I'm trying to implement a multi-user key-value store over the file system, such as the local Linux or Windows file system, or a network-based one (SMB or NFS). My intent is to fully avoid the need of a server because servers require some VM, deployment, upgrades, etc. And filesystems are typically readily available.
The engine returns the timestamp of when the value was set. One operation that uses the timestamp is "put if not modified since", which is similar to compare-and-swap and supports synchronization among processes. It turns out that this is quite costly to implement without a server.
It seems that no file system supports "write if not modified" or any form of conditional write semantics. At best I can lock a file, but then I need to read the date and compare inside the process, and only then write the new content and release the lock. The minimum number of IOs to implement is four: 1) lock entire file; 2) read modification date and compare locally; 3) write the new content; 4) unlock. And this ignores the IOs to open and close the file, which are pooled so they will be less frequent.
Is there any OS or filesystem facility, or algorithm that could reduce the number of IOs? Please remember that I need the solution to work over NFS or SMB...
Thanks
Filesystems already do read-ahead and write avoidance, so I/O calls will only block for disk when read data is not in cache or write cache is full and a flush is required. The performance problem with the "write if not modified since" is the 4 syscalls, which can get expensive. One way to fix this would be to add a conditional write kernel module. You would pass it the timestamp, file name, and data. It would do the conditional write using internal calls and callbacks, and return the status and new timestamp, reducing the overhead to a single syscall. Properly written, it should be filesystem-agnostic.
I would appreciate insight from anyone who can suggest the best or better solution in editing large files anyway ranges from 1MB to 200MB using nodejs.
Our process needs to merge lines to an existing file in the filesystem, we get the changed data in the following format which needs to be merged to filesystem file at the position defined in the changed details.
[{"range":{"startLineNumber":3,"startColumn":3,"endLineNumber":3,"endColumn":3},"rangeLength":0,"text":"\n","rangeOffset":4,"forceMoveMarkers":false},{"range":{"startLineNumber":4,"startColumn":1,"endLineNumber":4,"endColumn":1},"rangeLength":0,"text":"\n","rangeOffset":5,"forceMoveMarkers":false},{"range":{"startLineNumber":5,"startColumn":1,"endLineNumber":5,"endColumn":1},"rangeLength":0,"text":"\n","rangeOffset":6,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":1,"endLineNumber":6,"endColumn":1},"rangeLength":0,"text":"f","rangeOffset":7,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":2,"endLineNumber":6,"endColumn":2},"rangeLength":0,"text":"a","rangeOffset":8,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":3,"endLineNumber":6,"endColumn":3},"rangeLength":0,"text":"s","rangeOffset":9,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":4,"endLineNumber":6,"endColumn":4},"rangeLength":0,"text":"d","rangeOffset":10,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":5,"endLineNumber":6,"endColumn":5},"rangeLength":0,"text":"f","rangeOffset":11,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":6,"endLineNumber":6,"endColumn":6},"rangeLength":0,"text":"a","rangeOffset":12,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":7,"endLineNumber":6,"endColumn":7},"rangeLength":0,"text":"s","rangeOffset":13,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":8,"endLineNumber":6,"endColumn":8},"rangeLength":0,"text":"f","rangeOffset":14,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":9,"endLineNumber":6,"endColumn":9},"rangeLength":0,"text":"s","rangeOffset":15,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":10,"endLineNumber":6,"endColumn":10},"rangeLength":0,"text":"a","rangeOffset":16,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":11,"endLineNumber":6,"endColumn":11},"rangeLength":0,"text":"f","rangeOffset":17,"forceMoveMarkers":false},{"range":{"startLineNumber":6,"startColumn":12,"endLineNumber":6,"endColumn":12},"rangeLength":0,"text":"s","rangeOffset":18,"forceMoveMarkers":false}]
If we just open the full file and merge those details would work but it would break if we getting too many of those changed details very frequently that can cause out of memory issues as the file been opened many times which is also a very inefficient way.
There is a similar question aimed specifically at c# here. If we open the file in stream mode, is there similar example in nodejs?
I would appreciate insight from anyone who can suggest the best or better solution in editing large files anyway ranges from 1MB to 200MB using nodejs.
Our process needs to merge lines to an existing file in the filesystem, we get the changed data in the following format which needs to be merged to filesystem file at the position defined in the changed details.
General OS file systems do not directly support the concept of inserting info into a file. So, if you have a flat file and you want to insert data into it starting at a particular line number, you have to do the following steps:
Open the file and start reading from the beginning.
As you read data from the file, count lines until you reach the desired linenumber.
Then, if you're inserting new data, you need to read some more and buffer into memory the amount of data you intend to insert.
Then do a write to the file at the position of insertion of the data to insert.
Now using another buffer the size of the data you inserted, take turns reading another buffer, then writing out the previous buffer.
Continue until the end of the file is reach and all data is written back to the file (after the newly inserted data).
This has the effect of rewriting all the data after the insertion point back to the file so it will now correctly be in its new location in the file.
As you can tell, this is not efficient at all for large files as you have to read the entire file a buffer at a time and you have to write the insertion and everything after the insertion point.
In node.js, you can use features in the fs module to carry out all these steps, but you have to write the logic to connect them all together as there is no built-in feature to insert new data into a file while pushing the existing data after it.
There is a similar question aimed specifically at c# here. If we open the file in stream mode, is there similar example in nodejs?
The C# example you reference appears to just be appending new data onto the end of the file. That's trivial to do in pretty much any file system library. In node.js, you can do that with fs.appendFile() or you can open any file handle in append mode and then write to it.
To insert data into a file more efficiently, you would need to use a more efficient storage system than a single flat file for all the data. For example, if you stored the file in pieces in approximately 100 line blocks, then to insert data you'd only have to rewrite a portion of one block of data and then perhaps have some cleanup process that rebalances the block boundaries if a block gets way too big or too small.
For efficient line management, you would need to maintain an accurate index of how many lines each file piece contains and obviously what order the pieces should be in. This would allow you to insert data at a somewhat fixed cost no matter how big the entire file was as the most you would need to do is to rewrite one or two blocks of data, even if the entire content was hundreds of GB in size.
Note, you would essentially be building a new file system on top of the OS file system in order to give yourself more efficient inserts or deletions within the overall data. Obviously, the chunks of data could also be stored in a database too and managed there.
Note, if this project is really an editor, text editing a line-based structure is a very well studied problem and you could also study the architectures used in previous projects for further ideas. It's a bit beyond the scope of a typical answer here to study the pros and cons of various architectures. If your system is also a client/server editor where the change instructions are being sent from a client to a server, that also affects some of the desired tradeoffs in the design since you may desire differing tradeoffs in terms of the number of transactions or the amount of data to be sent between client and server.
If some other language uses an optimal way then I think it would be better to find that option as you saying nodejs might not have that option.
This doesn't really have anything to do with the language you choose. This is about how modern and typical operating systems store data in files.
In fs module there is a function named appendFile. It would let you append data in your file. Link.
I need to implement external multithreading sort. I dont't have experience in multithreading programming and now I'm not sure if my algorithm is good anoth also I don't know how to complete it. My idea is:
Thread reads next block of data from input file
Sort it using standart algorith(std::sort)
Writes it to another file
After this I have to merge such files. How should I do this?
If I wait untill input file will be entirely processed until merge
I recieve a lot of temporary files
If I try to merge file straight after sort, I can not come up with
an algorithm to avoid merging files with quite different sizes, which
will lead to O(N^2) difficulty.
Also I suppose this is a very common task, however I cannot find good prepared algoritm in the enternet. I would be very grateful for such a link especially for it's c++ implementation.
Well, the answer isn't that simple, and it actually depends on many factors, amongst them the number of items you wish to process, and the relative speed of your storage system and CPUs.
But the question is why to use multithreading at all here. Data too big to be held in memory? So many items that even a qsort algorithm can't sort fast enough? Take advantage of multiple processors or cores? Don't know.
I would suggest that you first write some test routines to measure the time needed to read and write the input file and the output files, as well as the CPU time needed for sorting. Please note that I/O is generally A LOT slower than CPU execution (actually they aren't even comparable), and I/O may not be efficient if you read data in parallel (there is one disk head which has to move in and out, so reads are in effect serialized - even if it's a digital drive it's still a device, with input and output channels). That is, the additional overhead of reading/writing temporary files may more than eliminate any benefit from multithreading. So I would say, first try making an algorithm that reads the whole file in memory, sorts it and writes it, and put in some time counters to check their relative speed. If I/O is some 30% of the total time (yes, that little!), it's definitely not worth, because with all that reading/merging/writing of temporary files, this will rise a lot more, so a solution processing the whole data at once would rather be preferable.
Concluding, don't see why use multithreading here, the only reason imo would be if data are actually delivered in blocks, but then again take into account my considerations above, about relative I/O-CPU speeds and the additional overhead of reading/writing the temporary files. And a hint, your file accessing must be very efficient, eg reading/writing in larger blocks using application buffers, not one by one (saves on system calls), otherwise this may have a detrimental effect if the file(s) are stored on a machine other than yours (eg a server).
Hope you find my suggestions useful.
Picture a directory with a ton of files. As a rough gauge of magnitude I think the most that we've seen so far is a couple of million but it could technically go another order higher. Using node, I would like to read files from this directory, process them (upload them, basically), and then move them out of the directory. Pretty simple. New files are constantly being added while the application is running, and my job (like a man on a sinking ship holding a bucket) is to empty this directory as fast as it's being filled.
So what are my options? fs.readdir is not ideal, it loads all of the filenames into memory which becomes a problem at this kind of scale. Especially as new files are being added all the time and so it would require repeated calls. (As an aside for anybody referring to this in the future, there is something being proposed to address this whole issue which may or may not have been realised within your timeline.)
I've looked at the myriad of fs drop-ins (graceful-fs, chokadir, readdirp, etc), none of which have this particular use-case within their remit.
I've also come across a couple of people suggesting that this can be handled with child_process, and there's a wrapper called inotifywait which tasks itself with exactly what I am asking but I really don't understand how this addresses the underlying problem, especially at this scale.
I'm wondering if what I really need to do is find a way to just get the first file (or, realistically, batch of files) from the directory without having the overhead of reading the entire directory structure into memory. Some sort of stream that could be terminated after a certain number of files had been read? I know Go has a parameter for reading the first n files from a directory but I can't find a node equivalent, has anybody here come across one or have any interesting ideas? Left-field solutions more than welcome at this point!
You can use your operation system listing file command, and stream the result into NodeJS.
For example in Linux:
var cp=require('child_process')
var stdout=cp.exec('ls').stdout
stdout.on('data',function(a){
console.log(a)
});0
RunKit: https://runkit.com/aminanadav/57da243180f3bb140059a31d
I have a Node.js application that stores some configuration data in a file. If you change some settings, the configuration file is written to disk.
At the moment, I am using a simple fs.writeFile.
Now my question is: What happens when Node.js crashes while the file is being written? Is there the chance to have a corrupt file on disk? Or does Node.js guarantee that the file is written in an atomic way, so that either the old or the new version is valid?
If not, how could I implement such a guarantee? Are there any modules for this?
What happens when Node.js crashes while the file is being written? Is
there the chance to have a corrupt file on disk? Or does Node.js
guarantee that the file is written in an atomic way, so that either
the old or the new version is valid?
Node implements only a (thin) async wrapper over system calls, thus it does not provide any guarantees about atomicity of writes. In fact, fs.writeAll repeatedly calls fs.write until all data is written. You are right that when Node.js crashes, you may end up with a corrupted file.
If not, how could I implement such a guarantee? Are there any modules for this?
The simplest solution I can come up with is the one used e.g. for FTP uploads:
Save the content to a temporary file with a different name.
When the content is written on disk, rename temporary file to destination file.
The man page says that rename guarantees to leave an instance of newpath in place (on Unix systems like Linux or OSX).
fs.writeFile, just like all the other methods in the fs module are implemented as simple wrappers around standard POSIX functions (as stated in the docs).
Digging a bit in nodejs' code, one can see that the fs.js, where all the wrappers are defined, uses fs.c for all its file system calls. More specifically, the write method is used to write the contents of the buffer. It turns out that the POSIX specification for write explicitly says that:
Atomic/non-atomic: A write is atomic if the whole amount written in
one operation is not interleaved with data from any other process.
This is useful when there are multiple writers sending data to a
single reader. Applications need to know how large a write request can
be expected to be performed atomically. This maximum is called
{PIPE_BUF}. This volume of IEEE Std 1003.1-2001 does not say whether
write requests for more than {PIPE_BUF} bytes are atomic, but requires
that writes of {PIPE_BUF} or fewer bytes shall be atomic.
So it seems it is pretty safe to write, as long as the size of the buffer is smaller than PIPE_BUF. This is a constant that is system-dependent though, so you might need to check it somewhere else.
write-file-atomic will do what you need. It writes to temporary file, then rename. That's safe.