Read large txt file multithreaded?

Question

I have large txt file with 100000 lines. I need to start n-count of threads and give every thread unique line from this file.

What is the best way to do this? I thin

Answer 1

If you want to limit the number of threads to n, the easiest way is to use AsParallel() along with WithDegreeOfParallelism(n) to limit the thread count:

string filename = "C:\\TEST\\TEST.DATA";
int n = 5;

foreach (var line in File.ReadLines(filename).AsParallel().WithDegreeOfParallelism(n))
{
    // Process line.
}

Answer 2

You can use the File.ReadLines Method to read the file line-by-line without loading the whole file into memory at once, and the Parallel.ForEach Method to process the lines in multiple threads in parallel:

Parallel.ForEach(File.ReadLines("file.txt"), (line, _, lineNumber) =>
{
    // your code here
});

Answer 3

As @dtb mentioned above, the fastest way to read a file and then process the individual lines in a file is to: 1) do a File.ReadAllLines() into an array 2) Use a Parallel.For loop to iterate over the array.

You can read more performance benchmarks here.

The basic gist of the code you would have to write is:

string[] AllLines = File.ReadAllLines(fileName);
Parallel.For(0, AllLines.Length, x =>
{
    DoStuff(AllLines[x]);
    //whatever you need to do
});

With the introduction of bigger array sizes in .Net4, as long as you have plenty of memory, this shouldn't be an issue.

Answer 4

Read the file on one thread, adding its lines to a blocking queue. Start N tasks reading from that queue. Set max size of the queue to prevent out of memory errors.

Answer 5

After performing my own benchmarks for loading 61,277,203 lines into memory and shoving values into a Dictionary / ConcurrentDictionary() the results seem to support @dtb's answer above that using the following approach is the fastest:

Parallel.ForEach(File.ReadLines(catalogPath), line =>
{

}); 

My tests also showed the following:

1. File.ReadAllLines() and File.ReadAllLines().AsParallel() appear to run at almost exactly the same speed on a file of this size. Looking at my CPU activity, it appears they both seem to use two out of my 8 cores?
2. Reading all the data first using File.ReadAllLines() appears to be much slower than using File.ReadLines() in a Parallel.ForEach() loop.
3. I also tried a producer / consumer or MapReduce style pattern where one thread was used to read the data and a second thread was used to process it. This also did not seem to outperform the simple pattern above.

I have included an example of this pattern for reference, since it is not included on this page:

var inputLines = new BlockingCollection<string>();
ConcurrentDictionary<int, int> catalog = new ConcurrentDictionary<int, int>();

var readLines = Task.Factory.StartNew(() =>
{
    foreach (var line in File.ReadLines(catalogPath)) 
        inputLines.Add(line);

        inputLines.CompleteAdding(); 
});

var processLines = Task.Factory.StartNew(() =>
{
    Parallel.ForEach(inputLines.GetConsumingEnumerable(), line =>
    {
        string[] lineFields = line.Split('\t');
        int genomicId = int.Parse(lineFields[3]);
        int taxId = int.Parse(lineFields[0]);
        catalog.TryAdd(genomicId, taxId);   
    });
});

Task.WaitAll(readLines, processLines);

Here are my benchmarks:

I suspect that under certain processing conditions, the producer / consumer pattern might outperform the simple Parallel.ForEach(File.ReadLines()) pattern. However, it did not in this situation.

Answer 6

Something like:

public class ParallelReadExample
{
    public static IEnumerable LineGenerator(StreamReader sr)
    {
        while ((line = sr.ReadLine()) != null)
        {
            yield return line;
        }
    }

    static void Main()
    {
        // Display powers of 2 up to the exponent 8:
        StreamReader sr = new StreamReader("yourfile.txt")

        Parallel.ForEach(LineGenerator(sr), currentLine =>
            {
                // Do your thing with currentLine here...
            } //close lambda expression
        );

        sr.Close();
    }
}

Think it would work. (No C# compiler/IDE here)