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I made some comparision with bombardier[0], the one listed here are 30s looped requests with two concurrent clients: [ static download of ext-all.js ]: lvl avg / stdev / max none 1.98 MiB 100 % 5.17ms / 1.30ms / 32.38ms fastest 813.14 KiB 42 % 20.53ms / 2.85ms / 58.71ms default 626.35 KiB 30 % 39.70ms / 3.98ms / 85.47ms [ deterministic (pre-defined data), but real API call ]: lvl avg / stdev / max none 129.09 KiB 100 % 2.70ms / 471.58us / 26.93ms fastest 42.12 KiB 33 % 3.47ms / 606.46us / 32.42ms default 34.82 KiB 27 % 4.28ms / 737.99us / 33.75ms The reduction is quite better with default, but it's also slower, but only when testing over unconstrained network. For real world scenarios where compression actually matters, e.g., when using a spotty train connection, we will be faster again with better compression. A GPRS limited connection (Firefox developer console) requires the following load (until the DOMContentLoaded event triggered) times: lvl t x faster none 9m 18.6s x 1.0 fastest 3m 20.0s x 2.8 default 2m 30.0s x 3.7 So for worst case using sligthly more CPU time on the server has a tremendous effect on the client load time. Using a more realistical example and limiting for "Good 2G" gives: none 1m 1.8s x 1.0 fastest 22.6s x 2.7 default 16.6s x 3.7 16s is somewhat OK, >1m just isn't... So, use default level to ensure we get bearable load times on clients, and if we want to improve transmission size AND speed then we could always use a in-memory cache, only a few MiB would be required for the compressable static files we server. Signed-off-by: Thomas Lamprecht <t.lamprecht@proxmox.com> |
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TODO.rst |
``rustup`` Toolchain ==================== We normally want to build with the ``rustc`` Debian package. To do that you can set the following ``rustup`` configuration: # rustup toolchain link system /usr # rustup default system Versioning of proxmox helper crates =================================== To use current git master code of the proxmox* helper crates, add:: git = "git://git.proxmox.com/git/proxmox" or:: path = "../proxmox/proxmox" to the proxmox dependency, and update the version to reflect the current, pre-release version number (e.g., "0.1.1-dev.1" instead of "0.1.0"). Local cargo config ================== This repository ships with a ``.cargo/config`` that replaces the crates.io registry with packaged crates located in ``/usr/share/cargo/registry``. A similar config is also applied building with dh_cargo. Cargo.lock needs to be deleted when switching between packaged crates and crates.io, since the checksums are not compatible. To reference new dependencies (or updated versions) that are not yet packaged, the dependency needs to point directly to a path or git source (e.g., see example for proxmox crate above). Build ===== on Debian Buster Setup: 1. # echo 'deb http://download.proxmox.com/debian/devel/ buster main' >> /etc/apt/sources.list.d/proxmox-devel.list 2. # sudo wget http://download.proxmox.com/debian/proxmox-ve-release-6.x.gpg -O /etc/apt/trusted.gpg.d/proxmox-ve-release-6.x.gpg 3. # sudo apt update 4. # sudo apt install devscripts debcargo clang 5. # git clone git://git.proxmox.com/git/proxmox-backup.git 6. # sudo mk-build-deps -ir Note: 2. may be skipped if you already added the PVE or PBS package repository You are now able to build using the Makefile or cargo itself. Design Notes ============ Here are some random thought about the software design (unless I find a better place). Large chunk sizes ----------------- It is important to notice that large chunk sizes are crucial for performance. We have a multi-user system, where different people can do different operations on a datastore at the same time, and most operation involves reading a series of chunks. So what is the maximal theoretical speed we can get when reading a series of chunks? Reading a chunk sequence need the following steps: - seek to the first chunk start location - read the chunk data - seek to the first chunk start location - read the chunk data - ... Lets use the following disk performance metrics: :AST: Average Seek Time (second) :MRS: Maximum sequential Read Speed (bytes/second) :ACS: Average Chunk Size (bytes) The maximum performance you can get is:: MAX(ACS) = ACS /(AST + ACS/MRS) Please note that chunk data is likely to be sequential arranged on disk, but this it is sort of a best case assumption. For a typical rotational disk, we assume the following values:: AST: 10ms MRS: 170MB/s MAX(4MB) = 115.37 MB/s MAX(1MB) = 61.85 MB/s; MAX(64KB) = 6.02 MB/s; MAX(4KB) = 0.39 MB/s; MAX(1KB) = 0.10 MB/s; Modern SSD are much faster, lets assume the following:: max IOPS: 20000 => AST = 0.00005 MRS: 500Mb/s MAX(4MB) = 474 MB/s MAX(1MB) = 465 MB/s; MAX(64KB) = 354 MB/s; MAX(4KB) = 67 MB/s; MAX(1KB) = 18 MB/s; Also, the average chunk directly relates to the number of chunks produced by a backup:: CHUNK_COUNT = BACKUP_SIZE / ACS Here are some staticics from my developer worstation:: Disk Usage: 65 GB Directories: 58971 Files: 726314 Files < 64KB: 617541 As you see, there are really many small files. If we would do file level deduplication, i.e. generate one chunk per file, we end up with more than 700000 chunks. Instead, our current algorithm only produce large chunks with an average chunks size of 4MB. With above data, this produce about 15000 chunks (factor 50 less chunks).