19%
21.08.2012
with the compute node:
[root@test1 ~]# pbsnodes -a
n0001
state = free
np = 3
ntype = cluster
status = rectime=1343594239,varattr=,jobs=,state=free,netload=118255091,gres=,loadave=0.02,ncpus=3
19%
18.07.2013
]. The new SPDY protocol is implemented in Nginx version 1.3.15 and will probably be integrated into the stable version 1.4, which is expected in May. (A SPDY patch is available for older versions of the 1.3
19%
31.10.2025
kernel
sles:~ # grep crash /proc/cmdline
root=/dev/disk/by-uuid/10a83ffe-5a9f-48a2-b8cb-551c2cc6b42d resume=/dev/sda3 splash=silent text showopts crashkernel=128
sles:~ # /etc/init.d/boot.kdump status
19%
07.10.2014
summary of the status of the system. Let me explain with an example. Figure 1 is a screen shot of my desktop when I was running Python code test3.py (a long-running processor- and memory-intensive piece
19%
14.08.2017
to manage them disappeared.
Container Linux ruthlessly replaces the entire /usr directory instead of individual files (Figure 3). The main work is handled by Linux containers à la Docker [20], or Rkt [21
19%
11.02.2016
+----------------------------------+---------+---------------------+
40 | 47e0142a3638fdc24fe40d4e4fbce3f1 | Row 1 | 2015-09-13 15:24:12 |
41 | b833c1e4c5bfc47d0dbe31c2e3f30837 | Row 3 | 2015-09-13 15:24:14 |
42 | c7d46523a316de4e1496c65c3cbdf358 | Row 2 | 2015
19%
30.11.2025
existing backups, enter:
burp -a l -b a
Of course, more complex queries are also possible. For example,
burp -a l -b 3 -r
lists all of the files in backup 3 that match the "regular
19%
02.02.2021
5221548db 58 seconds ago 5.67MB
80dc7d447a48 About a minute ago 167MB
alpine 3.9 78a2ce922f86 5 months ago 5.55MB
The command you really
19%
29.09.2020
-amd64.tar.gz.sha256sum
[...snip]
e6be589df85076108c33e12e60cfb85dcd82c5d756a6f6ebc8de0ee505c9fd4c helm-v3.1.2-linux-amd64.tar.gz
$ sha256sum helm-v3.1.2-linux-amd64.tar.gz
e6be589df85076108c33e12e60cfb85
19%
19.06.2023
object
O
Python object
A simple example from nkmk creates a float64
data type (64-bit floating-point number):
import numpy as np
a = np.array([1, 2, 3], dtype=np.float64
