34%
07.06.2019
:315798907716a51610bb3c270c191e0e61112b19aae9a3bb0c2a60c53d074750",
04 "RepoTags": [
05 "nginx:1.15-alpine"
06 ],
07 "RepoDigests": [
08 "nginx@sha256:385fbcf0f
34%
01.08.2019
:jonathonf/python-3.6
$ apt-get update
$ apt-get install python3.6
In Figure 3 you can see that Python v3.6 adds about 23MB of files to your machine. Depending on how much time you've spent with Python, you might
33%
05.08.2024
, as in Python [3] or Node [4].
Recent books have been published about writing shell commands in Rust [5], Python [6], Node.js [7], and even Go [8], and it is into this last language's interesting performance
33%
11.04.2016
(512 MB) copied, 49.1424 s, 10.4 MB/s
If you want to empty the read and write cache for benchmark purposes, you can do so using:
sync; echo 3 > /proc/sys/vm/drop_caches
Sequential access
33%
29.09.2020
-line operations.
To install Dockly [3], you can choose one of two routes: with npm (see the "Installation by npm" box for that route) and in a Docker container. For context, on my laptop, about 43MB of file space
33%
16.03.2021
, ioengine=libaio, iodepth=32
fio-3.12
Starting 1 process
Jobs: 1 (f=1)
test: (groupid=0, jobs=1): err= 0: pid=5872: Sat Jan 9 16:35:08 2021
read: IOPS=251k, BW=979MiB/s (1026MB/s)(2045MiB/2089msec
32%
09.01.2013
a 256-bit AES key. An additional SHA-256 HMAC checksum protects the data from manipulation.
Compression: S3QL compresses the data before storing, using either LZMA, bzip2, or gzip. This compression ... advantages: S3QL. ... S3QL filesystem for cloud backups
32%
31.10.2025
(depending on the RAID level). These chunks are usually 1GB for data and 256MB for metadata. One exception is the first metadata chunk, which mkfs.btrfs creates 1GB in size, assuming there is enough space
32%
07.01.2013
of Ubuntu on the virtual machine. The virtual machine uses one CPU (core) and 128MB of RAM.
The filesystem is created as a QCOW2 image file of 4GB. Of these, 3GB are reserved for the system partition
32%
10.07.2017
with the original Raspberry Pi Model A, ranging from two to more than 250 nodes. That early 32-bit system had a single core running at 700MHz with 256MB of memory. You can build a cluster of five RPi3 nodes with 20
