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Anonymous
Not applicable

Disk recommendation / IOPS - throughput?

Hi All,

I need to give to the infrastructure team of my companies recommendation on the speed access to the disk for QlikView :

- QlikView Server

- Publisher

- Desktop.

a) For Desktop and Publisher, it's mainly big files read and written, so it's more straightforward. But if you have recommendation, please share them.

b) For QlikView Server it's a bit more complex as this impact the experience of the users : accessing the .shared to read/write bookmarks or objects. Is there any document that provide recommendation on this.

The only one I've got is the Technical Brief on SAN-NAS it's usefull but not detailed on iops/throughput or mesurable requirement.

Do you have any recommendation on this tricky one?

We will certainly use a NAS, if possible attached on a 10 Gb network, but I need to confirm that this will work, compared to a DAS.

Thank-you.

Stephane

4 Replies
sujeetsingh
Master III
Master III

I do not have any much idea but you can take help of this doc.

Anonymous
Not applicable
Author

Hi, Thank-you, I've read this one but it's not providing measurable disk access requirement.

How do you choose between different disk, disk solutions, mounting solution, networks, for the hardware?

Not applicable
Author

I have this same question.  I need some documentation around disk IOP requirements for QlikView Publisher.

hps
Employee
Employee

Hi Stephane,

Regarding SAN and NAS I assume you have read and are referring to the techincal paper titled:

"WHAT IS THE DIFFERENCE BETWEEN SAN AND NAS AND HOW CAN I USE THEM IN MY QLIKVIEW ENVIRONMENT?"

In general it is hard to give an estimation of I/O required as it depends on many factors.

For the shared/PGO files it is generally driven by number of concurrent users and QVS nodes in the cluster.

For Publisher has been shown in tests that for a single reload more than 100Mbit/s not required for straight QVD loads (optimized), but with many parallel reloads (concurrent QVBs) each might consume up to that point. Loading data non optimized and from SQL or other sources obviously reduces this requirement.

Regards,

Hampus von Post