LDF | CVPR2020 paper Label Decoupling Framework | Machine Learning library

For some reason, I must save the SQL Server files (.mdf and .ldf files) on the customer's computer. But I don't want anyone to attach my database and see my data, except my application.

Do we have any way to implement this requirement?

I am using R to calculate whole lake temperatures at every timestamp from the open water season.

I have loggers at various depths logging temperature every 10 minutes.

Each data frame for each lake has over 100k entries with over 10k different timestamps.

This is how I have solved this using a for loop. However, the code is extremely inefficient and it takes a couple of hours per lake depending how deep it is (deeper lakes have more loggers).

Example below resembles what my data look like. Running the script on the example goes fast, but takes hours on real data.

There should be a more effective way of doing this, with some apply-family function but idk how.

I have multiple files under the folder of "rawdata", after read them and assigned them as seperated dataset, i also want to rename them from "dataset 1 a.csv" to "dataset1".

I wrote the code that achieve the first goal,using the first loop read all files as a list, then use the second loop to unset the list: ldf. But I don't know where I should add the code to let R change all file's name at once? I tried to add str_replace_all (names(ldf)," ", "-") at different places, but all returned wrong outputs, and it cannot solve the issue of getting rid of ".csv". Thanks a lot~~

Here is my code:

I have a dataframe that contains a grouping variable. Trivial to create a list of dataframes using group_split but then I'd like to turn around and make a plot that groups these 5 at a time using facetting. For reproducibility I'll use mtcars

I created a backup of a SQL Server database named mydb. I need to restore it programmatically with a C# code.

The restore must create a new database named mydbnew. I'm doing it using the Microsoft.SqlServer.Management.Smo library.

The code is this:

I am a newbie in SQL Server, I have a task to move the whole SQL Server to another.

I am trying to estimate how much space I need in the new SQL Server.

I ran EXEC sp_spaceused

And the following came up:

When I look into the output, it seems that the Database is using ~122GB (reserved), but when looking in the total database size (mdf + ldf) it is ~1.8 TB.

Does that mean when I copy the Database from the existing SQL Server to a new one I will need ~1.8 TBs into the new?

I am thinking about creating a back-up and copy the back-up to the new Server. How does the back-up takes into consideration the unallocated space? Does the back gets closer to the reserved or the database_size? I understand that this is without taking into consideration the uncompressed in the back-up, which will improve the file size.

Thx for the help.

I have docker-compose.yml file with two services:

• a NodeJs API
• a microsoft mssql database

so I am creating an bidding app, this is the schema for the bidding model

I need to define an optimization objective function for Scipy SLSQP slover. The difficulties is that the number of independent variables in my objective function is not fixed. I was trying to use the following code: