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  • Python - Create a list with initial capacity

    - by Claudiu
    Code like this often happens: l = [] while foo: #baz l.append(bar) #qux This is really slow if you're about to append thousands of elements to your list, as the list will have to constantly be re-initialized to grow. (I understand that lists aren't just wrappers around some array-type-thing, but something more complicated. I think this still applies, though; let me know if not). In Java, you can create an ArrayList with an initial capacity. If you have some idea how big your list will be, this will be a lot more efficient. I understand that code like this can often be re-factored into a list comprehension. If the for/while loop is very complicated, though, this is unfeasible. Is there any equivalent for us python programmers?

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  • HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows?

    - by Chris Hoffman
    If you’ve ever purchased a computer with a hard disk capacity of 500 GB and opened Windows Explorer only to find that its capacity looked more like 440 GB, you may be wondering where all those gigabytes went. There are several reasons Windows could display the wrong amount of available space, from invisible shadow files, formatting overhead, and hidden recovery partitions to misleading (though technically accurate) storage capacities advertised by hard drive manufacturers. Image Credit: Norlando Pobre HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows? Java is Insecure and Awful, It’s Time to Disable It, and Here’s How What Are the Windows A: and B: Drives Used For?

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  • Windows 7 Reading Proper Disk Usage Statistics on Mounted Volumes

    - by Troy Perkins
    I'm running windows 7 with 2 x 1.5 TBYTE Drives. The second internal drive is setup as a mounted volume as C:\Archives Clicking computer icon in windows explorer, it only shows capacity stats for C: and Not C:\Archives Also, the usage stats that do show for C: show to be 100% capacity red - yet the system runs fine. No warnings. Can someone explain this? I do have a lot of stuff on the c: drive, but I'm sure its not 1.5 TB worth and C:\Archives hardly has anything it. Thanks! Troy

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  • Can I have 2Gbit over 1Gbit Nics

    - by Daniel
    So this really baffles me. Apparently because 1Gbit can transmit data in both directions simultaneously it should be possible to get 2Gbit of data transfer on a single NIC (1Gbit flow seend and 1Gbit receive). People claim that because 1Gbit is full-duplex (almost always) it is exactly 2Gbit in total. My intuition and electrical background tells me that something is not right here 4 twisted pairs 250Mbit capacity each gives 1Gbit. Unless it is really possible to transfer data in both directions simultaneously. I did a test with iperf. Ubuntu server 12.04 <-- MacBook Pro. Both with decent CPU speed. Tested speed of connection individually and on Mac I can see 112MB/s regardless which direction data is going. On Ubuntu with vnstat and ifstat I got 970Mbit speeds. Now, launching iperf in server mode on both machines at the same time and sending data using 2 iperf clients shows that I'm for example on Ubuntu box sending at 600Mbit, and receiving 350Mbit. which adds up to pretty much 1Gbit link. So to me there is no magical 2Gbit. Can someone confirm that or tell why I'm wrong? Another thing that confuses me i the fact that e.g. 24-port switch has for example: Throughput»up»to:»50.6Mpps Switching»capacity:»68Gbps Switch»fabric»speed:»88Gbps Which would suggest thay can handle 2GBit per port.

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  • AdWords Keyword Tool planner CPC completely different to real CPC?

    - by steve
    I'm new to AdWords, and trying to figure out the best keywords to use. I go to Adwords Keyword Planner, and typed in an example keyword. It gives me an average CPC of $0.94. But when I go to set up a real campaign and type it the same keyword, I get an error saying 'below first page bid estimate' which is $8.75. What gives? Is there a better way to get more accurate feedback on how much this will cost?

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  • resizing arrays when close to memory capacity

    - by user548928
    So I am implementing my own hashtable in java, since the built in hashtable has ridiculous memory overhead per entry. I'm making an open-addressed table with a variant of quadratic hashing, which is backed internally by two arrays, one for keys and one for values. I don't have the ability to resize though. The obvious way to do it is to create larger arrays and then hash all of the (key, value) pairs into the new arrays from the old ones. This falls apart though when my old arrays take up over 50% of my current memory, since I can't fit both the old and new arrays in memory at the same time. Is there any way to resize my hashtable in this situation Edit: the info I got for current hashtable memory overheads is from here How much memory does a Hashtable use? Also, for my current application, my values are ints, so rather than store references to Integers, I have an array of ints as my values.

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  • Why do ticket websites crash?

    - by Soloman Smart
    I hope this fits into the expanse of serverfault. Apologies if it doesn't. Why do ticket websites selling tickets for major concerts/events still crash when they make the tickets available? Surely, they know there is going to be huge demand and can ensure they have capacity to deal with that? May seem like a very simple question so sorry for those who understand! Thanks!

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  • How to get the correct battery status?

    - by GUI Junkie
    At this moment, ever since I installed Ubuntu on this machine, the battery status says: not present. Looking at this answer, however, I find that /proc/acpi/battery/BAT1/info (sometimes its /proc/acpi/battery/BAT0/info, use tab complete to help) has the following info: present: yes design capacity: 4400 mAh last full capacity: 4400 mAh battery technology: rechargeable design voltage: 11100 mV design capacity warning: 300 mAh design capacity low: 132 mAh cycle count: 0 capacity granularity 1: 32 mAh capacity granularity 2: 32 mAh model number: BAT1 serial number: 11 battery type: 11 OEM info: 11 In accordance to this answer, I've checked the /proc/acpi/battery/BAT1/state file: present: yes capacity state: ok charging state: charged present rate: unknown remaining capacity: unknown present voltage: 10000 mV The acpi -b command returns: Battery 0: Unknown, 0%, rate information unavailable Any suggestions on getting the battery info updated?

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  • Data Source Connection Pool Sizing

    - by Steve Felts
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} One of the most time-consuming procedures of a database application is establishing a connection. The connection pooling of the data source can be used to minimize this overhead.  That argues for using the data source instead of accessing the database driver directly. Configuring the size of the pool in the data source is somewhere between an art and science – this article will try to move it closer to science.  From the beginning, WLS data source has had an initial capacity and a maximum capacity configuration values.  When the system starts up and when it shrinks, initial capacity is used.  The pool can grow to maximum capacity.  Customers found that they might want to set the initial capacity to 0 (more on that later) but didn’t want the pool to shrink to 0.  In WLS 10.3.6, we added minimum capacity to specify the lower limit to which a pool will shrink.  If minimum capacity is not set, it defaults to the initial capacity for upward compatibility.   We also did some work on the shrinking in release 10.3.4 to reduce thrashing; the algorithm that used to shrink to the maximum of the currently used connections or the initial capacity (basically the unused connections were all released) was changed to shrink by half of the unused connections. The simple approach to sizing the pool is to set the initial/minimum capacity to the maximum capacity.  Doing this creates all connections at startup, avoiding creating connections on demand and the pool is stable.  However, there are a number of reasons not to take this simple approach. When WLS is booted, the deployment of the data source includes synchronously creating the connections.  The more connections that are configured in initial capacity, the longer the boot time for WLS (there have been several projects for parallel boot in WLS but none that are available).  Related to creating a lot of connections at boot time is the problem of logon storms (the database gets too much work at one time).   WLS has a solution for that by setting the login delay seconds on the pool but that also increases the boot time. There are a number of cases where it is desirable to set the initial capacity to 0.  By doing that, the overhead of creating connections is deferred out of the boot and the database doesn’t need to be available.  An application may not want WLS to automatically connect to the database until it is actually needed, such as for some code/warm failover configurations. There are a number of cases where minimum capacity should be less than maximum capacity.  Connections are generally expensive to keep around.  They cause state to be kept on both the client and the server, and the state on the backend may be heavy (for example, a process).  Depending on the vendor, connection usage may cost money.  If work load is not constant, then database connections can be freed up by shrinking the pool when connections are not in use.  When using Active GridLink, connections can be created as needed according to runtime load balancing (RLB) percentages instead of by connection load balancing (CLB) during data source deployment. Shrinking is an effective technique for clearing the pool when connections are not in use.  In addition to the obvious reason that there times where the workload is lighter,  there are some configurations where the database and/or firewall conspire to make long-unused or too-old connections no longer viable.  There are also some data source features where the connection has state and cannot be used again unless the state matches the request.  Examples of this are identity based pooling where the connection has a particular owner and XA affinity where the connection is associated with a particular RAC node.  At this point, WLS does not re-purpose (discard/replace) connections and shrinking is a way to get rid of the unused existing connection and get a new one with the correct state when needed. So far, the discussion has focused on the relationship of initial, minimum, and maximum capacity.  Computing the maximum size requires some knowledge about the application and the current number of simultaneously active users, web sessions, batch programs, or whatever access patterns are common.  The applications should be written to only reserve and close connections as needed but multiple statements, if needed, should be done in one reservation (don’t get/close more often than necessary).  This means that the size of the pool is likely to be significantly smaller then the number of users.   If possible, you can pick a size and see how it performs under simulated or real load.  There is a high-water mark statistic (ActiveConnectionsHighCount) that tracks the maximum connections concurrently used.  In general, you want the size to be big enough so that you never run out of connections but no bigger.   It will need to deal with spikes in usage, which is where shrinking after the spike is important.  Of course, the database capacity also has a big influence on the decision since it’s important not to overload the database machine.  Planning also needs to happen if you are running in a Multi-Data Source or Active GridLink configuration and expect that the remaining nodes will take over the connections when one of the nodes in the cluster goes down.  For XA affinity, additional headroom is also recommended.  In summary, setting initial and maximum capacity to be the same may be simple but there are many other factors that may be important in making the decision about sizing.

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  • passing back answers in prolog

    - by AhmadAssaf
    i have this code than runs perfectly .. returns a true .. when tracing the values are ok .. but its not returning back the answer .. it acts strangely when it ends and always return empty list .. uninstantiated variable .. test :- extend(4,12,[4,3,1,2],[[1,5],[3,4],[6]],_ExtendedBins). %printing basic information about the extend(NumBins,Capacity,RemainingNumbers,BinsSoFar,_ExtendedBins) :- getNumberofBins(BinsSoFar,NumberOfBins), msort(RemainingNumbers,SortedRemaining),nl, format("Current Number of Bins is :~w\n",[NumberOfBins]), format("Allowed Capacity is :~w\n",[Capacity]), format("maximum limit in bin is :~w\n",[NumBins]), format("Trying to fit :~w\n\n",[SortedRemaining]), format("Possible Solutions :\n\n"), fitElements(NumBins,NumberOfBins, Capacity,SortedRemaining,BinsSoFar,[]). %this is were the creation for possibilities will start %will check first if the number of bins allowed is less than then %we create a new list with all the possible combinations %after that we start matching to other bins with capacity constraint fitElements(NumBins,NumberOfBins, Capacity,RemainingNumbers,Bins,ExtendedBins) :- ( NumberOfBins < NumBins -> print('Creating new set: '); print('Sorry, Cannot create New Sets')), createNewList(Capacity,RemainingNumbers,Bins,ExtendedBins). createNewList(Capacity,RemainingNumbers,Bins,ExtendedBins) :- createNewList(Capacity,RemainingNumbers,Bins,[],ExtendedBins), print(ExtendedBins). createNewList(0,Bins,Bins,ExtendedBins,ExtendedBins). createNewList(_,[],_,ExtendedBins,ExtendedBins). createNewList(Capacity,[Element|Rest],Bins,Temp,ExtendedBins) :- conjunct_to_list(Element,ListedElement), append(ListedElement,Temp,NewList), sumlist(NewList,Sum), (Sum =< Capacity, append(ListedElement,ExtendedBins,Result); Capacity = 0), createNewList(Capacity,Rest,Bins,NewList,Result). fit(0,[],ExtendedBins,ExtendedBins). fit(Capacity,[Element|Rest],Bin,ExtendedBins) :- conjunct_to_list(Element,Listed), append(Listed,Bin,NewBin), sumlist(NewBin,Sum), (Sum =< Capacity -> fit(Capacity,Rest,NewBin,ExtendedBins); Capacity = 0, append(NewBin,ExtendedBins,NewExtendedBins), print(NewExtendedBins), fit(0,[],NewBin,ExtendedBins)). %get the number of bins provided getNumberofBins(List,NumberOfBins) :- getNumberofBins(List,0,NumberOfBins). getNumberofBins([],NumberOfBins,NumberOfBins). getNumberofBins([_List|Rest],TempCount,NumberOfBins) :- NewCount is TempCount + 1, %calculate the count getNumberofBins(Rest,NewCount,NumberOfBins). %recursive call %Convert set of terms into a list - used when needed to append conjunct_to_list((A,B), L) :- !, conjunct_to_list(A, L0), conjunct_to_list(B, L1), append(L0, L1, L). conjunct_to_list(A, [A]). Greatly appreciate the help

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  • Initial capacity of collection types, i.e. Dictionary, List

    - by Neil N
    Certain collection types in .Net have an optional "Initial Capacity" constructor param. i.e. Dictionary<string, string> something = new Dictionary<string,string>(20); List<string> anything = new List<string>(50); I can't seem to find what the default initial capacity is for these objects on MSDN. If I know I will only be storing 12 or so items in a dictionary, doesn't it make sense to set the initial capacity to something like 20? My reasoning is, assuming the capacity grows like it does for a StringBuiler, which doubles each time the capacity is hit, and each re-allocation is costly, why not pre-set the size to something you know will hold your data, with some extra room just in case? If the initial capacity is 100, and I know I will only need a dozen or so, it seems as though the rest of that allocated RAM is allocated for nothing. Please spare me the "premature optimization" speil for the O(n^n)th time. I know it won't make my apps any faster or save any meaningful amount of memory, this is mostly out of curiosity.

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  • Netbook performs hard shutdown without warning on low battery power

    - by Steve Kroon
    My Asus EEE netbook performs a hard shutdown when it reaches low battery power, without giving any warning - i.e. the power just goes off, without any shutdown process. I can't find anything in the syslog, and no error messages are printed before it happens. I've had this problem on previous (K)Ubuntu versions, and hoped updating to Ubuntu Precise would help resolve the issue, but it hasn't. The option in the Power application for "when power is critically low" is currently blank - the only options are a (grayed-out) hibernate and "Power off". I have re-installed indicator-power to no effect. The time remaining reported by acpi is unstable, as is the time remaining reported by gnome-power-statistics. (For example, running acpi twice in succession, I got 2h16min, and then 3h21min remaining. These sorts of jumps in the remaining time are also in the gnome-power-statistics graphs.) It might be possible to write a script to give me advance warning (as per @RanRag's comment below), but I would prefer to isolate why I don't get a critical battery notification from the system before this happens, so that I can take action as appropriate (suspend/shutdown/plug in power) when I get a notification. Some additional information on the battery: kroon@minia:~$ upower -i /org/freedesktop/UPower/devices/battery_BAT0 native-path: /sys/devices/LNXSYSTM:00/device:00/PNP0A08:00/PNP0C0A:00/power_supply/BAT0 vendor: ASUS model: 1005P power supply: yes updated: Fri Aug 17 07:31:23 2012 (9 seconds ago) has history: yes has statistics: yes battery present: yes rechargeable: yes state: charging energy: 33.966 Wh energy-empty: 0 Wh energy-full: 34.9272 Wh energy-full-design: 47.52 Wh energy-rate: 3.7692 W voltage: 12.61 V time to full: 15.3 minutes percentage: 97.248% capacity: 73.5% technology: lithium-ion History (charge): 1345181483 97.248 charging 1345181453 97.155 charging 1345181423 97.062 charging 1345181393 96.970 charging History (rate): 1345181483 3.769 charging 1345181453 3.899 charging 1345181423 4.061 charging 1345181393 4.201 charging kroon@minia:~$ cat /proc/acpi/battery/BAT0/state present: yes capacity state: ok charging state: charging present rate: 332 mA remaining capacity: 3149 mAh present voltage: 12612 mV kroon@minia:~$ cat /proc/acpi/battery/BAT0/info present: yes design capacity: 4400 mAh last full capacity: 3209 mAh battery technology: rechargeable design voltage: 10800 mV design capacity warning: 10 mAh design capacity low: 5 mAh cycle count: 0 capacity granularity 1: 44 mAh capacity granularity 2: 44 mAh model number: 1005P serial number: battery type: LION OEM info: ASUS

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  • What happens to the storage capacity when I uninstall Ubuntu?

    - by shole1202
    I used the wubi installer for Ubuntu 12.04. After having trouble with getting the Operating System to boot, I tried uninstalling it with wubi. From 'My Computer' (in Windows 7), I noticed the maximum capacity of my hard drive drop from 256gb to 238gb. I have tried using some methods with the command prompt to locate the missing storage, but Windows now only recognizes that the storage on the disk to have 238gb instead of the original 256. Is there any way to recover that memory?

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  • Maximum number of files in one ext3 directory while still getting acceptable performance?

    - by knorv
    I have an application writing to an ext3 directory which over time has grown to roughly three million files. Needless to say, reading the file listing of this directory is unbearably slow. I don't blame ext3. The proper solution would have been to let the application code write to sub-directories such as ./a/b/c/abc.ext rather than using only ./abc.ext. I'm changing to such a sub-directory structure and my question is simply: roughly how many files should I expect to store in one ext3 directory while still getting acceptable performance? What's your experience? Or in other words; assuming that I need to store three million files in the structure, how many levels deep should the ./a/b/c/abc.ext structure be? Obviously this is a question that cannot be answered exactly, but I'm looking for a ball park estimate.

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  • how much more memcache memory do i need to get 95% hit ratio? [on hold]

    - by OneSolitaryNoob
    I have a memcache instance running that has a 90% hit ratio. How can I estimate how much more memory it needs to get to a 95% hit ratio? edit: This question was blocked, but I do not think this is impossible to answer. After all, anyone that's used a caching system HAS answered this question, most likely with trial&error&luck. I can look at my usage patterns. I can increase or decrease memory and see how hit rate changes. Both of these provide data that informs an estimate. But what's a good/better/best way to do this?

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  • Is it possible create a 4TB bootable partition in the x86 edition of Windows Server 2003 Enterprise?

    - by Giffyguy
    I'd like to find out if there is any way to accomplish this, since it would benifit my storage server greatly. I am using a Promise FastTrak 8660 and five Seagate ST31000340NS 1TB drives in a RAID 5 array. I figure that if the x86 ENTERPRISE edition of Server 2003 can handle 64GB of RAM, it should have no problem supporting larger HDD volumes as well. I've read (somewhere...) that the Windows Server operating systems are not limited to the standard 2TB like Windows XP and 2000 are. I'm hoping it's something that just needs to be turned on, similar to the way PAE works for the 4GB RAM limit in x86 servers.

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  • HPC Cluster planning workflow?

    - by Veronica
    After three days of intensive Google searching, I have not found any high-level workflow of how to build a low profile - cheap - computing cluster (we are not interested in HA yet). This is just a front-end plus a node for now. We want to start small with rockscluster, provide a web-based server for offering services, and then add nodes as our budget increases. We're small company, so we haven't enough human resources to implement it smoothly. Here are some facts about our environment: Our hardware is not constant (we will add nodes). Our workload will vary (in the order from 200Mb - 1Tb) Our software will change (scientific applications for data mining) Do you know any visual workflow, worksheet, chart, describing the general necessary steps to begin our cluster planning?

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  • Increasing a Linux partition once VM size increased in vSphere?

    - by dannymcc
    I have a Ubuntu 12.04 VM running on VMWares ESXi 5.1. The server (VM) itself has run out of space, the results of df -h are as follows: Filesystem Size Used Avail Use% Mounted on /dev/sda1 19G 17G 1.2G 94% / udev 490M 4.0K 490M 1% /dev tmpfs 200M 232K 199M 1% /run none 5.0M 0 5.0M 0% /run/lock none 498M 0 498M 0% /run/shm The original VM HDD size was just under 19GB which is I have now increased to 100GB within the vCenter GUI: Is there a simple way of doing this? The VM doesn't seem to acknowledge the increase at all.

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  • What disk setup is needed / best practice for hypervisor-only servers?

    - by Luke404
    Planning to buy some servers to run an hypervisor (Citrix XenServer or VMware vSphere, still have to decide between the two) we'd like to boot off the local redundant SD card module offered by various vendors (eg. Dell, HP, etc...). The actual VMs will run from an existing iSCSI SAN (which, by the way, can't support booting the servers directly off the SAN). What are the reasons, if any, to choose completely diskless servers VS having some local storage? And what would be the guidelines to choose that local storage? (number of spindles, raid level, etc)

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  • MongoDB and datasets that don't fit in RAM no matter how hard you shove

    - by sysadmin1138
    This is very system dependent, but chances are near certain we'll scale past some arbitrary cliff and get into Real Trouble. I'm curious what kind of rules-of-thumb exist for a good RAM to Disk-space ratio. We're planning our next round of systems, and need to make some choices regarding RAM, SSDs, and how much of each the new nodes will get. But now for some performance details! During normal workflow of a single project-run, MongoDB is hit with a very high percentage of writes (70-80%). Once the second stage of the processing pipeline hits, it's extremely high read as it needs to deduplicate records identified in the first half of processing. This is the workflow for which "keep your working set in RAM" is made for, and we're designing around that assumption. The entire dataset is continually hit with random queries from end-user derived sources; though the frequency is irregular, the size is usually pretty small (groups of 10 documents). Since this is user-facing, the replies need to be under the "bored-now" threshold of 3 seconds. This access pattern is much less likely to be in cache, so will be very likely to incur disk hits. A secondary processing workflow is high read of previous processing runs that may be days, weeks, or even months old, and is run infrequently but still needs to be zippy. Up to 100% of the documents in the previous processing run will be accessed. No amount of cache-warming can help with this, I suspect. Finished document sizes vary widely, but the median size is about 8K. The high-read portion of the normal project processing strongly suggests the use of Replicas to help distribute the Read traffic. I have read elsewhere that a 1:10 RAM-GB to HD-GB is a good rule-of-thumb for slow disks, As we are seriously considering using much faster SSDs, I'd like to know if there is a similar rule of thumb for fast disks. I know we're using Mongo in a way where cache-everything really isn't going to fly, which is why I'm looking at ways to engineer a system that can survive such usage. The entire dataset will likely be most of a TB within half a year and keep growing.

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  • vSphere education - What are the downsides of configuring virtual machines with *too* much RAM?

    - by ewwhite
    VMware memory management seems to be a tricky balancing act. With cluster RAM, Resource Pools, VMware's management techniques (TPS, ballooning, host swapping), in-guest RAM utilization, swapping, reservations, shares and limits, there are a lot of variables. I'm in a situation where clients are using dedicated vSphere cluster resources. However, they are configuring the virtual machines as though they were on physical hardware. In turn, this means a standard VM build may have 4 vCPUs and 16GB or more of RAM. I come from the school of starting small (1 vCPU, minimal RAM), checking real-world use and adjusting up as necessary. Some examples from a "problem" cluster. Resource pool summary - Looks almost 4:1 overcommitted. Note the high amount of ballooned RAM. Resource allocation - The Worst Case Allocation column shows that these VMs would have access to less than 50% of their configured RAM under constrained conditions. The real-time memory utilization graph of the top VM in the listing above. 4 vCPU and 64GB RAM allocated. It averages under 9GB use. Summary of the same VM What are the downsides of overcommitting and overconfiguring resources (specifically RAM) in vSphere environments? Assuming that the VMs can run in less RAM, is it fair to say that there's overhead to configuring virtual machines with more RAM than they need? What is the counter-argument to: "if a VM has 16GB of RAM allocated, but only uses 4GB, what's the problem??"? E.g. do customers need to be educated? What specific metric should be used to meter RAM usage. Tracking the peaks of "Active" versus time?

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  • Why aren't there 8gb RAM modules yet?

    - by user49951
    Why is RAM module development seemingly stuck at the same size for a while now (a couple of years)? I bought 2x2gb modules 2 years ago, and now it's all the same size, with prices even bigger. I want more memory, because I work a lot on my computer and I just need it. What is going on? Hardware/memory progress was being made constantly until these couple of years, and I'm a big computer user for over 15 years. Why isn't here 4gb/8gb modules yet? I would gladly replace my DDR2 motherboard for a DDRX one if it had at least 4gb DDRX modules for a reasonable price. Now we have a situation with very cheap usb drives reaching 64gb size, and a ram modules with pathetic 2gb size. Sounds like some sort of conspiracy.

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  • How many websites can my server potentially hold?

    - by Daniel Kindler
    Sorry for the "noob" question, but... About how many medium-sized websites with average traffic could this server hold? Just like the average website, kind of like a small business site. How many sites could this server hold, but still maintain nice, decent speed? PowerEdge R510 PE R510 Chassis for Up to Four 3.5" Cabled Hard Drives, LED edit Processor Intel® Xeon® E5630 2.53Ghz, 12M Cache,Turbo, HT, 1066MHz Max Mem edit Memory 8GB Memory (4x2GB), 1333MHz Single Ranked UDIMMs for 1 Procs, Optimized edit Operating System SUSE Linux Enterprise Server 10, SP3, Up To 32 CPU Lic, 1 YR Sub, DIB, Media edit Red Hat Enterprise Linux Licensing Hard Drives 250GB 7.2K RPM SATA 3.5" Cabled Hard Drive edit Hard Drives 1TB 7.2K RPM SATA 3.5" Cabled Hard Drive edit Hard Drives 2 X 2TB 7.2K RPM SATA 3.5in Cabled Hard Drive Hard Drive Configuration No RAID, Embedded SATA Controller for x4 Chassis edit Power Supply 480 Watt Non-Redundant Power Supply edit Thank you!

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