c ++ – What is the efficient way to write large data in a .csv file?

I am trying to write the big data in a csv file and the number of rows I am dealing with is in millions.

My code is generating the rows in the form of a double matrix. The code takes a long time to write data to the file (twice as much as writing the same number of records in the database with a massive 10k insert on the same machine).

I tried to buffer rows 10000 and 100000 in the std :: string.

m_Csvfile.open("Fact.csv", std::ios_base::out | std::ios_base::app);
void class::PrepareRow()
{
    for (int i = 1; i < m_nColumnCount; i++)
    {
        if (arrayOfRowVals(i) != NULL_NUMBER)
        {
            char buffer(50) = {};
            sprintf(buffer, "%9.7lf", arrayOfRowVals(i));
            strBulkcsvString.append(buffer); // strBulkcsvString is std::string
        }

        if (i < m_nColumnCount)
            strBulkcsvString.append(",");
    }
    strBulkcsvString.append("n");
    m_rowcount++;

    if (m_rowcount == 10000)
    {
        m_rowcount = 0;
        strBulkcsvString.clear();
        m_Csvfile << strBulkcsvString.c_str();
        strBulkcsvString.clear();
        m_rowcount = 0;
    }
}

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sql server: the clustered index occupies a large amount of space

I have been working on indexing a database that deals with historical data and recently found a problem with a clustered index that surprised me.

The database is SQL Server 2018. The table itself deals with the account information and is essentially a fact table, it is completed with around 200k records per day and has 200 columns. It is currently in 68 thousand records, and before the index occupied about 120 GB of space.

Because it is a historical table about the account information, and we do not have UUID configured (which would be a great effort that my boss told me not to devote my time to this database), I created the primary key + clustered index in the Date field and account number with an extract equivalent to:

ALTER TABLE AcctHistory 
ADD CONSTRAINT PK_AcctHistory PRIMARY KEY CLUSTERED (Date, Account_Number)

The Date field is a Date and time field (This is a DEV environment that I did not configure but I am now building. I only know that I plan to update it to a date soon, but I provide the type if it is relevant.), The Account_Number field It is a bigint.

After executing this declaration, according to the SSMS disk space report per table, the amount of space consumed by the table skyrocketed up to 480 GB, 4 times what it took before the index.

I know that indexes take up space, but I've never heard of anything like that. Is this normal or is it indicative of a problem that I can solve to save space?

Large touch screen and UX / UI kiosk

I am looking for some entries such as research, articles and things related to large touch screens / UX / UI kiosks

Thank you

java – Deal with large base code quickly in agile

In my current company, the project I work on is coded in Java, at least for the systems / backend part. Every time I am assigned a task related to Java code, it takes me hours or even days to solve everything and apply my solutions. The reasons are:

1] Very large Java EE code base

2] A lot of abstraction

3] I get lost in discovering all abstractions, such as methods, then I often go around a hole where I think of something else and forget my original solution, etc.

My work environment is agile and I am expected to deliver quickly, but as a fairly new member of the company and a huge code base that was created before joining, it is difficult for me to meet the "agile" time.

How are we supposed to deal with such a large code base where almost all lines / functions lead to another abstraction and within them there are even more abstractions in a timely manner?

Edit: I know I can ask my classmates, but at the same time I don't want to bother them constantly, since problem solving is part of my job.

Controls – How large should an analog stick be in a mobile game?

I am developing a mobile game, for fun, and I add an analog stick to control the main character. It looks something like this:

enter the description of the image here

I hope to get some advice on the right size and position.

Key Considerations:

  1. When the user moves the analog stick, the central part moves outside its boundary circle, which means that the larger the stick, the more it could run off the screen.

enter the description of the image here

  1. If the user's finger leaves the screen by mistake, the analog stick will return to the center and stop the movement of the players; This could be crucial in a tense part of the game.

  2. The larger the analog stick, the more control the user has, but also more space the stick occupies.

  3. For older devices we have much less space in pixels. An analog memory of 100 pixels suddenly occupies more than a third of the screen once we consider the padding.

Ideally, there will be an additional analog stick in the lower right corner, but this could be more an action button to interact with an element, object, etc.

I know that touch screen devices are not as tactile as a real controller, but that is why I want to make sure that my controls feel as natural as possible. Mainly looking at the size of the analog stick (diameter) and the position in the lower left corner.

Probability theory: Efficient algorithm to simulate cards from a large deck of cards?

In spill-type card games, the dealer starts by distributing a shuffled deck to the players (if there is N players card i goes to the player i mod N) If the number of each type of card is known, is there a way to simulate the distribution of the cards and get a count of each type of card each player has?

For example, if there are N = 3 players, and there are 5 types of cards and the count of each card is (3000000000, 3000000000, 3000000000, 3000000000, 2), one possible way out is (1000000000, 1000000000, 1000000000, 1000000000, 1), (1000000000, 1000000000, 1000000000, 1000000000, 1), (1000000000, 1000000000, 1000000000, 1000000000, 0), which represents the number of cards of each type that each player has.

A naive algorithm is to create a wide variety of all cards, mix them with Fisher-Yates and then go through each item and increase the card count for the current player and set the current player for the next player. . For the previous example, this creates an array of size 12000000002 and requires many iterations, but there are only 5 types of cards and 3 players (the output is size 15).

Is there a more efficient algorithm? He would have to generate the output with the same probability as the naive algorithm would.