Mac OS: Copying many large (100GB+) files from NAS to local RAID - macos

I'm facing the problem of frequently copying multiple hundred huge media files (each way bigger than 100GB) from a Synology NAS to a local Thunderbolt RAID via LAN using a Mac. I've tried many different options ranging from Finder to rsync. None of which seem to work great (or even good).
Surprisingly just copying using Mac OS Finder is the fastest option that I tested so far. It averages at about 100MB/s. But for many reasons (error handling, no checksums, .DS-Store problems, etc) this method is not at all satisfactory.
Although I do not need to sync anything (just copy entire directories from A to B), rsync has exactly what I need in terms of features but it seems to be way too slow for this kind of task. It averages at about 50-70MB/s (-vaEWh --progress).
My question is: Am I holding it wrong or is rsync not the right tool for this? What else could be used to copy many very large files at speeds above 100MB/s with a decent amount of monitoring and logging?
Thanks a lot!

Related

Move/copy millions of images from Macos to external drive to ubuntu server

I have created a dataset of millions (>15M, so far) of images for a machine-learning project, taking up over 500GB of storage. I created them on my Macbook Pro but want to get them to our DGX1 (GPU cluster) somehow. I thought it would be faster to copy to a fast external SSD (2x nvme in raid0) and then plug that drive directly into local terminal and copy it to the network scratch disk. I'm not so sure anymore, as I've been cp-ing to the external drive for over 24 hrs now.
I tried using the finder gui to copy at first (bad idea!). For a smaller dataset (2M images), I used 7zip to create a few archives. I'm now using the terminal in MacOS to copy the files using cp.
I tried "cp /path/to/dataset /path/to/external-ssd"
Finder was definitely not the best approach as it took forever at the "preparing" to copy stage.
Using 7zip to archive the dataset increased the "file" transfer speed, but it took over 4 days(!) to extract the files, and that for a dataset an order of magnitude smaller.
Using the command line cp, started off quickly but seems to have slowed down. Activity monitor says I'm getting 6-8k IO's on the disk. It's been 24 hours and it isn't quite halfway done.
Is there a better way to do this?
rsync is the preferred tool for this kind of workload. It is used for both local and network copies.
Main benefits are (excerpt from manpage):
delta-transfer algorithm, which reduces the amount of data sent
if it is interrupted for any reason, then you can restart it easily with very little cost. It can even restart part way through a large file
options that control every aspect of its behavior and permit very flexible specification of the set of files to be copied.
Rsync is widely used for backups and mirroring and as an improved copy command for everyday use.
Regarding command usage and syntax, for local transfers is almost the same as cp:
rsync -az /path/to/dataset /path/to/external-ssd

Copying file to multiple destinations

Is there a way to copy, at the same time, a single directory to multiple hard drives without the copy processes having each to read the source files? (Something like a Raid 1 perhaps)
In the specific, where I work we need to deploy (even multiple times a day) a folder containing around ~50gb of data from a PC (with Windows 7) to multiple others... using USB drives... (yup, usb drives, can't do anything about that). Often serially copying the files to each USB takes ages and it creates LONG dead times, especially for the last people to receive their copy.
Since the source PC in question has 8 USB 3.0 ports, would it be possible somehow to copy at the same time the source directory to USB drives in all 8 ports? (Of course without having 8 copy processes fighting for the limited read speed of the source hard drive... just readying each file and copying it to all destinations)
I tried searching for an answer but all I got were answers for linux or networked machines.
http://sourceforge.net/projects/n2ncopy/
I've searched it on google, i have never tryed the program

How do I get Windows to go as fast as Linux for compiling C++?

I know this is not so much a programming question but it is relevant.
I work on a fairly large cross platform project. On Windows I use VC++ 2008. On Linux I use gcc. There are around 40k files in the project. Windows is 10x to 40x slower than Linux at compiling and linking the same project. How can I fix that?
A single change incremental build 20 seconds on Linux and > 3 mins on Windows. Why? I can even install the 'gold' linker in Linux and get that time down to 7 seconds.
Similarly git is 10x to 40x faster on Linux than Windows.
In the git case it's possible git is not using Windows in the optimal way but VC++? You'd think Microsoft would want to make their own developers as productive as possible and faster compilation would go a long way toward that. Maybe they are trying to encourage developers into C#?
As simple test, find a folder with lots of subfolders and do a simple
dir /s > c:\list.txt
on Windows. Do it twice and time the second run so it runs from the cache. Copy the files to Linux and do the equivalent 2 runs and time the second run.
ls -R > /tmp/list.txt
I have 2 workstations with the exact same specs. HP Z600s with 12gig of ram, 8 cores at 3.0ghz. On a folder with ~400k files Windows takes 40seconds, Linux takes < 1 second.
Is there a registry setting I can set to speed up Windows? What gives?
A few slightly relevant links, relevant to compile times, not necessarily i/o.
Apparently there's an issue in Windows 10 (not in Windows 7) that closing a process holds a global lock. When compiling with multiple cores and therefore multiple processes this issue hits.
The /analyse option can adversely affect perf because it loads a web browser. (Not relevant here but good to know)
Unless a hardcore Windows systems hacker comes along, you're not going to get more than partisan comments (which I won't do) and speculation (which is what I'm going to try).
File system - You should try the same operations (including the dir) on the same filesystem. I came across this which benchmarks a few filesystems for various parameters.
Caching. I once tried to run a compilation on Linux on a RAM disk and found that it was slower than running it on disk thanks to the way the kernel takes care of caching. This is a solid selling point for Linux and might be the reason why the performance is so different.
Bad dependency specifications on Windows. Maybe the chromium dependency specifications for Windows are not as correct as for Linux. This might result in unnecessary compilations when you make a small change. You might be able to validate this using the same compiler toolchain on Windows.
A few ideas:
Disable 8.3 names. This can be a big factor on drives with a large number of files and a relatively small number of folders: fsutil behavior set disable8dot3 1
Use more folders. In my experience, NTFS starts to slow down with more than about 1000 files per folder.
Enable parallel builds with MSBuild; just add the "/m" switch, and it will automatically start one copy of MSBuild per CPU core.
Put your files on an SSD -- helps hugely for random I/O.
If your average file size is much greater than 4KB, consider rebuilding the filesystem with a larger cluster size that corresponds roughly to your average file size.
Make sure the files have been defragmented. Fragmented files cause lots of disk seeks, which can cost you a factor of 40+ in throughput. Use the "contig" utility from sysinternals, or the built-in Windows defragmenter.
If your average file size is small, and the partition you're on is relatively full, it's possible that you are running with a fragmented MFT, which is bad for performance. Also, files smaller than 1K are stored directly in the MFT. The "contig" utility mentioned above can help, or you may need to increase the MFT size. The following command will double it, to 25% of the volume: fsutil behavior set mftzone 2 Change the last number to 3 or 4 to increase the size by additional 12.5% increments. After running the command, reboot and then create the filesystem.
Disable last access time: fsutil behavior set disablelastaccess 1
Disable the indexing service
Disable your anti-virus and anti-spyware software, or at least set the relevant folders to be ignored.
Put your files on a different physical drive from the OS and the paging file. Using a separate physical drive allows Windows to use parallel I/Os to both drives.
Have a look at your compiler flags. The Windows C++ compiler has a ton of options; make sure you're only using the ones you really need.
Try increasing the amount of memory the OS uses for paged-pool buffers (make sure you have enough RAM first): fsutil behavior set memoryusage 2
Check the Windows error log to make sure you aren't experiencing occasional disk errors.
Have a look at Physical Disk related performance counters to see how busy your disks are. High queue lengths or long times per transfer are bad signs.
The first 30% of disk partitions is much faster than the rest of the disk in terms of raw transfer time. Narrower partitions also help minimize seek times.
Are you using RAID? If so, you may need to optimize your choice of RAID type (RAID-5 is bad for write-heavy operations like compiling)
Disable any services that you don't need
Defragment folders: copy all files to another drive (just the files), delete the original files, copy all folders to another drive (just the empty folders), then delete the original folders, defragment the original drive, copy the folder structure back first, then copy the files. When Windows builds large folders one file at a time, the folders end up being fragmented and slow. ("contig" should help here, too)
If you are I/O bound and have CPU cycles to spare, try turning disk compression ON. It can provide some significant speedups for highly compressible files (like source code), with some cost in CPU.
NTFS saves file access time everytime. You can try disabling it:
"fsutil behavior set disablelastaccess 1"
(restart)
The issue with visual c++ is, as far I can tell, that it is not a priority for the compiler team to optimize this scenario.
Their solution is that you use their precompiled header feature. This is what windows specific projects have done. It is not portable, but it works.
Furthermore, on windows you typically have virus scanners, as well as system restore and search tools that can ruin your build times completely if they monitor your buid folder for you. windows 7 resouce monitor can help you spot it.
I have a reply here with some further tips for optimizing vc++ build times if you're really interested.
The difficulty in doing that is due to the fact that C++ tends to spread itself and the compilation process over many small, individual, files. That's something Linux is good at and Windows is not. If you want to make a really fast C++ compiler for Windows, try to keep everything in RAM and touch the filesystem as little as possible.
That's also how you'll make a faster Linux C++ compile chain, but it is less important in Linux because the file system is already doing a lot of that tuning for you.
The reason for this is due to Unix culture:
Historically file system performance has been a much higher priority in the Unix world than in Windows. Not to say that it hasn't been a priority in Windows, just that in Unix it has been a higher priority.
Access to source code.
You can't change what you can't control. Lack of access to Windows NTFS source code means that most efforts to improve performance have been though hardware improvements. That is, if performance is slow, you work around the problem by improving the hardware: the bus, the storage medium, and so on. You can only do so much if you have to work around the problem, not fix it.
Access to Unix source code (even before open source) was more widespread. Therefore, if you wanted to improve performance you would address it in software first (cheaper and easier) and hardware second.
As a result, there are many people in the world that got their PhDs by studying the Unix file system and finding novel ways to improve performance.
Unix tends towards many small files; Windows tends towards a few (or a single) big file.
Unix applications tend to deal with many small files. Think of a software development environment: many small source files, each with their own purpose. The final stage (linking) does create one big file but that is an small percentage.
As a result, Unix has highly optimized system calls for opening and closing files, scanning directories, and so on. The history of Unix research papers spans decades of file system optimizations that put a lot of thought into improving directory access (lookups and full-directory scans), initial file opening, and so on.
Windows applications tend to open one big file, hold it open for a long time, close it when done. Think of MS-Word. msword.exe (or whatever) opens the file once and appends for hours, updates internal blocks, and so on. The value of optimizing the opening of the file would be wasted time.
The history of Windows benchmarking and optimization has been on how fast one can read or write long files. That's what gets optimized.
Sadly software development has trended towards the first situation. Heck, the best word processing system for Unix (TeX/LaTeX) encourages you to put each chapter in a different file and #include them all together.
Unix is focused on high performance; Windows is focused on user experience
Unix started in the server room: no user interface. The only thing users see is speed. Therefore, speed is a priority.
Windows started on the desktop: Users only care about what they see, and they see the UI. Therefore, more energy is spent on improving the UI than performance.
The Windows ecosystem depends on planned obsolescence. Why optimize software when new hardware is just a year or two away?
I don't believe in conspiracy theories but if I did, I would point out that in the Windows culture there are fewer incentives to improve performance. Windows business models depends on people buying new machines like clockwork. (That's why the stock price of thousands of companies is affected if MS ships an operating system late or if Intel misses a chip release date.). This means that there is an incentive to solve performance problems by telling people to buy new hardware; not by improving the real problem: slow operating systems. Unix comes from academia where the budget is tight and you can get your PhD by inventing a new way to make file systems faster; rarely does someone in academia get points for solving a problem by issuing a purchase order. In Windows there is no conspiracy to keep software slow but the entire ecosystem depends on planned obsolescence.
Also, as Unix is open source (even when it wasn't, everyone had access to the source) any bored PhD student can read the code and become famous by making it better. That doesn't happen in Windows (MS does have a program that gives academics access to Windows source code, it is rarely taken advantage of). Look at this selection of Unix-related performance papers: http://www.eecs.harvard.edu/margo/papers/ or look up the history of papers by Osterhaus, Henry Spencer, or others. Heck, one of the biggest (and most enjoyable to watch) debates in Unix history was the back and forth between Osterhaus and Selzer http://www.eecs.harvard.edu/margo/papers/usenix95-lfs/supplement/rebuttal.html
You don't see that kind of thing happening in the Windows world. You might see vendors one-uping each other, but that seems to be much more rare lately since the innovation seems to all be at the standards body level.
That's how I see it.
Update: If you look at the new compiler chains that are coming out of Microsoft, you'll be very optimistic because much of what they are doing makes it easier to keep the entire toolchain in RAM and repeating less work. Very impressive stuff.
I personally found running a windows virtual machine on linux managed to remove a great deal of the IO slowness in windows, likely because the linux vm was doing lots of caching that Windows itself was not.
Doing that I was able to speed up compile times of a large (250Kloc) C++ project I was working on from something like 15 minutes to about 6 minutes.
Incremental linking
If the VC 2008 solution is set up as multiple projects with .lib outputs, you need to set "Use Library Dependency Inputs"; this makes the linker link directly against the .obj files rather than the .lib. (And actually makes it incrementally link.)
Directory traversal performance
It's a bit unfair to compare directory crawling on the original machine with crawling a newly created directory with the same files on another machine. If you want an equivalent test, you should probably make another copy of the directory on the source machine. (It may still be slow, but that could be due to any number of things: disk fragmentation, short file names, background services, etc.) Although I think the perf issues for dir /s have more to do with writing the output than measuring actual file traversal performance. Even dir /s /b > nul is slow on my machine with a huge directory.
I'm pretty sure it's related to the filesystem. I work on a cross-platform project for Linux and Windows where all the code is common except for where platform-dependent code is absolutely necessary. We use Mercurial, not git, so the "Linuxness" of git doesn't apply. Pulling in changes from the central repository takes forever on Windows compared to Linux, but I do have to say that our Windows 7 machines do a lot better than the Windows XP ones. Compiling the code after that is even worse on VS 2008. It's not just hg; CMake runs a lot slower on Windows as well, and both of these tools use the file system more than anything else.
The problem is so bad that most of our developers that work in a Windows environment don't even bother doing incremental builds anymore - they find that doing a unity build instead is faster.
Incidentally, if you want to dramatically decrease compilation speed in Windows, I'd suggest the aforementioned unity build. It's a pain to implement correctly in the build system (I did it for our team in CMake), but once done automagically speeds things up for our continuous integration servers. Depending on how many binaries your build system is spitting out, you can get 1 to 2 orders of magnitude improvement. Your mileage may vary. In our case I think it sped up the Linux builds threefold and the Windows one by about a factor of 10, but we have a lot of shared libraries and executables (which decreases the advantages of a unity build).
How do you build your large cross platform project?
If you are using common makefiles for Linux and Windows you could easily degrade windows performance by a factor of 10 if the makefiles are not designed to be fast on Windows.
I just fixed some makefiles of a cross platform project using common (GNU) makefiles for Linux and Windows. Make is starting a sh.exe process for each line of a recipe causing the performance difference between Windows and Linux!
According to the GNU make documentation
.ONESHELL:
should solve the issue, but this feature is (currently) not supported for Windows make. So rewriting the recipes to be on single logical lines (e.g. by adding ;\ or \ at the end of the current editor lines) worked very well!
IMHO this is all about disk I/O performance. The order of magnitude suggests a lot of the operations go to disk under Windows whereas they're handled in memory under Linux, i.e. Linux is caching better. Your best option under windows will be to move your files onto a fast disk, server or filesystem. Consider buying an Solid State Drive or moving your files to a ramdisk or fast NFS server.
I ran the directory traversal tests and the results are very close to the compilation times reported, suggesting this has nothing to do with CPU processing times or compiler/linker algorithms at all.
Measured times as suggested above traversing the chromium directory tree:
Windows Home Premium 7 (8GB Ram) on NTFS: 32 seconds
Ubuntu 11.04 Linux (2GB Ram) on NTFS: 10 seconds
Ubuntu 11.04 Linux (2GB Ram) on ext4: 0.6 seconds
For the tests I pulled the chromium sources (both under win/linux)
git clone http://github.com/chromium/chromium.git
cd chromium
git checkout remotes/origin/trunk
To measure the time I ran
ls -lR > ../list.txt ; time ls -lR > ../list.txt # bash
dir -Recurse > ../list.txt ; (measure-command { dir -Recurse > ../list.txt }).TotalSeconds #Powershell
I did turn off access timestamps, my virus scanner and increased the cache manager settings under windows (>2Gb RAM) - all without any noticeable improvements. Fact of the matter is, out of the box Linux performed 50x better than Windows with a quarter of the RAM.
For anybody who wants to contend that the numbers wrong - for whatever reason - please give it a try and post your findings.
Try using jom instead of nmake
Get it here:
https://github.com/qt-labs/jom
The fact is that nmake is using only one of your cores, jom is a clone of nmake that make uses of multicore processors.
GNU make do that out-of-the-box thanks to the -j option, that might be a reason of its speed vs the Microsoft nmake.
jom works by executing in parallel different make commands on different processors/cores.
Try yourself an feel the difference!
I want to add just one observation using Gnu make and other tools from MinGW tools on Windows: They seem to resolve hostnames even when the tools can not even communicate via IP. I would guess this is caused by some initialisation routine of the MinGW runtime. Running a local DNS proxy helped me to improve the compilation speed with these tools.
Before I got a big headache because the build speed dropped by a factor of 10 or so when I opened a VPN connection in parallel. In this case all these DNS lookups went through the VPN.
This observation might also apply to other build tools, not only MinGW based and it could have changed on the latest MinGW version meanwhile.
I recently could archive an other way to speed up compilation by about 10% on Windows using Gnu make by replacing the mingw bash.exe with the version from win-bash
(The win-bash is not very comfortable regarding interactive editing.)

Compiling code on an external drive

To make things easier when switching between machines (my workstation at the office and my personal laptop) I have thought about trying an external hard drive to store my working directory on. Specifically I am looking at Firewire 800 drives (most are 5400 rpm 8mb cache). What I am wondering is if anyone has experience with doing this with Visual Studio projects and what sort of performance hit they see.
It depends on the size of the project. The throughput is low and the latency is high, so you're going to get hit every which way, but due to the latency you'll be hit harder if you have a lot of little files rather than a few large ones.
Have you considered simply carrying around a GIT or other distributed repository and updating the machine repositories as you move around? Then you can compile locally and treat the drive and a roving server. Since only changes will be moved across, it should be faster, and your code will be 'backed up' in more places.
If you forget the drive, it breaks, or is lost/stolen, then you can still sit down at a PC and program with no code missing if you're at the last PC you used, or very little code missing (which will be updated later with a resync anyway).
And it's just a hop skip and a jump away from simply using the network to move the changes between the systems if you don't want to carry the drive around later.
I use vmware and the virtual machines are on an external usb drive. Performance is fine. You might have some issues with the drive name changing - not an issue if you use virtual machines.
Granted I work in an industry were Personal Information and Intellectual Property are king, but I don't like that idea at all. That hard drive disappears and you have a big problem.
Why not Remote Desktop into the work machine?
EDIT Stipud Spelingg

Quicker way to create duplicate Virtual PC images?

I use Virtual PC to create fresh environments for testing my installer. But I must be doing something wrong because a VPC image with Vista or XP inside is taking around 15GB of disk space (that includes VS2005/S2008 installed in them).
To create a new copy for testing I copy and paste the folder that has the .vhd, .vmc and .vsv files inside. After using the new VPC image for testing I then delete that copied folder. This works but it takes a looong time to copy 15GB each time. Is there some faster/more efficent approach?
Use differencing/undo disks. This means when you shut down your VPC you'll be asked if you want to save changes, simply answer no and you'll be back to where you started.
Doesn't VirtualPC have a fake-write/snapshot mode? That way it should not write to your original disk at all unless you say so at the end of the session.
If it doesn't, you might seriously want to consider VMWare or VirtualBox as these do have this feature and it's REALLY useful for things like this.
Edit: it looks like VPC does have a feature like this called differencing disks. Have a look at this:
http://www.andrewconnell.com/blog/articles/UseVirtualPCsDifferencingDisksToYourAdvantage.aspx
VPC has a so called undo disk. you create sg similar like "restore point" and in vpc you can roll back to that version. ideal for testing setups.
Sound like you need to use differencing virtual hard disks rather than creating a new copy every time.
Instructions here
Another option: you can use Microsoft's ImageX to store VHDs in WIM format. If you have multiple images you are constantly reusing, this is an incredible way to manage VMs. I have a slew of Windows XP and 2003 images I keep in compressed WIM format.
You can capture the VMs by mounting them in Windows PE and then capturing them to a network drive.
Also, you mentioned cut & paste, this is not the best way to be copying large amounts of data within windows. At least use xcopy, robocopy is even faster.
Also, another option if you are looking to duplicate the images for use on other real machines, you can convert the disk to a dynamically expanding disk which will reduce the size of the vdisk making it easier to copy. This also allows for a more rapid backup, which looks to be part of what your testing does by default. The problem with dynamic disks is they tend to be slightly slower performance wise than fixed-size disks.
However, if all you are doing is using it for testing on the same machine, see the answers above. Differencing is the way to go.

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