11-21-2011
So let me get this straight. You detached mirrors and patched the server 40 days ago. For 40 days the server was running with patched version of the operation system, correct? Then today you found out that the applications are not really working properly with the patched system (after using it for 40 days) correct? So you booted second disk today, which contains the system as it was 40 days ago, right?
10 More Discussions You Might Find Interesting
1. Solaris
Hi All,
I have to remove the disk from SVM.
Kindly guide me or suggest me some link where in I can steps to remove SVM from Solaris 10 .Also I have one metaset which require deletion.
Thanks in anticipation! (10 Replies)
Discussion started by: kumarmani
10 Replies
2. Solaris
gurus,
i have configured the LUN's in solaris 10.after labeled the disk,i have added the disk into one of the soft partition using metattach d0 c5t1000d10s6.actully before that i should confiure the powermt and than i should have add metattch d0 emcpowerc2.i forget to do that and increased... (0 Replies)
Discussion started by: rjay.com
0 Replies
3. Solaris
Really sorry for the long posting. But i would really want to clear all the doubts.
I have 2 disk c0t0d0 & c0t1d0, i wanted to mirror c0t1d0 (mirror) to c0t0d0 (main).
Creating state database replica:
metadb -a -c3 -f c0t0d0s7
... (3 Replies)
Discussion started by: beginningDBA
3 Replies
4. Solaris
I am trying to set up a new server. It has 8 HD's in it. I am using 2 for the system disk. IE set one up mirror to the other. I am using the other 6 as data disks. For those I want to concat 3 together, mirror to the other 3 (also concated together of course) and then make various soft... (7 Replies)
Discussion started by: NewSolarisAdmin
7 Replies
5. UNIX for Dummies Questions & Answers
i have taken two separate disk
A and B
created 4 slices in each
A b
s4 s4
s5 s5
s6 s6
s7 s7
took slices s4 of A and slice s6 0f B ---created a meta device d0
took slices s4 of B and slice s6 0f A---created a meta device d1
created main mirror d2 using d0... (1 Reply)
Discussion started by: vivek_ng
1 Replies
6. Solaris
HI,
I added by error to a submirror some disks :
metattach d53 c2t90d0s0 c2t90d1s0 ... instead of doing a stripe by disk (like that) :
metattach d53 c2t90d0s0
metattach d53 c2t90d1s0
..
then, I did a growfs -M to expand FS and the size isn't correct.
I tried to launch a... (1 Reply)
Discussion started by: phil.nakache
1 Replies
7. UNIX for Advanced & Expert Users
How to list out multiple Disk sets in SVM
# metaset -s <disksetname> --- This will list out only one diskset
but I need a list of disk sets configured for the node.
Is there any command,please let me know ...
Thanks in advance. (1 Reply)
Discussion started by: pramath
1 Replies
8. UNIX for Advanced & Expert Users
Hi All,
I want to know what is the Interlace value in SVM and what is the need of this ?
regards,
prashant (1 Reply)
Discussion started by: prashant2507198
1 Replies
9. Solaris
Hello
I want to ask that how to mount and run fsck in SVM disk.In my scenario if i have to disks c0t0d0 and c0t1d0 these two disks are in Mirroring (raid1) if i want to run fsck on the disks than below are the right steps?
ok boot cdrom -s
mount /dev/dsk/c0t0d0s0 /a
cd /a
fsck... (3 Replies)
Discussion started by: jhonnybravo
3 Replies
10. Solaris
Dear All,
I face some errors in SVM.Need help.
Actually couple of days ago i got a call from one of the customer mentioning that one of the sub-mirror was in Need maintance state. So we replaced that disk. After Replacing the disk it comes back to "Okay" State.
But the Error are... (3 Replies)
Discussion started by: sudhansu
3 Replies
LEARN ABOUT DEBIAN
svm-train
svm-train(1) User Manuals svm-train(1)
NAME
svm-train - train one or more SVM instance(s) on a given data set to produce a model file
SYNOPSIS
svm-train [-s svm_type ] [ -t kernel_type ] [ -d degree ] [ -g gamma ] [ -r coef0 ] [ -c cost ] [ -n nu ] [ -p epsilon ] [ -m cachesize ] [
-e epsilon ] [ -h shrinking ] [ -b probability_estimates ] ] [ -wi weight ] [ -v n ] [ -q ]
training_set_file [ model_file ]
DESCRIPTION
svm-train trains a Support Vector Machine to learn the data indicated in the training_set_file
and produce a model_file
to save the results of the learning optimization. This model can be used later with svm_predict(1) or other LIBSVM enabled software.
OPTIONS
-s svm_type
svm_type defaults to 0 and can be any value between 0 and 4 as follows:
0 -- C-SVC
1 -- nu-SVC
2 -- one-class SVM
3 -- epsilon-SVR
4 -- nu-SVR
-t kernel_type
kernel_type defaults to 2 (Radial Basis Function (RBF) kernel) and can be any value between 0 and 4 as follows:
0 -- linear: u.v
1 -- polynomial: (gamma*u.v + coef0)^degree
2 -- radial basis function: exp(-gamma*|u-v|^2)
3 -- sigmoid: tanh(gamma*u.v + coef0)
4 -- precomputed kernel (kernel values in training_set_file) --
-d degree
Sets the degree of the kernel function, defaulting to 3
-g gamma
Adjusts the gamma in the kernel function (default 1/k)
-r coef0
Sets the coef0 (constant offset) in the kernel function (default 0)
-c cost
Sets the parameter C ( cost ) of C-SVC, epsilon-SVR, and nu-SVR (default 1)
-n nu Sets the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
-p epsilon
Set the epsilon in the loss function of epsilon-SVR (default 0.1)
-m cachesize
Set the cache memory size to cachesize in MB (default 100)
-e epsilon
Set the tolerance of termination criterion to epsilon (default 0.001)
-h shrinking
Whether to use the shrinking
heuristics, 0 or 1 (default 1)
-b probability-estimates
probability_estimates is a binary value indicating whether to calculate probability estimates when training the SVC or SVR model.
Values are 0 or 1 and defaults to 0 for speed.
-wi weight
Set the parameter C (cost) of class i to weight*C, for C-SVC (default 1)
-v n Set n for n -fold cross validation mode
-q quiet mode; suppress messages to stdout.
FILES
training_set_file must be prepared in the following simple sparse training vector format:
<label> <index1>:<value1> <index2>:<value2> . . .
.
.
.
There is one sample per line. Each sample consists of a target value (label or regression target) followed by a sparse representation of
the input vector. All unmentioned coordinates are assumed to be 0. For classification, <label> is an integer indicating the class label
(multi-class is supported). For regression, <label> is the target value which can be any real number. For one-class SVM, it's not used so
can be any number. Except using precomputed kernels (explained in another section), <index>:<value> gives a feature (attribute) value.
<index> is an integer starting from 1 and <value> is a real number. Indices must be in an ASCENDING order.
ENVIRONMENT
No environment variables.
DIAGNOSTICS
None documented; see Vapnik et al.
BUGS
Please report bugs to the Debian BTS.
AUTHOR
Chih-Chung Chang, Chih-Jen Lin <cjlin@csie.ntu.edu.tw>, Chen-Tse Tsai <ctse.tsai@gmail.com> (packaging)
SEE ALSO
svm-predict(1), svm-scale(1)
Linux MAY 2006 svm-train(1)