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Embedded resources - resx - performance - C#

Embedded resources is only used to compile a file as binary part?
Is it a good idea to use embedded resources for performances reasons?
This question concerns
XML files saved as embedded resources
Resx files (strings)
In the two cases, is there same performance benefit: some caching strategy, or some thing like that (since it's could be managed like sources code/assemblies).
For exemple instead of the resx, I can use a hash-table (lately created). In my case that hashtable could be so big to stay forever in memory. So Resx is it a help with some cache strategy ?
I have the same problem for a tree object. Using it from an XML embedded-file couldn't help me, or should I implement all the cache-strategy?
THINKS

The embedded resource feature was added primarily because of performance reasons. There is no way to do it faster on a demand-page virtual memory operating system like Windows. You get the full benefit of a memory-mapped file to read the resource content.
That is not massively better than reading a separate file but you don't pay for having to find the file. Which is usually the costly operation on small resources and heavily affects the cold-start time of an app. Not having a large blob of files to deploy is very much a practical advantage.
They do occupy memory of course but it is virtual memory. Just numbers to the processor, one each for every 4096 bytes. Also the cheap kind of virtual memory, it is backed by the executable file instead of the paging file. You don't actually pay and start to use RAM until you access the resource in your program. That RAM will usually be released again soon unless you repeatedly use the resource. It does set an upper limit on the amount of resource data you can embed, peters out at 2 gigabytes.
That they start as an XML resource only matters at build time, the Resgen.exe tool turns it into a binary blob before it is embedded in the executable file. The advantage of XML is that it plays nice with the IDE and makes it easy to recover the original resource after you lost track of the original art work.

how to copy big amount of small files in high performance?

In my case, I call file.copy() to copy those small files (3KB) from different directories to different directories each. I put the source paths in a list<string>.
What can I do to improve the performance of copying?
Should I use multi-thread? On just the sequential way?

I'm not sure how you could force performance into the issue as copying files is handled by Windows and you will be pretty much limited by the hardware that you have, e.g., the type of storage you are using (disk or SSD), the type of connection you have (LAN/USB 2.0 or 3.0/etc).
That being said an asynchronous file copy would probably work best for what you want to do whatever the scenario is. The best resource for that would be the Asynchronous File I/O reference on MSDN.

"C# how to copy **big amount of small files in high performance**?".
There is not much code in your question, so i am giving you a direction(help url) towards solution..
I would recommended using Zipping as an option. Advantages i feel..
Compression of the size.
Files are reduced to single zip file.
Because of above n/w copying get faster...
NOTE : For .Net 4.5 you can go ahead and use the ZipFile, prior to that you might need to use GZip or Deflate compression algorithms
MSDN url - http://msdn.microsoft.com/en-us/library/ms404280(v=vs.110).aspx

There may be some advantage to reading them into memory in large chunks (say, 1GB at a time) and then writing them out. This could allow them to be written to disk sequentially without having to move the disk heads back and forth so much.
Also consider using the more flexible CopyFileEx API as described here. It allows you to specify NoBuffering to avoid filling up your cache with files you don't care about, plus offers asynchronous modes, cancellation, and progress reporting.

I think You should copy file Asynchronously. Please find the below link that will help you to make an Asynchronous call for copying file.
Asynchronous Programming Techniques

how to improve a large number of smaller files read and write speed or performance

Yesterday,I asked the question at here:how do disable disk cache in c# invoke win32 CreateFile api with FILE_FLAG_NO_BUFFERING.
In my performance test show(write and read test,1000 files and total size 220M),the FILE_FLAG_NO_BUFFERING can't help me improve performance and lower than .net default disk cache,since i try change FILE_FLAG_NO_BUFFERING to FILE_FLAG_SEQUENTIAL_SCAN can to reach the .net default disk cache and faster little.
before,i try use mongodb's gridfs feature replace the windows file system，not good(and i don't need to use distributed feature,just taste).
in my Product,the server can get a lot of the smaller files(60-100k) on per seconds through tcp/ip,then need save it to the disk,and third service read these files once(just read once and process).if i use asynchronous I/O whether can help me,whether can get best speed and best low cpu cycle?. someone can give me suggestion?or i can still use FileStream class?
update 1
the memory mapped file whether can to achieve my demand.that all files write to one big file or more and read from it?

If your PC is taking 5-10 seconds to write a 100kB file to disk, then you either have the world's oldest, slowest PC, or your code is doing something very inefficient.
Turning off disk caching will probably make things worse rather than better. With a disk cache in place, your writes will be fast, and Windows will do the slow part of flushing the data to disk later. Indeed, increasing I/O buffering usually results in significantly improved I/O in general.
You definitely want to use asynchronous writes - that means your server starts the data writing, and then goes back to responding to its clients while the OS deals with writing the data to disk in the background.
There shouldn't be any need to queue the writes (as the OS will already be doing that if disc caching is enabled), but that is something you could try if all else fails - it could potentially help by writing only one file at a time to minimise the need for disk seeks..
Generally for I/O, using larger buffers helps to increase your throughput. For example instead of writing each individual byte to the file in a loop, write a buffer-ful of data (ideally the entire file, for the sizes you mentioned) in one Write operation. This will minimise the overhead (instead of calling a write function for every byte, you call a function once for the entire file). I suspect you may be doing something like this, as it's the only way I know to reduce performance to the levels you've suggested you are getting.
Memory-mapped files will not help you. They're really best for accessing the contents of huge files.

One of buggest and significant improvements, in your case, can be, imo, process the filles without saving them to a disk and after, if you really need to store them, push them on Queue and provess it in another thread, by saving them on disk. By doing this you will immidiately get processed data you need, without losing time to save a data on disk, but also will have a file on disk after, without losing computational power of your file processor.

Logic in Disk Defragmantation & Disk Check

What is the logic behind disk defragmentation and Disk Check in Windows? Can I do it using C# coding?

For completeness sake, here's a C# API wrapper for defragmentation:
http://blogs.msdn.com/jeffrey_wall/archive/2004/09/13/229137.aspx
Defragmentation with these APIs is (supposed to be) very safe nowadays. You shouldn't be able to corrupt the file system even if you wanted to.
Commercial defragmentation programs use the same APIs.

Look at Defragmenting Files at msdn for possible API helpers.
You should carefully think about using C# for this task, as it may introduce some undesired overhead for marshaling into native Win32.

If you don't know the logic for defragmentation, and if you didn't write the file system yourself so you can't authoritatively check it for errors, why not just start new processes running 'defrag' and 'chkdsk'?

Mark Russinovich wrote an article Inside Windows NT Disk Defragmentation a while ago which gives in-depth details. If you really want to do this I would really advise you to use the built-in facilities for defragmenting. More so, on recent OSes I have never seen a need as a user to even care about defragmenting; it will be done automatically on a schedule and the NTFS folks at MS are definitely smarter at that stuff than you (sorry, but they do this for some time now, you don't).

Despite its importance, the file system is no more than a data structure that maps file names into lists of disk blocks. And keeps track of meta-information such as the actual length of the file and special files that keep lists of files (e.g., directories). A disk checker verifies that the data structure is consistent. That is, every disk block must either be free for allocation to a file or belong to a single file. It can also check for certain cases where a set of disk blocks appears to be a file that should be in a directory but is not for some reason.
Defragmentation is about looking at the lists of disk blocks assigned to each file. Files will generally load faster if they use a contiguous set of blocks rather than ones scattered all over the disk. And generally the entire file system will perform best if all the disk blocks in use confine themselves to a single congtiguous range of the disk. Thus the trick is moving disk blocks around safely to achieve this end while not destroying the file system.
The major difficulty here is running these application while a disk is in use. It is possible but one has to be very, very, very careful not to make some kind of obvious or extremely subtle error and destroy most or all of the files. It is easier to work on a file system offline.
The other difficulty is dealing with the complexities of the file system. For example, you'd be much better off building something that supports FAT32 rather than NTFS because the former is a much, much simpler file system.
As long as you have low-level block access and some sensible way for dealing with concurrency problems (best handled by working on the file system when it is not in use) you can do this in C#, perl or any language you like.
BUT BE VERY CAREFUL. Early versions of the program will destroy entire file systems. Later versions will do so but only under obscure circumstances. And users get extremely angry and litigious if you destroy their data.

What's the best way to read and parse a large text file over the network?

I have a problem which requires me to parse several log files from a remote machine.
There are a few complications:
1) The file may be in use
2) The files can be quite large (100mb+)
3) Each entry may be multi-line
To solve the in-use issue, I need to copy it first. I'm currently copying it directly from the remote machine to the local machine, and parsing it there. That leads to issue 2. Since the files are quite large copying it locally can take quite a while.
To enhance parsing time, I'd like to make the parser multi-threaded, but that makes dealing with multi-lined entries a bit trickier.
The two main issues are:
1) How do i speed up the file transfer (Compression?, Is transferring locally even neccessary?, Can I read an in use file some other way?)
2) How do i deal with multi-line entries when splitting up the lines among threads?
UPDATE: The reason I didnt do the obvious parse on the server reason is that I want to have as little cpu impact as possible. I don't want to affect the performance of the system im testing.

If you are reading a sequential file you want to read it in line by line over the network. You need a transfer method capable of streaming. You'll need to review your IO streaming technology to figure this out.
Large IO operations like this won't benefit much by multithreading since you can probably process the items as fast as you can read them over the network.
Your other great option is to put the log parser on the server, and download the results.

The better option, from the perspective of performance, is going to be to perform your parsing at the remote server. Apart from exceptional circumstances the speed of your network is always going to be the bottleneck, so limiting the amount of data that you send over your network is going to greatly improve performance.
This is one of the reasons that so many databases use stored procedures that are run at the server end.
Improvements in parsing speed (if any) through the use of multithreading are going to be swamped by the comparative speed of your network transfer.
If you're committed to transferring your files before parsing them, an option that you could consider is the use of on-the-fly compression while doing your file transfer.
There are, for example, sftp servers available that will perform compression on the fly.
At the local end you could use something like libcurl to do the client side of the transfer, which also supports on-the-fly decompression.

The easiest way considering you are already copying the file would be to compress it before copying, and decompress once copying is complete. You will get huge gains compressing text files because zip algorithms generally work very well on them. Also your existing parsing logic could be kept intact rather than having to hook it up to a remote network text reader.
The disadvantage of this method is that you won't be able to get line by line updates very efficiently, which are a good thing to have for a log parser.

I guess it depends on how "remote" it is. 100MB on a 100Mb LAN would be about 8 secs...up it to gigabit, and you'd have it in around 1 second. $50 * 2 for the cards, and $100 for a switch would be a very cheap upgrade you could do.
But, assuming it's further away than that, you should be able to open it with just read mode (as you're reading it when you're copying it). SMB/CIFS supports file block reading, so you should be streaming the file at that point (of course, you didn't actually say how you were accessing the file - I'm just assuming SMB).
Multithreading won't help, as you'll be disk or network bound anyway.

Use compression for transfer.
If your parsing is really slowing you down, and you have multiple processors, you can break the parsing job up, you just have to do it in a smart way -- have a deterministic algorithm for which workers are responsible for dealing with incomplete records. Assuming you can determine that a line is part of a middle of a record, for example, you could break the file into N/M segments, each responsible for M lines; when one of the jobs determines that its record is not finished, it just has to read on until it reaches the end of the record. When one of the jobs determines that it's reading a record for which it doesn't have a beginning, it should skip the record.

If you can copy the file, you can read it. So there's no need to copy it in the first place.
EDIT: use the FileStream class to have more control over the access and sharing modes.
new FileStream("logfile", FileMode.Open, FileAccess.Read, FileShare.ReadWrite)
should do the trick.

I've used SharpZipLib to compress large files before transferring them over the Internet. So that's one option.
Another idea for 1) would be to create an assembly that runs on the remote machine and does the parsing there. You could access the assembly from the local machine using .NET remoting. The remote assembly would need to be a Windows service or be hosted in IIS. That would allow you to keep your copies of the log files on the same machine, and in theory it would take less time to process them.

i think using compression (deflate/gzip) would help

The given answer do not satisfy me and maybe my answer will help others to not think it is super complicated or multithreading wouldn't benefit in such a scenario. Maybe it will not make the transfer faster but depending on the complexity of your parsing it may make the parsing/or analysis of the parsed data faster.
It really depends upon the details of your parsing. What kind of information do you need to get from the log files? Are these information like statistics or are they dependent on multiple log message?
You have several options:
parse multiple files at the same would be the easiest I guess, you have the file as context and can create one thread per file
another option as mentioned before is use compression for the network communication
you could also use a helper that splits the log file into lines that belong together as a first step and then with multiple threads process these blocks of lines; the parsing of this depend lines should be quite easy and fast.
Very important in such a scenario is to measure were your actual bottleneck is. If your bottleneck is the network you wont benefit of optimizing the parser too much. If your parser creates a lot of objects of the same kind you could use the ObjectPool pattern and create objects with multiple threads. Try to process the input without allocating too much new strings. Often parsers are written by using a lot of string.Split and so forth, that is not really as fast as it could be. You could navigate the Stream by checking the coming values without reading the complete string and splitting it again but directly fill the objects you will need after parsing is done.
Optimization is almost always possible, the question is how much you get out for how much input and how critical your scenario is.