Thanks for the reply . i am not using a backing file. My concern is growing file system. The performance of 64K is better than 1M , 2M or 32K
Is the degrade in performance is only due to allocation of large cluster during expansion of qcow2 image ? But the trend is same in case of Sequential write Random write of 1 GB data In random i can understand the sparseness of data But in sequential write I don't understand as the write is performed on sequential bases is there is any reason behind it or i am not getting it right ? On Thu, Feb 23, 2012 at 2:02 PM, Stefan Hajnoczi <stefa...@gmail.com> wrote: > On Thu, Feb 23, 2012 at 11:01:46AM +0530, PANKAJ RAWAT wrote: > > I theory regarding cluster size it is written that as the size of > cluster > > increase performance should increase. > > > > But something surprising happen The performance is degrading as the size > of > > cluster increased from 64K to 1M ( during expansion of qcow2 image) > > It's not true that performance should increase by raising the cluster > size, otherwise the default would be infinity. It's an algorithms/data > structure trade-off. > > Most importantly is the relative latency between a small guest I/O > request (e.g. 4 KB) and the cluster size (e.g. 64 KB). If the cluster > size latency is orders of magnitude larger than a small guest I/O > request, then be prepared to see extreme effects described below: > > * Bigger clusters decrease the frequency of metadata operations and > increase metadata cache hit rates. Bigger clusters means less > metadata so qcow2 performs fewer metadata operations overall. > > Performance boost. > > * Bigger clusters increase the cost of allocating a new cluster. For > example, a 8 KB write to a new cluster will incur a 1 MB write to the > image file (the untouched regions are filled with zeros). This can > be optimized in some cases but not everywhere (e.g. reallocating a > data cluster versus extending the image file size and relying on the > file system to provide zeroed space). This is especially expensive > when a backing file is in use because up to 1 MB of the backing file > needs to be read to populate the newly allocated cluster! > > Performance loss. > > * Bigger clusters can reduce fragmentation of data on the physical > disk. The file system sees fewer, bigger allocating writes and is > therefore able to allocate more contiguous data - less fragmentation. > > Performance boost. > > * Bigger clusters reduce the compactness of sparse files. you use more > image file space on the host file system when the cluster size is > large. > > Space efficiency loss. > > Here's a scenario where a 1 MB cluster size is great compared to a large > cluster size: > > You have a fully allocated qcow2 image, you will never need to do any > allocating writes. > > Here's a scenario where a 1 MB cluster size is terrible compared to a > small cluster size: > > You have an empty qcow2 file and perform 4 KB writes to the first sector > of each 1 MB chunk, and there is a backing file. > > So it depends on the application. > > Stefan > -- *Pankaj Rawat*
