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  • Alter multiple tables' columns length

    - by gdoron
    So, we just found out that 254 tables in our Oracle DBMS have one column named "Foo" with the wrong length- Number(10) instead of Number(3). That foo column is a part from the PK of the tables. Those tables have other tables with forigen keys to it. What I did is: backed-up the table with a temp table. Disabled the forigen keys to the table. Disabled the PK with the foo column. Nulled the foo column for all the rows. Restored all the above But now we found out it's not just couple of tables but 254 tables. Is there an easy way, (or at least easier than this) to alter the columns length? P.S. I have DBA permissions.

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  • Accessing Variables in Javascript using .length

    - by CoV
    Hey all, I'm pretty new to Javascript, so forgive me if this is a simple question. I'm trying to access the length of a set of checkboxes in a form using Javascript. However, I need to be able to change the "name" field of the checkboxes to check several different sets of them. Right now, my sample code looks like: var set = "set" + x; totalLength = optionBoxes.set.length; The variable x is being incremented by a for loop that wraps the whole thing and the name of the checkbox sets that I'm trying to access are set0, set1, set2, etc. Thanks. Edit: small typo fixes

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  • any other way to find char array length?

    - by user2785137
    public static int getLenth(char[] t) { int i=0; int count=0; try { while(t[i]!='\0') { ++count; i++; } return count; } catch(ArrayIndexOutOfBoundsException aiobe) { return count; } } This method returns length of charArray. But my question is, is there is some other "ways" to find the length of charArray without using this try, catch statements & all ?? Thanks in advance :)

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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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  • BizTalk and IBM WebSphere MQ Errors

    - by Christopher House
    The project I'm currently working on is going to make heavy use of IBM WebShere MQ to send messages from BizTalk to the client's iSeries box.  I'd never previously worked with WebSphere MQ, so I didn't really have any idea what it would take to get this to work.  I was pleasantly surprised that it wasn't too difficult to configure a send port and pass messages through it to a queue.  Or so I thought... A couple of weeks ago, the client gave me the name of a host, queue manager and queue that I'd been using for my development.  Everything was going great, I was able to put messages onto the queue, I was happy, the client was happy.  Life was good.  Then the client tells me that the host I've been connecting to is actually a Solaris box and that in prod, we'll actually be sending to an iSeries.  We both agree that it would behoove us to start pointing my dev environment to their dev iSeries box in order to flush out any weirdness there might be.  As it turns out, it was a good thing we made the change.  As soon as I reconfigured my BRE policy that sets endpoint information to point to the iSeries queue, we started seeing failures in the event log.  An example from the event log: Event Type: Error Event Source: BizTalk Server 2009 Event Category: BizTalk Server 2009 Event ID: 5754 Date:  6/9/2010 Time:  10:16:41 AM User:  N/A Computer: WINDOWS2003 Description: A message sent to adapter "MQSC" on send port "<my dynamic sendport name>" with URI "mqsc://client/tcp/<hostname>(1414)/<queue manager name>/<queue name>" is suspended.  Error details: Failure encountered while attempting to open queue. queue = <queue name> queueManager = <queue manager name>, reasonCode = 6124  MessageId:  {76825C7C-611A-4A56-8A6F-35E1124BDB5C}  InstanceID: {BA389103-DF9B-493F-8C61-44574822AAD6} The key piece of information in the event entry is the reasonCode, 6124.  A quick Google search shows that reasonCode 6124 is the code for MQRC_NOT_CONNECTED.  According to IBM's docs, this means that you've tried to send a message without first opening a connection to the queue manager.  Obviously, in the context of BizTalk, this is an unexpected error, since this sort of thing should be managed entirely by the send adapter. Perusing IBM's documentation a bit more, I came across some info on how to turn on tracing for MQ.  With tracing enabled, I tried sending a message again, then went and reviewed the trace files.  The bulk of the information in the trace files didn't mean a thing to me, but at the end of one of the files, I did notice this: 00006257 15:40:20.327795   3500.4      RSESS:000009 ------{  reqReleaseConn 00006258 15:40:20.328714   3500.4      RSESS:000009 ------}  reqReleaseConn (rc=OK) 00006259 15:40:20.328727   3500.4      RSESS:000009 ------{  xcsClearTraceIdent 0000625A 15:40:20.328739   3500.4           :       ------}  xcsClearTraceIdent (rc=OK) 0000625B 15:40:20.328752   3500.4           :       -----}! trmzstMQCONNX (rc=MQRC_NOT_AUTHORIZED) 0000625C 15:40:20.328765   3500.4           :       ----}! MQCONNX (rc=MQRC_NOT_AUTHORIZED) 0000625D 15:40:20.328766   3500.4           :       ---}! ImqQueueManager::connect (rc=MQRC_NOT_AUTHORIZED) 0000625E 15:40:20.328767   3500.4           :       --}! ImqObject::open (rc=MQRC_NOT_CONNECTED) 0000625F 15:40:20.328768   3500.4           :       --{  ImqQueue::lock 00006260 15:40:20.328769   3500.4           :       --}! ImqQueue::lock (rc=Unknown(1)) 00006261 15:40:20.328769   3500.4           :       --{  ImqQueue::unlock 00006262 15:40:20.328769   3500.4           :       --}! ImqQueue::unlock (rc=Unknown(1)) It seemed like the MQRC_NOT_CONNECTED error was being caused by a security related issue (MQRC_NOT_AUTHORIZED).  I did notice something earlier in the log where it appeared that MQ was passing a field named UID with a value equal to the account name that my BizTalk service was running under.  I ended up creating a new local account on the BizTalk server that had the same name as a user which had access to the queue manager on the iSeries.  I then created a new host instance that ran under this new account, created a send handler for the MQSC adapter on this new host instance and reconfigured my orchestration to run on the new host instance.  After bouncing all my host instances, I was now able to send messages to the iSeries. It's still not clear to me why we were able to connect to the Solaris server.  I ended up contacting IBM's support and they did confirm that the process sending to MQ does in fact pass the identity to the queue manager it's connecting to.

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  • C#/.NET Little Wonders: The Concurrent Collections (1 of 3)

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In the next few weeks, we will discuss the concurrent collections and how they have changed the face of concurrent programming. This week’s post will begin with a general introduction and discuss the ConcurrentStack<T> and ConcurrentQueue<T>.  Then in the following post we’ll discuss the ConcurrentDictionary<T> and ConcurrentBag<T>.  Finally, we shall close on the third post with a discussion of the BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. A brief history of collections In the beginning was the .NET 1.0 Framework.  And out of this framework emerged the System.Collections namespace, and it was good.  It contained all the basic things a growing programming language needs like the ArrayList and Hashtable collections.  The main problem, of course, with these original collections is that they held items of type object which means you had to be disciplined enough to use them correctly or you could end up with runtime errors if you got an object of a type you weren't expecting. Then came .NET 2.0 and generics and our world changed forever!  With generics the C# language finally got an equivalent of the very powerful C++ templates.  As such, the System.Collections.Generic was born and we got type-safe versions of all are favorite collections.  The List<T> succeeded the ArrayList and the Dictionary<TKey,TValue> succeeded the Hashtable and so on.  The new versions of the library were not only safer because they checked types at compile-time, in many cases they were more performant as well.  So much so that it's Microsoft's recommendation that the System.Collections original collections only be used for backwards compatibility. So we as developers came to know and love the generic collections and took them into our hearts and embraced them.  The problem is, thread safety in both the original collections and the generic collections can be problematic, for very different reasons. Now, if you are only doing single-threaded development you may not care – after all, no locking is required.  Even if you do have multiple threads, if a collection is “load-once, read-many” you don’t need to do anything to protect that container from multi-threaded access, as illustrated below: 1: public static class OrderTypeTranslator 2: { 3: // because this dictionary is loaded once before it is ever accessed, we don't need to synchronize 4: // multi-threaded read access 5: private static readonly Dictionary<string, char> _translator = new Dictionary<string, char> 6: { 7: {"New", 'N'}, 8: {"Update", 'U'}, 9: {"Cancel", 'X'} 10: }; 11:  12: // the only public interface into the dictionary is for reading, so inherently thread-safe 13: public static char? Translate(string orderType) 14: { 15: char charValue; 16: if (_translator.TryGetValue(orderType, out charValue)) 17: { 18: return charValue; 19: } 20:  21: return null; 22: } 23: } Unfortunately, most of our computer science problems cannot get by with just single-threaded applications or with multi-threading in a load-once manner.  Looking at  today's trends, it's clear to see that computers are not so much getting faster because of faster processor speeds -- we've nearly reached the limits we can push through with today's technologies -- but more because we're adding more cores to the boxes.  With this new hardware paradigm, it is even more important to use multi-threaded applications to take full advantage of parallel processing to achieve higher application speeds. So let's look at how to use collections in a thread-safe manner. Using historical collections in a concurrent fashion The early .NET collections (System.Collections) had a Synchronized() static method that could be used to wrap the early collections to make them completely thread-safe.  This paradigm was dropped in the generic collections (System.Collections.Generic) because having a synchronized wrapper resulted in atomic locks for all operations, which could prove overkill in many multithreading situations.  Thus the paradigm shifted to having the user of the collection specify their own locking, usually with an external object: 1: public class OrderAggregator 2: { 3: private static readonly Dictionary<string, List<Order>> _orders = new Dictionary<string, List<Order>>(); 4: private static readonly _orderLock = new object(); 5:  6: public void Add(string accountNumber, Order newOrder) 7: { 8: List<Order> ordersForAccount; 9:  10: // a complex operation like this should all be protected 11: lock (_orderLock) 12: { 13: if (!_orders.TryGetValue(accountNumber, out ordersForAccount)) 14: { 15: _orders.Add(accountNumber, ordersForAccount = new List<Order>()); 16: } 17:  18: ordersForAccount.Add(newOrder); 19: } 20: } 21: } Notice how we’re performing several operations on the dictionary under one lock.  With the Synchronized() static methods of the early collections, you wouldn’t be able to specify this level of locking (a more macro-level).  So in the generic collections, it was decided that if a user needed synchronization, they could implement their own locking scheme instead so that they could provide synchronization as needed. The need for better concurrent access to collections Here’s the problem: it’s relatively easy to write a collection that locks itself down completely for access, but anything more complex than that can be difficult and error-prone to write, and much less to make it perform efficiently!  For example, what if you have a Dictionary that has frequent reads but in-frequent updates?  Do you want to lock down the entire Dictionary for every access?  This would be overkill and would prevent concurrent reads.  In such cases you could use something like a ReaderWriterLockSlim which allows for multiple readers in a lock, and then once a writer grabs the lock it blocks all further readers until the writer is done (in a nutshell).  This is all very complex stuff to consider. Fortunately, this is where the Concurrent Collections come in.  The Parallel Computing Platform team at Microsoft went through great pains to determine how to make a set of concurrent collections that would have the best performance characteristics for general case multi-threaded use. Now, as in all things involving threading, you should always make sure you evaluate all your container options based on the particular usage scenario and the degree of parallelism you wish to acheive. This article should not be taken to understand that these collections are always supperior to the generic collections. Each fills a particular need for a particular situation. Understanding what each container is optimized for is key to the success of your application whether it be single-threaded or multi-threaded. General points to consider with the concurrent collections The MSDN points out that the concurrent collections all support the ICollection interface. However, since the collections are already synchronized, the IsSynchronized property always returns false, and SyncRoot always returns null.  Thus you should not attempt to use these properties for synchronization purposes. Note that since the concurrent collections also may have different operations than the traditional data structures you may be used to.  Now you may ask why they did this, but it was done out of necessity to keep operations safe and atomic.  For example, in order to do a Pop() on a stack you have to know the stack is non-empty, but between the time you check the stack’s IsEmpty property and then do the Pop() another thread may have come in and made the stack empty!  This is why some of the traditional operations have been changed to make them safe for concurrent use. In addition, some properties and methods in the concurrent collections achieve concurrency by creating a snapshot of the collection, which means that some operations that were traditionally O(1) may now be O(n) in the concurrent models.  I’ll try to point these out as we talk about each collection so you can be aware of any potential performance impacts.  Finally, all the concurrent containers are safe for enumeration even while being modified, but some of the containers support this in different ways (snapshot vs. dirty iteration).  Once again I’ll highlight how thread-safe enumeration works for each collection. ConcurrentStack<T>: The thread-safe LIFO container The ConcurrentStack<T> is the thread-safe counterpart to the System.Collections.Generic.Stack<T>, which as you may remember is your standard last-in-first-out container.  If you think of algorithms that favor stack usage (for example, depth-first searches of graphs and trees) then you can see how using a thread-safe stack would be of benefit. The ConcurrentStack<T> achieves thread-safe access by using System.Threading.Interlocked operations.  This means that the multi-threaded access to the stack requires no traditional locking and is very, very fast! For the most part, the ConcurrentStack<T> behaves like it’s Stack<T> counterpart with a few differences: Pop() was removed in favor of TryPop() Returns true if an item existed and was popped and false if empty. PushRange() and TryPopRange() were added Allows you to push multiple items and pop multiple items atomically. Count takes a snapshot of the stack and then counts the items. This means it is a O(n) operation, if you just want to check for an empty stack, call IsEmpty instead which is O(1). ToArray() and GetEnumerator() both also take snapshots. This means that iteration over a stack will give you a static view at the time of the call and will not reflect updates. Pushing on a ConcurrentStack<T> works just like you’d expect except for the aforementioned PushRange() method that was added to allow you to push a range of items concurrently. 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: // but you can also push multiple items in one atomic operation (no interleaves) 7: stack.PushRange(new [] { "Second", "Third", "Fourth" }); For looking at the top item of the stack (without removing it) the Peek() method has been removed in favor of a TryPeek().  This is because in order to do a peek the stack must be non-empty, but between the time you check for empty and the time you execute the peek the stack contents may have changed.  Thus the TryPeek() was created to be an atomic check for empty, and then peek if not empty: 1: // to look at top item of stack without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (stack.TryPeek(out item)) 5: { 6: Console.WriteLine("Top item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Stack was empty."); 11: } Finally, to remove items from the stack, we have the TryPop() for single, and TryPopRange() for multiple items.  Just like the TryPeek(), these operations replace Pop() since we need to ensure atomically that the stack is non-empty before we pop from it: 1: // to remove items, use TryPop or TryPopRange to get multiple items atomically (no interleaves) 2: if (stack.TryPop(out item)) 3: { 4: Console.WriteLine("Popped " + item); 5: } 6:  7: // TryPopRange will only pop up to the number of spaces in the array, the actual number popped is returned. 8: var poppedItems = new string[2]; 9: int numPopped = stack.TryPopRange(poppedItems); 10:  11: foreach (var theItem in poppedItems.Take(numPopped)) 12: { 13: Console.WriteLine("Popped " + theItem); 14: } Finally, note that as stated before, GetEnumerator() and ToArray() gets a snapshot of the data at the time of the call.  That means if you are enumerating the stack you will get a snapshot of the stack at the time of the call.  This is illustrated below: 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: var results = stack.GetEnumerator(); 7:  8: // but you can also push multiple items in one atomic operation (no interleaves) 9: stack.PushRange(new [] { "Second", "Third", "Fourth" }); 10:  11: while(results.MoveNext()) 12: { 13: Console.WriteLine("Stack only has: " + results.Current); 14: } The only item that will be printed out in the above code is "First" because the snapshot was taken before the other items were added. This may sound like an issue, but it’s really for safety and is more correct.  You don’t want to enumerate a stack and have half a view of the stack before an update and half a view of the stack after an update, after all.  In addition, note that this is still thread-safe, whereas iterating through a non-concurrent collection while updating it in the old collections would cause an exception. ConcurrentQueue<T>: The thread-safe FIFO container The ConcurrentQueue<T> is the thread-safe counterpart of the System.Collections.Generic.Queue<T> class.  The concurrent queue uses an underlying list of small arrays and lock-free System.Threading.Interlocked operations on the head and tail arrays.  Once again, this allows us to do thread-safe operations without the need for heavy locks! The ConcurrentQueue<T> (like the ConcurrentStack<T>) has some departures from the non-concurrent counterpart.  Most notably: Dequeue() was removed in favor of TryDequeue(). Returns true if an item existed and was dequeued and false if empty. Count does not take a snapshot It subtracts the head and tail index to get the count.  This results overall in a O(1) complexity which is quite good.  It’s still recommended, however, that for empty checks you call IsEmpty instead of comparing Count to zero. ToArray() and GetEnumerator() both take snapshots. This means that iteration over a queue will give you a static view at the time of the call and will not reflect updates. The Enqueue() method on the ConcurrentQueue<T> works much the same as the generic Queue<T>: 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5: queue.Enqueue("Second"); 6: queue.Enqueue("Third"); For front item access, the TryPeek() method must be used to attempt to see the first item if the queue.  There is no Peek() method since, as you’ll remember, we can only peek on a non-empty queue, so we must have an atomic TryPeek() that checks for empty and then returns the first item if the queue is non-empty. 1: // to look at first item in queue without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (queue.TryPeek(out item)) 5: { 6: Console.WriteLine("First item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Queue was empty."); 11: } Then, to remove items you use TryDequeue().  Once again this is for the same reason we have TryPeek() and not Peek(): 1: // to remove items, use TryDequeue. If queue is empty returns false. 2: if (queue.TryDequeue(out item)) 3: { 4: Console.WriteLine("Dequeued first item " + item); 5: } Just like the concurrent stack, the ConcurrentQueue<T> takes a snapshot when you call ToArray() or GetEnumerator() which means that subsequent updates to the queue will not be seen when you iterate over the results.  Thus once again the code below will only show the first item, since the other items were added after the snapshot. 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5:  6: var iterator = queue.GetEnumerator(); 7:  8: queue.Enqueue("Second"); 9: queue.Enqueue("Third"); 10:  11: // only shows First 12: while (iterator.MoveNext()) 13: { 14: Console.WriteLine("Dequeued item " + iterator.Current); 15: } Using collections concurrently You’ll notice in the examples above I stuck to using single-threaded examples so as to make them deterministic and the results obvious.  Of course, if we used these collections in a truly multi-threaded way the results would be less deterministic, but would still be thread-safe and with no locking on your part required! For example, say you have an order processor that takes an IEnumerable<Order> and handles each other in a multi-threaded fashion, then groups the responses together in a concurrent collection for aggregation.  This can be done easily with the TPL’s Parallel.ForEach(): 1: public static IEnumerable<OrderResult> ProcessOrders(IEnumerable<Order> orderList) 2: { 3: var proxy = new OrderProxy(); 4: var results = new ConcurrentQueue<OrderResult>(); 5:  6: // notice that we can process all these in parallel and put the results 7: // into our concurrent collection without needing any external locking! 8: Parallel.ForEach(orderList, 9: order => 10: { 11: var result = proxy.PlaceOrder(order); 12:  13: results.Enqueue(result); 14: }); 15:  16: return results; 17: } Summary Obviously, if you do not need multi-threaded safety, you don’t need to use these collections, but when you do need multi-threaded collections these are just the ticket! The plethora of features (I always think of the movie The Three Amigos when I say plethora) built into these containers and the amazing way they acheive thread-safe access in an efficient manner is wonderful to behold. Stay tuned next week where we’ll continue our discussion with the ConcurrentBag<T> and the ConcurrentDictionary<TKey,TValue>. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here.   Tweet Technorati Tags: C#,.NET,Concurrent Collections,Collections,Multi-Threading,Little Wonders,BlackRabbitCoder,James Michael Hare

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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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  • 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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  • 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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  • 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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