Situation:
I am scanning a directory using NtQueryDirectoryFile(..., FileBothDirectoryInformation, ...). In addition to data returned by this call I need security data (typically returned by GetKernelObjectSecurity) and list of alternate streams (NtQueryInformationFile(..., FileStreamInformation)).
Problem:
To retrieve security and alternate stream info I need to open (and close) each file. In my tests it slows down the operation by factor of 3. Adding GetKernelObjectSecurity and NtQueryInformationFile slows it down by factor of 4 (making it 12x).
Question:
Is there a better/faster way to get this information (by either opening files faster or avoiding file open altogether)?
Ideas:
If target file system is local I could access it directly and (knowing NTFS/FAT/etc details extract info from raw data). But it isn't going to work for remote file systems.
Custom SMB client is the answer, it seems. Skipping Windows/NT API layer opens all doors.
Related
I'm creating my custom binary file extension.
I use the RIFF standard for encoding data. And it seems to work pretty well.
But there are some additional requirements:
Binary files could be large up to 500 MB.
Real-time saving data into the binary file in intervals when data on the application has changed.
Application could run on the browser.
The problem I face is when I want to save data it needs to read everything from memory and rewrite the whole binary file.
This won't be a problem when data is small. But when it's getting larger, the Real-time saving feature seems to be unscalable.
So main requirement of this binary file could be:
Able to partially read the binary file (Cause file is huge)
Able to partially write changed data into the file without rewriting the whole file.
Streaming protocol like .m3u8 is not an option, We can't split it into chunks and point it using separate URLs.
Any guidance on how to design a binary file system that scales in this scenario?
There is an answer from a random user that has been deleted here.
It seems great to me.
You can claim your answer back and I'll delete this one.
He said:
If we design the file to be support addition then we able to add whatever data we want without needing to rewrite the whole file.
This idea gives me a very great starting point.
So I can append more and more changes at the end of the file.
Then obsolete old chunks of data in the middle of the file.
I can then reuse these obsolete data slots later if I want to.
The downside is that I need to clean up the obsolete slot when I have a chance to rewrite the whole file.
On the underlying server filesystem, MinIO seems to store the content of an uploaded file (e.g. X) in a file called xl.meta in a directory bearing the original file name (e.g. X/xl.meta).
However, the file xl.meta is encoded. How can I access the original file content on the server file system itself (i.e. see the text inside a plain text file or being able to play a sound file with a respective application)?
It would not be possible since the object you are seeing on the backend fs is not the actual object, it is only the erasure coded part(s) that is split across all the disks in a given erasure set. So, you could do it if you were just using fs mode (single node, single disk) but in erasure coded environment you will need to have quorum to be able to download the object, and that via an S3 supported method and not directly from the backend. Technically not quorum, rather n/2 if you just want to read the object, but as a rule you should avoid doing anything in the backend fs.
If you happen to want to just see the contents of xl.meta, and not recover the file itself, you can use this something like mc support inspect myminio/test/syslog/xl.meta --export=json (or you can build a binary from https://github.com/minio/minio/tree/master/docs/debugging/xl-meta but using mc is probably easier).
I would like to know if anybody has any experience writing data directly to disk without a file system - in a similar way that data would be written to a magnetic tape. In particular I would like to know if/how data is written in blocks, and whether a certain blocksize needs to be specified (like it does when writing to tape), and if there is a disk equivalent of a tape file mark, which separates the archives written to a tape.
We are creating a digital archive for over 1 PB of data, and we want redundancy built in to the system in as many levels as possible (by storing multiple copies using different storage media, and storage formats). Our current system works with tapes, and we have a mechanism for storing the block offset of each archive on each tape so we can restore it.
We'd like to extend the system to work with disk volumes without having to change much of the logic. Another advantage of not having a file system is that the solution would be portable across Operating Systems.
Note that the ability to browse the files on disk is not important in this application, since we are considering this for an archival copy of data which is not accessed independently. Also note that we would already have an index of the files stored in the application database, which we also write to the end of the tape/disk when it is almost full.
EDIT 27/05/2020: It seems that accessing the disk device as a raw/character device is what I'm looking for.
I want to be able to (programmatically) move (or copy and truncate) a file that is constantly in use and being written to. This would cause the file being written to would never be too big.
Is this possible? Either Windows or Linux is fine.
To be specific what I'm trying to do is log video with FFMPEG and create hour long videos.
It is possible in both Windows and Linux, but it would take cooperation between the applications involved. If the application that is writing the new data to the file is not aware of what the other application is doing, it probably would not work (well ... there is some possibility ... back to that in a moment).
In general, to get this to work, you would have to open the file shared. For example, if using the Windows API CreateFile, both applications would likely need to specify FILE_SHARE_READ and FILE_SHARE_WRITE. This would allow both (multiple) applications to read and write the file "concurrently".
Beyond sharing the file, though, it would also be necessary to coordinate the operations between the applications. You would need to use some kind of locking mechanism (either by locking some part of the file or some shared mutex/semaphore). Note that if you use file locking, you could lock some known offset in the file to act as a "semaphore" (it can even be a byte value beyond the physical end of the file). If one application were appending to the file at the same exact time that the other application were truncating it, then it would lead to unpredictable results.
Back to the comment about both applications needing to be aware of each other ... It is possible that if both applications opened the file exclusively and kept retrying the operations until they succeeded, then perform the operation, then close the file, it would essentially allow them to work without "knowledge" of each other. However, that would probably not work very well and not be very efficient.
Having said all that, you might want to consider alternatives for efficiency reasons. For example, if it were possible to have the writing application write to new files periodically, it might be more efficient than having to "move" the data constantly out of one file to another. Also, if you needed to maintain some portion of the file (e.g., move out the first 100 MB to another file and then move the second 100 MB to the beginning) that could be a fairly expensive operation as well.
logrotate would be a good option is linux, comes stock on just about any distro. I'm sure there's a similar windows service out there somewhere
Let’s pretend I have a network of 10,000 machines. I want to use all those machines to crawl the web as fast as possible. All pages should be downloaded only once. In addition there must be no single point of failure and we must minimize the number of communication required between machines. How would you accomplish this?
Is there anything more efficient than using consistent hashing to distribute the load across all machines and minimize communication between them?
Use a distributed Map Reduction system like Hadoop to divide the workspace.
If you want to be clever, or doing this in an academic context then try a Nonlinear dimension reduction.
Simplest implementation would probably be to use a hashing function on the name space key e.g. the domain name or URL. Use a Chord to assign each machine a subset of the hash values to process.
One Idea would be to use work queues (directories or DB), assuming you will be working out storage such that it meets your criteria for redundancy.
\retrieve
\retrieve\server1
\retrieve\server...
\retrieve\server10000
\in-process
\complete
1.) All pages to be seeds will be hashed and be placed in the queue using the hash as a file root.
2.) Before putting in the queue you check the complete and in-process queues to make sure you don't re-queue
3.) Each server retrieves a random batch (1-N) files from the retrieve queue and attempts to move it to the private queue
4.) Files that fail the rename process are assumed to have been “claimed” by another process
5.) Files that can be moved are to be processed put a marker in in-process directory to prevent re-queuing.
6.) Download the file and place it into the \Complete queue
7.) Clean file out of the in-process and server directories
8.) Every 1,000 runs check the oldest 10 in-process files by trying to move them from their server queues back into the general retrieve queue. This will help if a server hangs and also should load balance slow servers.
For the Retrieve, in-process and complete servers most file systems hate millions of files in 1 directory, Divide storage into segments based on the characters of the hash \abc\def\123\ would be the directory for file abcdef123FFFFFF…. If you were scaling to billions of downloads.
If you are using a mongo DB instead of a regular file store much of these problems would be avoided and you could benefit from the sharding etc…