is Apple or Apple or Apple or Apple, the query is still only going to list the first row. Once the "Or" condition matches true, short-circuiting kicks in, and no other conditions matter.
That does not sound like what you want.
Here's what I think you need to do:
Get rid of the prompts within the query
Load your options into a separate table -- the repetition can occur here
Change your query to perform an inner join on the new table
New table (named "Selection" for the sake of example):
Entry Ring Number Mounting Weight
----- ----------- ----------------
1 8105 you get the idea...
2 8110
3 8110
4 8110
5 8115
6 8130
7 8130
8 8130
9 8130
10 8150
New Query:
select
Ring.[Ring Number], Ring.[Mounting Weight]
from
Ring
Inner join Selection on Ring.[Ring Number] = Selection.[Ring Number]
This has the added advantage of allowing more (or less) than 10 records
I am looking for a solution which I can get that last 50 comments to the page's wall, or all comments in an hour to the page's wall and posts date wont matter, could be posted 2 years before but If gets a comment in an hour I need to get it. I don't want to get all posts and look one by one.
thank you for your effort
The first one is easy. Issue an API call to this endpoint:
/PAGE_NAME_OR_ID/feed?fields=comments.limit(50)
You will be restricted to the normal limits of feed, so the comments returned here will only be those made on the last 30 days or 50 posts, whichever is fewer.
If you want the last 50 comments, you'll need to use FQL.
SELECT time, text, text_tags, post_id FROM comment WHERE post_id IN
(SELECT post_id FROM stream WHERE source_id IN
(SELECT id FROM profile WHERE username="cocacola") LIMIT 100)
ORDER BY time DESC LIMIT 50
Keep in mind that Facebook's filtering algorithms operate after FQL. You may need to increase the LIMIT values substantially to be guaranteed get 50 results.