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  • raid advice with SSD and two HDD

    - by Nin
    I have a new machine with one 128GB SSD and two 1TB HDD. On the SSD is the OS and my initial thought was to put the two HDD in RAID 1 for user data. After some more thought I came up with two other setups and now I'm in doubt :) Can someone advise what would be the best setup? 1: single SSD and HDD in RAID 1 (original thought) 2: Create 2 partitions on the HDD (128GB and 872GB). Put the two 872GB in RAID 1 and create another RAID 1 with the SSD and one 128GB HDD partition. 3: Create 2 partitions on the HDD (750/250), put the 705GB in RAID 1 and use the 2 250GB as backup and make automatic snapshots of the SSD to (one of) these partitions. I think the 2 main questions are: Is it advisable to create a raid array with only part of a drive and actively use the other part of that drive or should you always use the full disk? Is it advisable to create a raid 1 array with a SSD and HDD or will that blow the whole speed advantage of the SSD?

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  • Rails 3 - raw/html_safe not working in some cases?

    - by Frexuz
    I'm having difficulties with output not being encoded even though I'm using raw or html_safe. This one is writing out the &nbsp in my final HTLM page. def build_tag_cloud(tag_cloud, style_list) tag_cloud.sort!{ |x,y| x.permalink <=> y.permalink } max, min = 0, 0 tag_cloud.each do |tag| max = tag.followers.to_i if tag.followers.to_i > max min = tag.followers.to_i if tag.followers.to_i < min end divisor = ((max - min) / style_list.size) + 1 html = "" tag_cloud.each do |tag| name = raw(tag.name.gsub('&','&amp;').gsub(' ','&nbsp;')) link = raw(link_to "#{name}", {:controller => "/shows", :action => "show", :permalink => tag.permalink}, :class => "#{style_list[(tag.followers.to_i - min) / divisor]}") html += raw("<li>#{link}</li> ") end return raw(html.to_s) end What is allowed in using raw and html_safe? And how should my example above be fixed?

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  • Why does BeginReceiveFrom never time out?

    - by James Hugard
    I am writing an asynchronous Ping using Raw Sockets in F#, to enable parallel requests using as few threads as possible ("System.Net.NetworkInformation.Ping" appears to use one thread per request, but have not tested this... also am interested in using F# async workflows). The synchronous version below correctly times out when the target host does not exist/respond, but the asynchronous version hangs. Both work when the host does respond... Any ideas? (note: the process must run as Admin for this code to work) This throws a timeout: let result = Ping.Ping ( IPAddress.Parse( "192.168.33.22" ), 1000 ) However, this hangs: let result = Ping.PingAsync ( IPAddress.Parse( "192.168.33.22" ), 1000 ) |> Async.RunSynchronously Here's the code... module Ping open System open System.Net open System.Net.Sockets open System.Threading //---- ICMP Packet Classes type IcmpMessage (t : byte) = let mutable m_type = t let mutable m_code = 0uy let mutable m_checksum = 0us member this.Type with get() = m_type member this.Code with get() = m_code member this.Checksum = m_checksum abstract Bytes : byte array default this.Bytes with get() = [| m_type m_code byte(m_checksum) byte(m_checksum >>> 8) |] member this.GetChecksum() = let mutable sum = 0ul let bytes = this.Bytes let mutable i = 0 // Sum up uint16s while i < bytes.Length - 1 do sum <- sum + uint32(BitConverter.ToUInt16( bytes, i )) i <- i + 2 // Add in last byte, if an odd size buffer if i <> bytes.Length then sum <- sum + uint32(bytes.[i]) // Shuffle the bits sum <- (sum >>> 16) + (sum &&& 0xFFFFul) sum <- sum + (sum >>> 16) sum <- ~~~sum uint16(sum) member this.UpdateChecksum() = m_checksum <- this.GetChecksum() type InformationMessage (t : byte) = inherit IcmpMessage(t) let mutable m_identifier = 0us let mutable m_sequenceNumber = 0us member this.Identifier = m_identifier member this.SequenceNumber = m_sequenceNumber override this.Bytes with get() = Array.append (base.Bytes) [| byte(m_identifier) byte(m_identifier >>> 8) byte(m_sequenceNumber) byte(m_sequenceNumber >>> 8) |] type EchoMessage() = inherit InformationMessage( 8uy ) let mutable m_data = Array.create 32 32uy do base.UpdateChecksum() member this.Data with get() = m_data and set(d) = m_data <- d this.UpdateChecksum() override this.Bytes with get() = Array.append (base.Bytes) (this.Data) //---- Synchronous Ping let Ping (host : IPAddress, timeout : int ) = let mutable ep = new IPEndPoint( host, 0 ) let socket = new Socket( AddressFamily.InterNetwork, SocketType.Raw, ProtocolType.Icmp ) socket.SetSocketOption( SocketOptionLevel.Socket, SocketOptionName.SendTimeout, timeout ) socket.SetSocketOption( SocketOptionLevel.Socket, SocketOptionName.ReceiveTimeout, timeout ) let packet = EchoMessage() let mutable buffer = packet.Bytes try if socket.SendTo( buffer, ep ) <= 0 then raise (SocketException()) buffer <- Array.create (buffer.Length + 20) 0uy let mutable epr = ep :> EndPoint if socket.ReceiveFrom( buffer, &epr ) <= 0 then raise (SocketException()) finally socket.Close() buffer //---- Entensions to the F# Async class to allow up to 5 paramters (not just 3) type Async with static member FromBeginEnd(arg1,arg2,arg3,arg4,beginAction,endAction,?cancelAction): Async<'T> = Async.FromBeginEnd((fun (iar,state) -> beginAction(arg1,arg2,arg3,arg4,iar,state)), endAction, ?cancelAction=cancelAction) static member FromBeginEnd(arg1,arg2,arg3,arg4,arg5,beginAction,endAction,?cancelAction): Async<'T> = Async.FromBeginEnd((fun (iar,state) -> beginAction(arg1,arg2,arg3,arg4,arg5,iar,state)), endAction, ?cancelAction=cancelAction) //---- Extensions to the Socket class to provide async SendTo and ReceiveFrom type System.Net.Sockets.Socket with member this.AsyncSendTo( buffer, offset, size, socketFlags, remoteEP ) = Async.FromBeginEnd( buffer, offset, size, socketFlags, remoteEP, this.BeginSendTo, this.EndSendTo ) member this.AsyncReceiveFrom( buffer, offset, size, socketFlags, remoteEP ) = Async.FromBeginEnd( buffer, offset, size, socketFlags, remoteEP, this.BeginReceiveFrom, (fun asyncResult -> this.EndReceiveFrom(asyncResult, remoteEP) ) ) //---- Asynchronous Ping let PingAsync (host : IPAddress, timeout : int ) = async { let ep = IPEndPoint( host, 0 ) use socket = new Socket( AddressFamily.InterNetwork, SocketType.Raw, ProtocolType.Icmp ) socket.SetSocketOption( SocketOptionLevel.Socket, SocketOptionName.SendTimeout, timeout ) socket.SetSocketOption( SocketOptionLevel.Socket, SocketOptionName.ReceiveTimeout, timeout ) let packet = EchoMessage() let outbuffer = packet.Bytes try let! result = socket.AsyncSendTo( outbuffer, 0, outbuffer.Length, SocketFlags.None, ep ) if result <= 0 then raise (SocketException()) let epr = ref (ep :> EndPoint) let inbuffer = Array.create (outbuffer.Length + 256) 0uy let! result = socket.AsyncReceiveFrom( inbuffer, 0, inbuffer.Length, SocketFlags.None, epr ) if result <= 0 then raise (SocketException()) return inbuffer finally socket.Close() }

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  • howto mount usb disk on esxi

    - by maruti
    have a USB drive NTFS attached to ESXi4 host. fdisk -l shows the device as /dev/mpx.... but when i try to mount that using mount /dev/xxx /mnt/usbdisk....it fails with message "no such file or dir" could anyone help with correct entry in etc/fstab? all that i am trying to do is backup the vms on esxi host to usb disk...thanks in advance

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  • Eject disk on Mac Pro running VMWare ESXi

    - by DougN
    I'm almost embarrassed to ask this, but I'm stuck. I installed VMWare ESXi on a Mac Pro. It's working great! The problem is that you press F12 to eject the disk, and F12 is what you use to shutdown ESX. I can power down, open the case, pull out the CD drive and use a paper clip to force the drawer open, but that's kind of a pain. Any other way to do this?

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  • Best available technology for layered disk cache in linux

    - by SpliFF
    I've just bought a 6-core Phenom with 16G of RAM. I use it primarily for compiling and video encoding (and occassional web/db). I'm finding all activities get disk-bound and I just can't keep all 6 cores fed. I'm buying an SSD raid to sit between the HDD and tmpfs. I want to setup a "layered" filesystem where reads are cached on tmpfs but writes safely go through to the SSD. I want files (or blocks) that haven't been read lately on the SSD to then be written back to a HDD using a compressed FS or block layer. So basically reads: - Check tmpfs - Check SSD - Check HD And writes: - Straight to SSD (for safety), then tmpfs (for speed) And periodically, or when space gets low: - Move least frequently accessed files down one layer. I've seen a few projects of interest. CacheFS, cachefsd, bcache seem pretty close but I'm having trouble determining which are practical. bcache seems a little risky (early adoption), cachefs seems tied to specific network filesystems. There are "union" projects unionfs and aufs that let you mount filesystems over each other (USB device over a DVD usually) but both are distributed as a patch and I get the impression this sort of "transparent" mounting was going to become a kernel feature rather than a FS. I know the kernel has a built-in disk cache but it doesn't seem to work well with compiling. I see a 20x speed improvement when I move my source files to tmpfs. I think it's because the standard buffers are dedicated to a specific process and compiling creates and destroys thousands of processes during a build (just guessing there). It looks like I really want those files precached. I've read tmpfs can use virtual memory. In that case is it practical to create a giant tmpfs with swap on the SSD? I don't need to boot off the resulting layered filesystem. I can load grub, kernel and initrd from elsewhere if needed. So that's the background. The question has several components I guess: Recommended FS and/or block layer for the SSD and compressed HDD. Recommended mkfs parameters (block size, options etc...) Recommended cache/mount technology to bind the layers transparently Required mount parameters Required kernel options / patches, etc..

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  • eAccelerator disk cache size

    - by Josh
    I am using eAccelerator to cache my PHP opcodes. I have the disk cache set to /var/cache/eAccelerator. How can I limit the size of the cache? It's already grown to 1.5 GiB and keeps growing!

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  • Create disk image from a remote system

    - by cringe
    I want to backup a disk from a remote system, but the remote system itself has not enough space available. Now I want to use ddand pipe the output through ssh, but I can't figure out how to do it. I read several sources on the web, but I'm stuck now. Can someone please point me to a good resource or write down the command line with explanations?

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  • Toast vs Disk Util?

    - by Grishanko
    I have several users that are insisting on the purchase of Toast. They will be using it to make backups of disks at possibly re-burn them if needed. I have used Disk Utility for that function. At this point there is no addition functionality needed. However, that can always change in the future. Is there any advantages or disadvantages to either solution?

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  • Mounting ubuntu's root.disk in Windows 7

    - by gAMBOOKa
    I've got Ubuntu 9.10 installed in an NTFS partition. After an update, I started getting kernel panics, so I need to reinstall it. But before I do that, I need to retrieve and backup my home directory. I believe Ubuntu's file system is packaged in the root.disk image. So how do I mount it in Windows?

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  • Architecture strategies for a complex competition scoring system

    - by mikewassmer
    Competition description: There are about 10 teams competing against each other over a 6-week period. Each team's total score (out of a 1000 total available points) is based on the total of its scores in about 25,000 different scoring elements. Most scoring elements are worth a small fraction of a point and there will about 10 X 25,000 = 250,000 total raw input data points. The points for some scoring elements are awarded at frequent regular time intervals during the competition. The points for other scoring elements are awarded at either irregular time intervals or at just one moment in time. There are about 20 different types of scoring elements. Each of the 20 types of scoring elements has a different set of inputs, a different algorithm for calculating the earned score from the raw inputs, and a different number of total available points. The simplest algorithms require one input and one simple calculation. The most complex algorithms consist of hundreds or thousands of raw inputs and a more complicated calculation. Some types of raw inputs are automatically generated. Other types of raw inputs are manually entered. All raw inputs are subject to possible manual retroactive adjustments by competition officials. Primary requirements: The scoring system UI for competitors and other competition followers will show current and historical total team scores, team standings, team scores by scoring element, raw input data (at several levels of aggregation, e.g. daily, weekly, etc.), and other metrics. There will be charts, tables, and other widgets for displaying historical raw data inputs and scores. There will be a quasi-real-time dashboard that will show current scores and raw data inputs. Aggregate scores should be updated/refreshed whenever new raw data inputs arrive or existing raw data inputs are adjusted. There will be a "scorekeeper UI" for manually entering new inputs, manually adjusting existing inputs, and manually adjusting calculated scores. Decisions: Should the scoring calculations be performed on the database layer (T-SQL/SQL Server, in my case) or on the application layer (C#/ASP.NET MVC, in my case)? What are some recommended approaches for calculating updated total team scores whenever new raw inputs arrives? Calculating each of the teams' total scores from scratch every time a new input arrives will probably slow the system to a crawl. I've considered some kind of "diff" approach, but that approach may pose problems for ad-hoc queries and some aggegates. I'm trying draw some sports analogies, but it's tough because most games consist of no more than 20 or 30 scoring elements per game (I'm thinking of a high-scoring baseball game; football and soccer have fewer scoring events per game). Perhaps a financial balance sheet analogy makes more sense because financial "bottom line" calcs may be calculated from 250,000 or more transactions. Should I be making heavy use of caching for this application? Are there any obvious approaches or similar case studies that I may be overlooking?

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  • Speed of TrueCrypt whole disk encryption

    - by Gareth
    I'm getting a new development laptop soon, and I'm thinking of using TrueCrypt to encrypt the whole disk. What kind of performance drop can I expect? 10%? 30%? more? Also, assuming the workload has an effect, would compiling/using Visual Studio be affected much? I cannot seem to find anything like this on the web.

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  • How to identify heavy write to disk?

    - by Darth
    I have this problem with server running CakePHP application. The server is insanely slow, I first thought that it's application problem, but then I found constant 5-6MB/s write to disk. What is the easiest way to find cause of such a heavy write? The server is running Gentoo.

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  • HP DL380 G7 Disk swap to a HP DL380 G6

    - by rnuno
    The HP DL380 G7 has 3 SAS disks in RAID 5 configuration. I need to change that server to another task and instead of make a clean install on the HP DL380 G6 can i just swap the 3 disks from HP DL380 G7 to the HP DL380 G6? I expect some driver issues maybe on the OS itself because the processor is different. They both use Smart Array P410i, if i power down the machines swap the disk by the same order will the RAID 5 configuration remain and the OS will boot?

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