I found a nice answer of S.Lott about what I've been searching for:
Client-server synchronization pattern / algorithm?
But my question is now, what if the client has a wrong time?
Here's my problem:
Let's say the time of the client is 1 hour behind the servers, then the client changes a file, so the last write time is now 1 hour behind the servers. When the user starts his program which synchronizes the file, the server says to the changed file: "Oh, that file you have there is 1 hour older than mine, so let's replace it", but that's wrong, because the users file is actually newer, so it should be uploaded to the server.
I need a system that checks if the file is newer on server or on the client, and that doesn't work if the time is wrong or different.
Any ideas?
By the way, I am trying to write a cloud program.
If you're resolving conflicts manually (which would make sense for most applications), this can probably be done better with versioning rather than timestamps. When a client modifies a file, set a flag. When synchronizing, check the flag and versions.
If the client flag is set and the client and server versions are the same, send the client file to the server.
If the client flag is not set and the server version is newer, send the server file to the client.
If the client flag is set and the server version is newer, a conflict occurred and should be resolved.
The versions are per-file and should be sent along with the files.
Reset all client flags after synchronization.
This 'flag' can just be a check whether the last modified time on the file is different from the time that file was received from the server (we can store this time separately right after getting the file from the server).
Alternatively, you could sync the time.
Here's one possible solution:
When receiving files from the server, first get the current time from the server, then offset the timestamp of each file received on the client side by the difference between the server and client time. When sending files to the server, you can do something similar by offsetting by the client time.
But this seems more complex than necessary.
Related
I have an empty API in laravel code with nginx & apache server. Now the problem is that the API takes a lot of time if I try with different files and the API responds quickly if I try with blank data.
Case 1 : I called the API with a blank request, that time response time will be only 228ms.
Case 2 : I called the API with a 5MB file request, then file transfer taking too much time. that's why response time will be too long that is 15.58s.
So how can we reduce transfer start time in apache or nginx server, Is there any server configuration or any other things that i missed up ?
When I searched on google it said keep all your versions up-to-date and use php-fpm, but when I configure php-fpm and http2 protocol on my server I noticed that it takes more time than above. All server versions are up-to-date with the current version.
This has more to do with the fact one request has nothing to process so the response will be prompt, whereas, the other request requires actual processing and so a response will take as long as the server requires to process the content of your request.
Depending on the size of the file and your server configuration, you might hit a limit which will result in a timeout response.
A solution to the issue you're encountering is to chunk your file upload. There are a few packages available so that you don't have to write that functionality yourself, an example of such a package is the Pionl Laravel Chunk Upload.
An alternative solution would be to offload the file processing to a Queue.
Update
When I searched on google about chunking it's not best solution for
small file like 5-10 MB. It's a best solution for big files like
50-100 MB. So is there any server side chunking configuration or any
other things or can i use this library to chunking a small files ?
According to the library document this is a web library. What should I
use if my API is calling from Android and iOS apps?
True, chunking might not be the best solution for smaller files but it is worthwhile knowing about. My recommendation would be to use some client-side logic to determine if sending the file in chunks is required. On the server use a Queue to process the file upload in the background allowing the request to continue processing without waiting on the upload and a response to be sent back to the client (iOS/Android app) in a timely manner.
I'm using Apache Camel to interact with several SFTP endpoints; for each one, I perform the following pipeline:
retrieve the list of existing files
validate those files against a given set of rules
download remote files, in case of successful validation
Everything works like a charm (for about a hundred different endpoints) and the URI used to retrieve the list of files is something like that: sftp://${HOST}:${PORT}/${DIR}?username=${USER}&download=false&recursive=true&disconnect=true&sendEmptyMessageWhenIdle=true
The problem is that, for one of those SFTP endpoints, the SFTP Camel component behaves, alternatively, as follows:
immediately return 0 remote files
takes a couple of minutes to list the remote content (which is composed by around 250 files, from 2KB to 2MB each)
In addition, in the latter case, the download takes around 30 seconds to download only 10KB of data.
Since this is happening on this specific SFTP only, I suppose it doesn't directly depend on Camel, which works fine for all other endpoints.
So, my questions are:
what can affect such a connection, leading to an unreasonable delay (there are no network issues, nor huge data to fetch)?
supposing it depends on the remote SFTP endpoint, why should the aforementioned Camel URI immediately return 0 files, since lots of files exist in the SFTP?
Thanks for any feedback.
Let's assume there is no bug in the Camel SFTP component of your version.
what can affect such a connection, leading to an unreasonable delay
(there are no network issues, nor huge data to fetch)?
Consider the fact that your app can immediately return 0 remote files, the problem source exist between your app and target server is relatively low. For server side, it could be
Too many folders to traverse
Server have slow action on each call
other problem on server side
For the case (Too many folders to traverse), consider to ignore folders that are useless and other config (e.g. stepwise)
supposing it depends on the remote SFTP endpoint, why should the
aforementioned Camel URI immediately return 0 files, since lots of
files exist in the SFTP?
The server side could be using multiple SFTP server nodes and some nodes are empty due to file system synchronization failure. When client is being redirect to any empty SFTP server node by server side's gateway, server node return 0 remote files in response and client report as-is.
Before downloading file, I need to set up a way it (the .csv typically, but not always) will be parsed.
I don't want to download the whole file especially if the "headers" do not match what is expected.
Is there a way to only download up until a certain number of byes and then gracefully kill the connection?
There's no explicit support for this in an FTP protocol.
There's an expired draft for RANG command that would allow this:
https://datatracker.ietf.org/doc/html/draft-bryan-ftp-range-08
But that's obviously supported by only new FTP servers.
Though there's nothing that prevents you from initiating a normal (full) download and forcefully break it as soon you get the amount of data you need.
All you need to do is to close the data transfer connection. This is basically what all FTP clients do, when an end user decides to abort the transfer.
This approach might result in few error messages in an FTP server log.
If you can use an SFTP protocol, then it's easy. The SFTP supports this natively.
What is a low-latency, low-bandwidth algorithm for synchronizing, say, a text file between a client and a server?
Is there a design where the client send a delta of it's current state and it's last ACK'd state from the server? I am thinking Quake3 networking..
EDIT 1:
More specifically, how would a diff/delta algorithm behave in a client/server environment.
e.g. Is it more expensive to calculate a diff on the client side, send to server, server interprets and updates its store, sends ACK to client? Or is it cheaper to have a replication model where client sends its full state and server stores it..?
EDIT 2:
100 KB text file. Something small, not too large.
You mean like a diff?
Store the server-side's version of the file in the client. Whenever you need to synchronize, run a diff (you can either write your own or use a library). Then send the difference over to the server and have the server patch it's local version.
If a client also edits text, and has an undo/redo feature then undo stack can be used for delta. For large texts and small changes using undo stack should be more efficient than running a diff.
For text you can use delta algorithm, take a look, for example, on how rsync works.
Google uses a different approach to update chrome, you can "google" it to see.
Edit: If it was a server generating one change and replicating in lots of clients, it should be done in server. From the question's changes, I understood that a client (or many clients) will produce the changes and want them to be replicated on server.
Well... I'd take in account 4 things:
network performance
number of clients
number of changes expected
performance of the server and of the client
Too many clients sending and doing that on server: it's almost a DoS
I'd only do that on server if there were few clients, high server performance and low client performance.
Otherwise, I'd only do that on clients.
I have over 500 machines distributed across a WAN covering three continents. Periodically, I need to collect text files which are on the local hard disk on each blade. Each server is running Windows server 2003 and the files are mounted on a share which can be accessed remotely as \server\Logs. Each machine holds many files which can be several Mb each and the size can be reduced by zipping.
Thus far I have tried using Powershell scripts and a simple Java application to do the copying. Both approaches take several days to collect the 500Gb or so of files. Is there a better solution which would be faster and more efficient?
I guess it depends what you do with them ... if you are going to parse them for metrics data into a database, it would be faster to have that parsing utility installed on each of those machines to parse and load into your central database at the same time.
Even if all you are doing is compressing and copying to a central location, set up those commands in a .cmd file and schedule it to run on each of the servers automatically. Then you will have distributed the work amongst all those servers, rather than forcing your one local system to do all the work. :-)
The first improvement that comes to mind is to not ship entire log files, but only the records from after the last shipment. This of course is assuming that the files are being accumulated over time and are not entirely new each time.
You could implement this in various ways: if the files have date/time stamps you can rely on, running them through a filter that removes the older records from consideration and dumps the remainder would be sufficient. If there is no such discriminator available, I would keep track of the last byte/line sent and advance to that location prior to shipping.
Either way, the goal is to only ship new content. In our own system logs are shipped via a service that replicates the logs as they are written. That required a small service that handled the log files to be written, but reduced latency in capturing logs and cut bandwidth use immensely.
Each server should probably:
manage its own log files (start new logs before uploading and delete sent logs after uploading)
name the files (or prepend metadata) so the server knows which client sent them and what period they cover
compress log files before shipping (compress + FTP + uncompress is often faster than FTP alone)
push log files to a central location (FTP is faster than SMB, the windows FTP command can be automated with "-s:scriptfile")
notify you when it cannot push its log for any reason
do all the above on a staggered schedule (to avoid overloading the central server)
Perhaps use the server's last IP octet multiplied by a constant to offset in minutes from midnight?
The central server should probably:
accept log files sent and queue them for processing
gracefully handle receiving the same log file twice (should it ignore or reprocess?)
uncompress and process the log files as necessary
delete/archive processed log files according to your retention policy
notify you when a server has not pushed its logs lately
We have a similar product on a smaller scale here. Our solution is to have the machines generating the log files push them to a NAT on a daily basis in a randomly staggered pattern. This solved a lot of the problems of a more pull-based method, including bunched-up read-write times that kept a server busy for days.
It doesn't sound like the storage servers bandwidth would be saturated, so you could pull from several clients at different locations in parallel. The main question is, what is the bottleneck that slows the whole process down?
I would do the following:
Write a program to run on each server, which will do the following:
Monitor the logs on the server
Compress them at a particular defined schedule
Pass information to the analysis server.
Write another program which sits on the core srver which does the following:
Pulls compressed files when the network/cpu is not too busy.
(This can be multi-threaded.)
This uses the information passed to it from the end computers to determine which log to get next.
Uncompress and upload to your database continuously.
This should give you a solution which provides up to date information, with a minimum of downtime.
The downside will be relatively consistent network/computer use, but tbh that is often a good thing.
It will also allow easy management of the system, to detect any problems or issues which need resolving.
NetBIOS copies are not as fast as, say, FTP. The problem is that you don't want an FTP server on each server. If you can't process the log files locally on each server, another solution is to have all the server upload the log files via FTP to a central location, which you can process from. For instance:
Set up an FTP server as a central collection point. Schedule tasks on each server to zip up the log files and FTP the archives to your central FTP server. You can write a program which automates the scheduling of the tasks remotely using a tool like schtasks.exe:
KB 814596: How to use schtasks.exe to Schedule Tasks in Windows Server 2003
You'll likely want to stagger the uploads back to the FTP server.