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CEPH + Librados++ is not returning consisten results


CEPH + Librados++ is not returning consisten results

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CEPH + Librados++ is not returning consisten results
Tag : cpp , By : Marc Dong
Date : November 28 2020, 04:01 AM

it fixes the issue The Ceph bufferlist structure is not actually NULL-terminated, even if you invoke the c_str() function. (Sorry about that bad design!)
So when you invoke bufferlist::c_str() and give it to a string constructor, it is going to be of arbitrary length until the first random NULL byte following it. You can fix this by getting the length and setting it explicitly when constructing the string.

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CEPH + Librados++ is not returning consisten results , C# and JavaScript results from same regular expression string are very different - how can I make results more consisten , Ceph gatherkeys KeyNotFoundError: Could not find keyring file: /etc/ceph/ceph.client.admin.keyring on host node1 , Consisten res ,

C# and JavaScript results from same regular expression string are very different - how can I make results more consisten

Tag : chash , By : Jet Thompson
Date : March 29 2020, 07:55 AM
it fixes the issue your .+ is being greedy. Try using .+? and make it lazy so that it grabs the least amount possible. This way it will grab the first

Ceph gatherkeys KeyNotFoundError: Could not find keyring file: /etc/ceph/ceph.client.admin.keyring on host node1

Tag : development , By : Cenneca
Date : March 29 2020, 07:55 AM
I wish this helpful for you It has been happened because in the ceph.conf you must set mon ip in the public network not in the private. And I had mon ip : 192.168.57.101 (which is the private) but public network was: 10.0.2.0/24.

Consisten results with Multiple runs of h2o deeplearning

Tag : r , By : Vrki
Date : March 29 2020, 07:55 AM
To fix this issue Deeplearning with H2O will not be reproducible if it is run on more than a single core. The results and performance metrics may vary slightly from what you see each time you train the deep learning model. The implementation in H2O uses a technique called "Hogwild!" which increases the speed of training at the cost of reproducibility on multiple cores.
So if you want reproducible results you will need to restrict H2O to run on a single core and make sure to use a seed in the h2o.deeplearning call.

Ceph-deploy is not creating ceph.bootstrap-rbd.keyring file

Tag : development , By : Epora75
Date : March 29 2020, 07:55 AM
will be helpful for those in need It is not important. Because rbd is native service for ceph. Do not worry about that

How to create Ceph Filesystem after Ceph Object Storage Cluster Setup?

Tag : development , By : Ron
Date : March 29 2020, 07:55 AM
I think the issue was by ths following , hi your install not Standard please read a below link very helpfull for install ceph:
http://docs.ceph.com/docs/master/start/quick-ceph-deploy/
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