search for: 4mil

...ouple (6) of relatively large datasets (min of 200.000 and max of 2mil rows). I have now been able to do so, however I think something might be going wrong in my codes. For reference, i have a dataset 1 (200.000), dataset 2 (600.000), dataset 3 (2mil) and dataset 4 (2mil) merged into one dataset of 4mil, and dataset 5 (4mil) and dataset 6 (4mil) merged into one dataset of 8mil. What i have done so far is the following: * Merged dataset 1 and dataset 2 using the following code = merged 1 <- dataset 2[dataset 1, nomatch = NA]. This results in a dataset of 600.000 (looks to be alright). *...

...ouple (6) of relatively large datasets (min of 200.000 and max of 2mil rows). I have now been able to do so, however I think something might be going wrong in my codes. For reference, i have a dataset 1 (200.000), dataset 2 (600.000), dataset 3 (2mil) and dataset 4 (2mil) merged into one dataset of 4mil, and dataset 5 (4mil) and dataset 6 (4mil) merged into one dataset of 8mil. What i have done so far is the following: * Merged dataset 1 and dataset 2 using the following code = merged 1 <- dataset 2[dataset 1, nomatch = NA]. This results in a dataset of 600.000 (looks to be alright). *...

...e (6) of relatively large datasets (min of 200.000 and max of 2mil rows). I have now been able to do so, however I think something might be going wrong in my codes. >For reference, i have a dataset 1 (200.000), dataset 2 (600.000), dataset 3 (2mil) and dataset 4 (2mil) merged into one dataset of 4mil, and dataset 5 (4mil) and dataset 6 (4mil) merged into one dataset of 8mil. >What i have done so far is the following: > > * Merged dataset 1 and dataset 2 using the following code = merged 1 <- dataset 2[dataset 1, nomatch = NA]. This results in a dataset of 600.000 (looks to be alr...

...ung -> 4, 1, 3 all jungle -> 4, *3, *1 Which for our purposes is returning non-matching results (marked with an asterisk). If we switch to using the QUERY_PHRASE flag, we avoid the extraneous results, but we lose the partial results. Also, with a large database (4mil documents) the first query takes an incredibly long time. One idea is to add all possible incomplete versions of each term to the document's term list. For the term 'welcome' we'd also add 'Sw', 'Swe', 'Swel' ... 'Swelcome'. That way we can adjust...

I suspect the standard optimisation - breaking up the rsync into smaller batches - is not going to work for us. This is our situation: We rsync two directories in /spool to a backup. They are large: almost 2mil files in the first dir, with about 4mil hard links in the second one linking to them. The files don't change much; a few thousand added daily, and with about 3 hard links created for each. Another few hundred might be deleted or changed. We use rsync -a -H --delete This worked very well at first, but since reaching 1mil files perf...

This is problem 1 of 3 problems we are having with live migration and/or ACPI on Xen-4.3 and Xen-4.2. Any help would be appreciated. Detailed description of problem: We are using Xen-4.3-rc1 with dom0 running Ubuntu Precise and 3.5.0-23-generic kernel, and domU running Ubuntu Precise (12.04) cloud images running 3.2.0-39-virtual. We are using the xl.conf below on qemu-upstream-dm and HVM and