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• Removing expired certificates from LDS (new ver of ADAM)

  - by jonthebrewer

  Hi all. This is my situation: We are in the process of replacing a certificate store currently hosted on Sun's iPlanet with Microsoft's Lightweight Directory Services (new version of ADAM with Server 2008). These certificates have been imported into LDS into an application partition (say o=myorg, C=AU). Under this structure I have around 40,000 OU's each one representing a customer under each customers OU are one or more user (iNetOrg) objects (around 60,000 in all). In each user are one or more certificates in the UserCertificate attribute. A combination of in-house written application code and proprietory PKI code reads and publishes these certficates to validate financial transactions. As the LDAP path of the certificates is stored within the customer certificates (and within the application code) and there is zero appetite for changing any of the code, I have had to pick up the iPlanet directory as a whole and dump it in LDS in the same structure. (I will not be using or hosting a Microsoft CA, just implementing an LDAP compliant directory to host these certificates) We have fully tested the application using the data in LDS and everything works fine - here is my dilema and question (finally, phew!) There was no process put in place for removing revoked or expired certificates, consequently the vast majority of the data is completely useless, the system has been running for about 8 years! I have done a quick analysis and I estimate that at least 80% of the data is no longer valid. As I am taking on responsibility for managing the directory I would like to start with a clean directory. Does anyone have any idea how I can cleanup these expired certificates. I am not a highly experienced scripter but have some background in VB. I have been researching the use of CAPICOM and have a feeling this may be able to be used but in exactly what way I am not sure?? I would prefer to write a script that I could specify an expiration date (say any certs that expired prior to 2010) then run against the LDS paritition. This way I can reuse the script periodically to cleanup the directory (as mentioned above - I have no way to adjust the applications that are writing the certs, this is with a third party). Another, less attractive, alternative is to massage the LDIF file (2.7 million lines!) to rip the certs out prior to the import Any help and advice MUCH appreciated. Cheers Jon

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• JBoss EJB Bean not bound

  - by portoalet

  Hi, I have the following error Exception in thread "main" javax.naming.NameNotFoundException: CounterBean not bound trying to access an EJB JAR CounterBean.jar deployed on JBoss5 from a client application outside the Application Server. From the Jboss log, it looks like it does not have a global JNDI name? Is this ok? What have I done wrong? JBoss log: 13:50:39,669 INFO [JBossASKernel] Created KernelDeployment for: Counter.jar 13:50:39,672 INFO [JBossASKernel] installing bean: jboss.j2ee:jar=Counter.jar,name=CounterBean,service=EJB3 13:50:39,672 INFO [JBossASKernel] with dependencies: 13:50:39,672 INFO [JBossASKernel] and demands: 13:50:39,673 INFO [JBossASKernel] partition:partitionName=DefaultPartition; Required: Described 13:50:39,673 INFO [JBossASKernel] jboss.ejb:service=EJBTimerService; Required: Described 13:50:39,673 INFO [JBossASKernel] and supplies: 13:50:39,673 INFO [JBossASKernel] jndi:CounterBean 13:50:39,673 INFO [JBossASKernel] Added bean(jboss.j2ee:jar=Counter.jar,name=CounterBean,service=EJB3) to KernelDeployment of: Counte r.jar 13:50:39,712 INFO [SessionSpecContainer] Starting jboss.j2ee:jar=Counter.jar,name=CounterBean,service=EJB3 13:50:39,727 INFO [EJBContainer] STARTED EJB: com.don.CounterBean ejbName: CounterBean 13:50:39,732 INFO [JndiSessionRegistrarBase] Binding the following Entries in Global JNDI: The client code is: public static void main(String[] args) throws NamingException, InterruptedException { InitialContext ctx = new InitialContext(); Counter s = (Counter)ctx.lookup("CounterBean/remote"); for(int i = 0; i < 100; i++ ) { s.printCount(i); Thread.sleep(1000); } } Error message: java -Djava.naming.provider.url=jnp://123.123.123.123:1099 -Djava.naming.factory.initial=org.jnp.interfaces.NamingContextFactory com.don.Client Exception in thread "main" javax.naming.NameNotFoundException: CounterBean not bound at org.jnp.server.NamingServer.getBinding(NamingServer.java:771) at org.jnp.server.NamingServer.getBinding(NamingServer.java:779) at org.jnp.server.NamingServer.getObject(NamingServer.java:785) at org.jnp.server.NamingServer.lookup(NamingServer.java:396) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at sun.rmi.server.UnicastServerRef.dispatch(UnicastServerRef.java:305) at sun.rmi.transport.Transport$1.run(Transport.java:159) at java.security.AccessController.doPrivileged(Native Method) at sun.rmi.transport.Transport.serviceCall(Transport.java:155) at sun.rmi.transport.tcp.TCPTransport.handleMessages(TCPTransport.java:535) at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.run0(TCPTransport.java:790) at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.run(TCPTransport.java:649) at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908) at java.lang.Thread.run(Thread.java:619) at sun.rmi.transport.StreamRemoteCall.exceptionReceivedFromServer(StreamRemoteCall.java:255) at sun.rmi.transport.StreamRemoteCall.executeCall(StreamRemoteCall.java:233) at sun.rmi.server.UnicastRef.invoke(UnicastRef.java:142) at org.jnp.server.NamingServer_Stub.lookup(Unknown Source) at org.jnp.interfaces.NamingContext.lookup(NamingContext.java:726) at org.jnp.interfaces.NamingContext.lookup(NamingContext.java:686) at javax.naming.InitialContext.lookup(InitialContext.java:392) at com.don.Client.main(Client.java:10)

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• Reliable way of generating unique hardware ID

  - by mr.b

  Question: what's the best way to accomplish following. I have to come up with unique ID for each networked client, such that: it (ID) should persist once client software is installed on target computer, and should continue to persist if software is re-installed on same computer and same OS installment, it should not change if hardware configuration is modified in most ways (except changing the motherboard) When hard drive with client software installed is cloned to another computer with identical hardware configuration (or, as similar as possible), client software should be aware of that change. A little bit of explanation and some back-story: This question is basically age old question that also touches topic of software copy-protection, as some of mechanisms used in that area are mentioned here. I should be clear at this point that I'm not looking for a copy-protection scheme. Please, read on. :) I'm working on a client-server software that is supposed to work in local network. One of problems I have to solve is to identify each unique client in network (not so much of a problem), so that I can apply certain attributes to every specific client, retain and enforce those attributes during deployment lifetime of a specific client. While I was looking for a solution, I was aware of following: Windows activation system uses some kind of heavy fingerprinting mechanism, that is extremely sensitive to hardware modifications, Disk imaging software copies along all Volume IDs (tied to each partition when formatted), and custom, uniquely generated IDs during installation process, during first run, or in any other way, that is strictly software in its nature, and stored in registry or on hard drive, so it's very easy to confuse two Obvious choice for this kind of problem would be to find out BIOS identifiers (not 100% sure if this is unique through identical motherboard models, though), as that's the only thing I can rely on, that isn't duplicated, transferred by cloning, and that can't be changed (at least not by using some user-space program). Everything else fails as either being not reliable (MAC cloning, anyone?), or too demanding (in terms that it's too sensitive to configuration changes). Am I missing something obvious here? Sub-question that I'd like to ask is, am I doing it correctly, architecture-wise? Perhaps there is a better tool for task that I have to accomplish... Another approach I had in mind is something similar to handshake mechanism, where server maintains internal lookup table of connected client IDs (which can be even completely software-based and non-unique at any given moment), and tells client to come up with different ID during handshake, if duplicate ID is provided upon connection. That approach, unfortunately, doesn't play nicely with one of requirements to tie attributes to specific client during lifetime.

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• Connecting to Active Directory Application Mode from Perl

  - by Khurram Aziz

  I am trying to connect to Active Directory Application Mode instance. The instance is conenctable from third party LDAP clients like Softerra LDAP Browser. But I am getting the following error when connecting from Perl Net::LDAP=HASH(0x876d8e4) sending: Net::LDAP=HASH(0x876d8e4) received: 30 84 00 00 00 A7 02 01 02 65 84 00 00 00 9E 0A 0........e...... 01 01 04 00 04 84 00 00 00 93 30 30 30 30 30 34 ..........000004 44 43 3A 20 4C 64 61 70 45 72 72 3A 20 44 53 49 DC: LdapErr: DSI 44 2D 30 43 30 39 30 36 32 42 2C 20 63 6F 6D 6D D-0C09062B, comm 65 6E 74 3A 20 49 6E 20 6F 72 64 65 72 20 74 6F ent: In order to 20 70 65 72 66 6F 72 6D 20 74 68 69 73 20 6F 70 perform this op 65 72 61 74 69 6F 6E 20 61 20 73 75 63 63 65 73 eration a succes 73 66 75 6C 20 62 69 6E 64 20 6D 75 73 74 20 62 sful bind must b 65 20 63 6F 6D 70 6C 65 74 65 64 20 6F 6E 20 74 e completed on t 68 65 20 63 6F 6E 6E 65 63 74 69 6F 6E 2E 2C 20 he connection., 64 61 74 61 20 30 2C 20 76 65 63 65 00 __ __ __ data 0, vece.` My directory structure is Partition: CN=Apps,DC=MyCo,DC=COM User exists as CN=myuser,CN=Apps,DC=MyCo,DC=COM I have couple of other entries of the custom class which I am interested to browse; those instances appear fine in ADSI Edit, Softerra LDAP Browser etc. I am new to Perl....My perl code is #!/usr/bin/perl use Net::LDAP; $ldap = Net::LDAP->new("127.0.0.1", debug => 2, user => "CN=myuser,CN=Apps,DC=MyCo,DC=COM", password => "secret" ) or die "$@"; $ldap->bind(version => 3) or die "$@"; print "Connected to ldap\n"; $mesg = $ldap->search( filter => "(objectClass=*)" ) or die ("Failed on search.$!"); my $max = $mesg->count; print "$max records found!\n"; for( my $index = 0 ; $index < $max ; $index++) { my $entry = $mesg->entry($index); my $dn = $entry->dn; @attrs = $entry->attributes; foreach my $var (@attrs) { $attr = $entry->get_value( $var, asref => 1 ); if ( defined($attr) ) { foreach my $value ( @$attr ) { print "$var: $value\n"; } } } } $ldap->unbind();

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• Finding minimum cut-sets between bounded subgraphs

  - by Tore

  If a game map is partitioned into subgraphs, how to minimize edges between subgraphs? I have a problem, Im trying to make A* searches through a grid based game like pacman or sokoban, but i need to find "enclosures". What do i mean by enclosures? subgraphs with as few cut edges as possible given a maximum size and minimum size for number of vertices for each subgraph that act as a soft constraints. Alternatively you could say i am looking to find bridges between subgraphs, but its generally the same problem. Given a game that looks like this, what i want to do is find enclosures so that i can properly find entrances to them and thus get a good heuristic for reaching vertices inside these enclosures. So what i want is to find these colored regions on any given map. My Motivation The reason for me bothering to do this and not just staying content with the performance of a simple manhattan distance heuristic is that an enclosure heuristic can give more optimal results and i would not have to actually do the A* to get some proper distance calculations and also for later adding competitive blocking of opponents within these enclosures when playing sokoban type games. Also the enclosure heuristic can be used for a minimax approach to finding goal vertices more properly. A possible solution to the problem is the Kernighan-Lin algorithm: function Kernighan-Lin(G(V,E)): determine a balanced initial partition of the nodes into sets A and B do A1 := A; B1 := B compute D values for all a in A1 and b in B1 for (i := 1 to |V|/2) find a[i] from A1 and b[i] from B1, such that g[i] = D[a[i]] + D[b[i]] - 2*c[a][b] is maximal move a[i] to B1 and b[i] to A1 remove a[i] and b[i] from further consideration in this pass update D values for the elements of A1 = A1 / a[i] and B1 = B1 / b[i] end for find k which maximizes g_max, the sum of g[1],...,g[k] if (g_max > 0) then Exchange a[1],a[2],...,a[k] with b[1],b[2],...,b[k] until (g_max <= 0) return G(V,E) My problem with this algorithm is its runtime at O(n^2 * lg(n)), i am thinking of limiting the nodes in A1 and B1 to the border of each subgraph to reduce the amount of work done. I also dont understand the c[a][b] cost in the algorithm, if a and b do not have an edge between them is the cost assumed to be 0 or infinity, or should i create an edge based on some heuristic. Do you know what c[a][b] is supposed to be when there is no edge between a and b? Do you think my problem is suitable to use a multi level problem? Why or why not? Do you have a good idea for how to reduce the work done with the kernighan-lin algorithm for my problem?

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• Best way to handle multiple tables to replace one big table in Rails? (e.g. 'Books1', 'Books2', etc.

  - by mikep

  Hello, I've decided to use multiple tables for an entity (e.g. Books1, Books2, Books3, etc.), instead of just one main table which could end up having a lot of rows (e.g. just Books). I'm doing this to try and to avoid a potential future performance drop that could come with having too many rows in one table. With that, I'm looking for a good way to handle this in Rails, mainly by trying to avoid loading a bunch of unused associations. (I know that I could use a partition for this, but, for now, I've decided to go the 'multiple tables' route.) Each user has their books placed into a specific table. The actual book table is chosen when the user is created, and all of their books go into the same table. I'm going to split the adds across the tables. The goal is to try and keep each table pretty much even -- but that's a different issue. One thing I don't particularly want to have is a bunch of unused associations in the User class. Right now, it looks like I'd have to do the following: class User < ActiveRecord::Base has_many :books1, :books2, :books3, :books4, :books5 end class Books1 < ActiveRecord::Base belongs_to :user end class Books2 < ActiveRecord::Base belongs_to :user end class Books3 < ActiveRecord::Base belongs_to :user end I'm assuming that the main performance hit would come in terms of memory and possibly some method call overhead for each User object, since it has to load all of those associations, which in turn creates all of those nice, dynamic model accessor methods like User.find_by_. But for each specific user, only one of the book tables would be usable/applicable, since all of a user's books are stored in the same table. So, only one of the associations would be in use at any time and any other has_many :bookX association that was loaded would be a waste. For example, with a user.id of 2, I'd only need books3.find_by_author('Author'), but the way I'm thinking of setting this up, I'd still have access to Books1..n. I don't really know Ruby/Rails does internally with all of those has_many associations though, so maybe it's not so bad. But right now I'm thinking that it's really wasteful, and that there may just be a better, more efficient way of doing this. So, a few questions: 1) Is there's some sort of special Ruby/Rails methodology that could be applied to this 'multiple tables to represent one entity' scheme? Are there any 'best practices' for this? 2) Is it really bad to have so many unused has_many associations for each object? Is there a better way to do this? 3) Does anyone have any advice on how to abstract the fact that there's multiple book tables behind a single books model/class? For example, so I can call books.find_by_author('Author') instead of books3.find_by_author('Author'). Thank you!

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• Is the design notion of layers contrived?

  - by Bruce

  Hi all I'm reading through Eric Evans' awesome work, Domain-Driven Design. However, I can't help feeling that the 'layers' model is contrived. To expand on that statement, it seems as if it tries to shoe-horn various concepts into a specific, neat model, that of layers talking to each other. It seems to me that the layers model is too simplified to actually capture the way that (good) software works. To expand further: Evans says: "Partition a complex program into layers. Develop a design within each layer that is cohesive and that depends only on the layers below. Follow standard architectural patterns to provide loose coupling to the layers above." Maybe I'm misunderstanding what 'depends' means, but as far as I can see, it can either mean a) Class X (in the UI for example) has a reference to a concrete class Y (in the main application) or b) Class X has a reference to a class Y-ish object providing class Y-ish services (ie a reference held as an interface). If it means (a), then this is clearly a bad thing, since it defeats re-using the UI as a front-end to some other application that provides Y-ish functionality. But if it means (b), then how is the UI any more dependent on the application, than the application is dependent on the UI? Both are decoupled from each other as much as they can be while still talking to each other. Evans' layer model of dependencies going one way seems too neat. First, isn't it more accurate to say that each area of the design provides a module that is pretty much an island to itself, and that ideally all communication is through interfaces, in a contract-driven/responsibility-driven paradigm? (ie, the 'dependency only on lower layers' is contrived). Likewise with the domain layer talking to the database - the domain layer is as decoupled (through DAO etc) from the database as the database is from the domain layer. Neither is dependent on the other, both can be swapped out. Second, the idea of a conceptual straight line (as in from one layer to the next) is artificial - isn't there more a network of intercommunicating but separate modules, including external services, utility services and so on, branching off at different angles? Thanks all - hoping that your responses can clarify my understanding on this..

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• MBR status confusion

  - by Ahmed Ghoneim

  EB 58 90 6D 6B 64 6F 73 66 73 00 00 02 08 20 00 02 00 00 00 00 F8 00 00 3E 00 83 00 00 00 00 00 94 88 7E 00 98 1F 00 00 00 00 00 00 02 00 00 00 01 00 06 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 29 A9 38 B1 34 57 61 76 65 20 20 20 20 20 20 20 46 41 54 33 32 20 20 20 0E 1F BE 77 7C AC 22 C0 74 0B 56 B4 0E BB 07 00 CD 10 5E EB F0 32 E4 CD 16 CD 19 EB FE 54 68 69 73 20 69 73 20 6E 6F 74 20 61 20 62 6F 6F 74 61 62 6C 65 20 64 69 73 6B 2E 20 20 50 6C 65 61 73 65 20 69 6E 73 65 72 74 20 61 20 62 6F 6F 74 61 62 6C 65 20 66 6C 6F 70 70 79 20 61 6E 64 0D 0A 70 72 65 73 73 20 61 6E 79 20 6B 65 79 20 74 6F 20 74 72 79 20 61 67 61 69 6E 20 2E 2E 2E 20 0D 0A 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 55 AA Learning disk records, this is my USB MBR record viewed by bless on ubuntu formatted with disk utility as MBR table and FAT partition, referring to this Wiki of first record status (0x80 = bootable (active), 0x00 = non-bootable, other = invalid ) but my MBR shows first offset as EB. What's this record stands for ? also, can you provide me with good tables/images tutorials for MBR and other disks' records :)

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• Loading the last related record instantly for multiple parent records using Entity framework

  - by Guillaume Schuermans

  Does anyone know a good approach using Entity Framework for the problem described below? I am trying for our next release to come up with a performant way to show the placed orders for the logged on customer. Of course paging is always a good technique to use when a lot of data is available I would like to see an answer without any paging techniques. Here's the story: a customer places an order which gets an orderstatus = PENDING. Depending on some strategy we move that order up the chain in order to get it APPROVED. Every change of status is logged so we can see a trace for statusses and maybe even an extra line of comment per status which can provide some extra valuable information to whoever sees this order in an interface. So an Order is linked to a Customer. One order can have multiple orderstatusses stored in OrderStatusHistory. In my testscenario I am using a customer which has 100+ Orders each with about 5 records in the OrderStatusHistory-table. I would for now like to see all orders in one page not using paging where for each Order I show the last relevant Status and the extra comment (if there is any for this last status; both fields coming from OrderStatusHistory; the record with the highest Id for the given OrderId). There are multiple scenarios I have tried, but I would like to see any potential other solutions or comments on the things I have already tried. Trying to do Include() when getting Orders but this still results in multiple queries launched on the database. Each order triggers an extra query to the database to get all orderstatusses in the history table. So all statusses are queried here instead of just returning the last relevant one, plus 100 extra queries are launched for 100 orders. You can imagine the problem when there are 100000+ orders in the database. Having 2 computed columns on the database: LastStatus, LastStatusInformation and a regular Linq-Query which gets those columns which are available through the Entity-model. The problem with this approach is the fact that those computed columns are determined using a scalar function which can not be changed without removing the formula from the computed column, etc... In the end I am very familiar with SQL and Stored procedures, but since the rest of the data-layer uses Entity Framework I would like to stick to it as long as possible, even though I have my doubts about performance. Using the SQL approach I would write something like this: WITH cte (RN, OrderId, [Status], Information) AS ( SELECT ROW_NUMBER() OVER (PARTITION BY OrderId ORDER BY Id DESC), OrderId, [Status], Information FROM OrderStatus ) SELECT o.Id, cte.[Status], cte.Information AS StatusInformation, o.* FROM [Order] o INNER JOIN cte ON o.Id = cte.OrderId AND cte.RN = 1 WHERE CustomerId = @CustomerId ORDER BY 1 DESC; which returns all orders for the customer with the statusinformation provided by the Common Table Expression. Does anyone know a good approach using Entity Framework?

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• Moving from Windows to Ubuntu.

  - by djzmo

  Hello there, I used to program in Windows with Microsoft Visual C++ and I need to make some of my portable programs (written in portable C++) to be cross-platform, or at least I can release a working version of my program for both Linux and Windows. I am total newcomer in Linux application development (and rarely use the OS itself). So, today, I installed Ubuntu 10.04 LTS (through Wubi) and equipped Code::Blocks with the g++ compiler as my main weapon. Then I compiled my very first Hello World linux program, and I confused about the output program. I can run my program through the "Build and Run" menu option in Code::Blocks, but when I tried to launch the compiled application externally through a File Browser (in /media/MyNTFSPartition/MyProject/bin/Release; yes, I saved it in my NTFS partition), the program didn't show up. Why? I ran out of idea. I need to change my Windows and Microsoft Visual Studio mindset to Linux and Code::Blocks mindset. So I came up with these questions: How can I execute my compiled linux programs externally (outside IDE)? In Windows, I simply run the generated executable (.exe) file How can I distribute my linux application? In Windows, I simply distribute the executable files with the corresponding DLL files (if any) What is the equivalent of LIBs (static library) and DLLs (dynamic library) in linux and how to use them? In Windows/Visual Studio, I simply add the required libraries to the Additional Dependencies in the Project Settings, and my program will automatically link with the required static library(-ies)/DLLs. Is it possible to use the "binary form" of a C++ library (if provided) so that I wouldn't need to recompile the entire library source code? In Windows, yes. Sometimes precompiled *.lib files are provided. If I want to create a wxWidgets application in Linux, which package should I pick for Ubuntu? wxGTK or wxX11? Can I run wxGTK program under X11? In Windows, I use wxMSW, Of course. If question no. 4 is answered possible, are precompiled wxX11/wxGTK library exists out there? Haven't tried deep google search. In Windows, there is a project called "wxPack" (http://wxpack.sourceforge.net/) that saves a lot of my time. Sorry for asking many questions, but I am really confused on these linux development fundamentals. Any kind of help would be appreciated =) Thanks.

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• How do I add "Press any key to boot from usb" when installing Windows from a flash drive? (Grub4dos question / how to remove a bootloader)

  - by Vincent

  Hi there! I've been struggling with this problem for a while now and finially decided to ask for help. Let me first explain what the main purpose of the app is: to provide the a very easy to use way of backing up files, after which I format the drive and start Windows 7 setup. I do this by booting WinPE, which runs a script to detect Windows installations and then opens a file browser. After the file browser is closed, the script continues and formats the drive that contains the Windows installation, and starts an unattended Windows 7 install. Now here is the problem: When you start Windows setup or WinPE from a dvd, you get a nice option to "Press any key to boot from DVD". This is to prevent the computer from booting the DVD when the first phase of the installation is complete and the computer reboots. However, when booting from a flash drive, Windows does not provide this option: it simply boots the flash drive every reboot. To replicate the "press any key" function, I installed Grub4Dos, which works great. It provides a small menu, the first standard item being "Continue installation", the second being "start installation". After quite a lot of tweaking, I got everything working: Start installation starts WinPE, which in turn starts the Windows installation. At first reboot, the Grub4Dos menu comes up, counts 5 seconds and boots the second stage of the installation. Here, I am greeted with the error: "Windows setup could not configure windows to run on this computer's hardware." When I boot into WinPE the normal way (put the bootmgr on the stick root) and change my bios to boot from the primary hdd after first reboot, I don't get this error. I've been looking around, and the only thing I could find was that the BIOS automatically names the boot device hd0, and that Windows can only be run / installed to hd 0. I'm not sure if this is the problem. I read about remapping to solve this problem, but to do that you have to know the phisical location of the hard drive and partition, like hd(0,1). I want this flash drive to work on any PC, regardless of where the OS is installed, so that's not really a possibility. A possible fix I thought of is removing the bootloader from the flash drive when I'm in WinPE. That way, when the pc reboots the BIOS will not see the flash drive as a boot drive and instead boot the primary hdd. I have yet to find a way to do this. Thank you for reading my question, and if you have any suggestion, please do.

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• Use an Ubuntu Live CD to Securely Wipe Your PC’s Hard Drive

  - by Trevor Bekolay

  Deleting files or quickly formatting a drive isn’t enough for sensitive personal information. We’ll show you how to get rid of it for good using a Ubuntu Live CD. When you delete a file in Windows, Ubuntu, or any other operating system, it doesn’t actually destroy the data stored on your hard drive, it just marks that data as “deleted.” If you overwrite it later, then that data is generally unrecoverable, but if the operating system don’t happen to overwrite it, then your data is still stored on your hard drive, recoverable by anyone who has the right software. By securely delete files or entire hard drives, your data will be gone for good. Note: Modern hard drives are extremely sophisticated, as are the experts who recover data for a living. There is no guarantee that the methods covered in this article will make your data completely unrecoverable; however, they will make your data unrecoverable to the majority of recovery methods, and all methods that are readily available to the general public. Shred individual files Most of the data stored on your hard drive is harmless, and doesn’t reveal anything about you. If there are just a few files that you know you don’t want someone else to see, then the easiest way to get rid of them is a built-in Linux utility called shred. Open a terminal window by clicking on Applications at the top-left of the screen, then expanding the Accessories menu and clicking on Terminal. Navigate to the file that you want to delete using cd to change directories and ls to list the files and folders in the current directory. As an example, we’ve got a file called BankInfo.txt on a Windows NTFS-formatted hard drive. We want to delete it securely, so we’ll call shred by entering the following in the terminal window: shred <file> which is, in our example: shred BankInfo.txt Notice that our BankInfo.txt file still exists, even though we’ve shredded it. A quick look at the contents of BankInfo.txt make it obvious that the file has indeed been securely overwritten. We can use some command-line arguments to make shred delete the file from the hard drive as well. We can also be extra-careful about the shredding process by upping the number of times shred overwrites the original file. To do this, in the terminal, type in: shred –remove –iterations=<num> <file> By default, shred overwrites the file 25 times. We’ll double this, giving us the following command: shred –remove –iterations=50 BankInfo.txt BankInfo.txt has now been securely wiped on the physical disk, and also no longer shows up in the directory listing. Repeat this process for any sensitive files on your hard drive! Wipe entire hard drives If you’re disposing of an old hard drive, or giving it to someone else, then you might instead want to wipe your entire hard drive. shred can be invoked on hard drives, but on modern file systems, the shred process may be reversible. We’ll use the program wipe to securely delete all of the data on a hard drive. Unlike shred, wipe is not included in Ubuntu by default, so we have to install it. Open up the Synaptic Package Manager by clicking on System in the top-left corner of the screen, then expanding the Administration folder and clicking on Synaptic Package Manager. wipe is part of the Universe repository, which is not enabled by default. We’ll enable it by clicking on Settings > Repositories in the Synaptic Package Manager window. Check the checkbox next to “Community-maintained Open Source software (universe)”. Click Close. You’ll need to reload Synaptic’s package list. Click on the Reload button in the main Synaptic Package Manager window. Once the package list has been reloaded, the text over the search field will change to “Rebuilding search index”. Wait until it reads “Quick search,” and then type “wipe” into the search field. The wipe package should come up, along with some other packages that perform similar functions. Click on the checkbox to the left of the label “wipe” and select “Mark for Installation”. Click on the Apply button to start the installation process. Click the Apply button on the Summary window that pops up. Once the installation is done, click the Close button and close the Synaptic Package Manager window. Open a terminal window by clicking on Applications in the top-left of the screen, then Accessories > Terminal. You need to figure our the correct hard drive to wipe. If you wipe the wrong hard drive, that data will not be recoverable, so exercise caution! In the terminal window, type in: sudo fdisk -l A list of your hard drives will show up. A few factors will help you identify the right hard drive. One is the file system, found in the System column of  the list – Windows hard drives are usually formatted as NTFS (which shows up as HPFS/NTFS). Another good identifier is the size of the hard drive, which appears after its identifier (highlighted in the following screenshot). In our case, the hard drive we want to wipe is only around 1 GB large, and is formatted as NTFS. We make a note of the label found under the the Device column heading. If you have multiple partitions on this hard drive, then there will be more than one device in this list. The wipe developers recommend wiping each partition separately. To start the wiping process, type the following into the terminal: sudo wipe <device label> In our case, this is: sudo wipe /dev/sda1 Again, exercise caution – this is the point of no return! Your hard drive will be completely wiped. It may take some time to complete, depending on the size of the drive you’re wiping. Conclusion If you have sensitive information on your hard drive – and chances are you probably do – then it’s a good idea to securely delete sensitive files before you give away or dispose of your hard drive. The most secure way to delete your data is with a few swings of a hammer, but shred and wipe from a Ubuntu Live CD is a good alternative! 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• Keeping track of File System Utilization in Ops Center 12c

  - by S Stelting

  Enterprise Manager Ops Center 12c provides significant monitoring capabilities, combined with very flexible incident management. These capabilities even extend to monitoring the file systems associated with Solaris or Linux assets. Depending on your needs you can monitor and manage incidents, or you can fine tune alert monitoring rules to specific file systems. This article will show you how to use Ops Center 12c to Track file system utilization Adjust file system monitoring rules Disable file system rules Create custom monitoring rules If you're interested in this topic, please join us for a WebEx presentation! Date: Thursday, November 8, 2012 Time: 11:00 am, Eastern Standard Time (New York, GMT-05:00) Meeting Number: 598 796 842 Meeting Password: oracle123 To join the online meeting ------------------------------------------------------- 1. Go to https://oracleconferencing.webex.com/oracleconferencing/j.php?ED=209833597&UID=1512095432&PW=NOWQ3YjJlMmYy&RT=MiMxMQ%3D%3D 2. If requested, enter your name and email address. 3. If a password is required, enter the meeting password: oracle123 4. Click "Join". To view in other time zones or languages, please click the link: https://oracleconferencing.webex.com/oracleconferencing/j.php?ED=209833597&UID=1512095432&PW=NOWQ3YjJlMmYy&ORT=MiMxMQ%3D%3D   Monitoring File Systems for OS Assets The Libraries tab provides basic, device-level information about the storage associated with an OS instance. This tab shows you the local file system associated with the instance and any shared storage libraries mounted by Ops Center. More detailed information about file system storage is available under the Analytics tab under the sub-tab named Charts. Here, you can select and display the individual mount points of an OS, and export the utilization data if desired: In this example, the OS instance has a basic root file partition and several NFS directories. Each file system mount point can be independently chosen for display in the Ops Center chart. File Systems and Incident  Reporting Every asset managed by Ops Center has a "monitoring policy", which determines what represents a reportable issue with the asset. The policy is made up of a bunch of monitoring rules, where each rule describes An attribute to monitor The conditions which represent an issue The level or levels of severity for the issue When the conditions are met, Ops Center sends a notification and creates an incident. By default, OS instances have three monitoring rules associated with file systems: File System Reachability: Triggers an incident if a file system is not reachable NAS Library Status: Triggers an incident for a value of "WARNING" or "DEGRADED" for a NAS-based file system File System Used Space Percentage: Triggers an incident when file system utilization grows beyond defined thresholds You can view these rules in the Monitoring tab for an OS: Of course, the default monitoring rules is that they apply to every file system associated with an OS instance. As a result, any issue with NAS accessibility or disk utilization will trigger an incident. This can cause incidents for file systems to be reported multiple times if the same shared storage is used by many assets, as shown in this screen shot: Depending on the level of control you'd like, there are a number of ways to fine tune incident reporting. Note that any changes to an asset's monitoring policy will detach it from the default, creating a new monitoring policy for the asset. If you'd like, you can extract a monitoring policy from an asset, which allows you to save it and apply the customized monitoring profile to other OS assets. Solution #1: Modify the Reporting Thresholds In some cases, you may want to modify the basic conditions for incident reporting in your file system. The changes you make to a default monitoring rule will apply to all of the file systems associated with your operating system. Selecting the File Systems Used Space Percentage entry and clicking the "Edit Alert Monitoring Rule Parameters" button opens a pop-up dialog which allows you to modify the rule. The first screen lets you decide when you will check for file system usage, and how long you will wait before opening an incident in Ops Center. By default, Ops Center monitors continuously and reports disk utilization issues which exist for more than 15 minutes. The second screen lets you define actual threshold values. By default, Ops Center opens a Warning level incident is utilization rises above 80%, and a Critical level incident for utilization above 95% Solution #2: Disable Incident Reporting for File System If you'd rather not report file system incidents, you can disable the monitoring rules altogether. In this case, you can select the monitoring rules and click the "Disable Alert Monitoring Rule(s)" button to open the pop-up confirmation dialog. Like the first solution, this option affects all file system monitoring. It allows you to completely disable incident reporting for NAS library status or file system space consumption. Solution #3: Create New Monitoring Rules for Specific File Systems If you'd like to have the greatest flexibility when monitoring file systems, you can create entirely new rules. Clicking the "Add Alert Monitoring Rule" (the icon with the green plus sign) opens a wizard which allows you to define a new rule.  This rule will be based on a threshold, and will be used to monitor operating system assets. We'd like to add a rule to track disk utilization for a specific file system - the /nfs-guest directory. To do this, we specify the following attribute FileSystemUsages.name=/nfs-guest.usedSpacePercentage The value of name in the attribute allows us to define a specific NFS shared directory or file system... in the case of this OS, we could have chosen any of the values shown in the File Systems Utilization chart at the beginning of this article. usedSpacePercentage lets us define a threshold based on the percentage of total disk space used. There are a number of other values that we could use for threshold-based monitoring of FileSystemUsages, including freeSpace freeSpacePercentage totalSpace usedSpace usedSpacePercentage The final sections of the screen allow us to determine when to monitor for disk usage, and how long to wait after utilization reaches a threshold before creating an incident. The next screen lets us define the threshold values and severity levels for the monitoring rule: If historical data is available, Ops Center will display it in the screen. Clicking the Apply button will create the new monitoring rule and active it in your monitoring policy. If you combine this with one of the previous solutions, you can precisely define which file systems will generate incidents and notifications. For example, this monitoring policy has the default "File System Used Space Percentage" rule disabled, but the new rule reports ONLY on utilization for the /nfs-guest directory. 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• Is Berkeley DB a NoSQL solution?

  - by Gregory Burd

  Berkeley DB is a library. To use it to store data you must link the library into your application. You can use most programming languages to access the API, the calls across these APIs generally mimic the Berkeley DB C-API which makes perfect sense because Berkeley DB is written in C. The inspiration for Berkeley DB was the DBM library, a part of the earliest versions of UNIX written by AT&T's Ken Thompson in 1979. DBM was a simple key/value hashtable-based storage library. In the early 1990s as BSD UNIX was transitioning from version 4.3 to 4.4 and retrofitting commercial code owned by AT&T with unencumbered code, it was the future founders of Sleepycat Software who wrote libdb (aka Berkeley DB) as the replacement for DBM. The problem it addressed was fast, reliable local key/value storage. At that time databases almost always lived on a single node, even the most sophisticated databases only had simple fail-over two node solutions. If you had a lot of data to store you would choose between the few commercial RDBMS solutions or to write your own custom solution. Berkeley DB took the headache out of the custom approach. These basic market forces inspired other DBM implementations. There was the "New DBM" (ndbm) and the "GNU DBM" (GDBM) and a few others, but the theme was the same. Even today TokyoCabinet calls itself "a modern implementation of DBM" mimicking, and improving on, something first created over thirty years ago. In the mid-1990s, DBM was the name for what you needed if you were looking for fast, reliable local storage. Fast forward to today. What's changed? Systems are connected over fast, very reliable networks. Disks are cheep, fast, and capable of storing huge amounts of data. CPUs continued to follow Moore's Law, processing power that filled a room in 1990 now fits in your pocket. PCs, servers, and other computers proliferated both in business and the personal markets. In addition to the new hardware entire markets, social systems, and new modes of interpersonal communication moved onto the web and started evolving rapidly. These changes cause a massive explosion of data and a need to analyze and understand that data. Taken together this resulted in an entirely different landscape for database storage, new solutions were needed. A number of novel solutions stepped up and eventually a category called NoSQL emerged. The new market forces inspired the CAP theorem and the heated debate of BASE vs. ACID. But in essence this was simply the market looking at what to trade off to meet these new demands. These new database systems shared many qualities in common. There were designed to address massive amounts of data, millions of requests per second, and scale out across multiple systems. The first large-scale and successful solution was Dynamo, Amazon's distributed key/value database. Dynamo essentially took the next logical step and added a twist. Dynamo was to be the database of record, it would be distributed, data would be partitioned across many nodes, and it would tolerate failure by avoiding single points of failure. Amazon did this because they recognized that the majority of the dynamic content they provided to customers visiting their web store front didn't require the services of an RDBMS. The queries were simple, key/value look-ups or simple range queries with only a few queries that required more complex joins. They set about to use relational technology only in places where it was the best solution for the task, places like accounting and order fulfillment, but not in the myriad of other situations. The success of Dynamo, and it's design, inspired the next generation of Non-SQL, distributed database solutions including Cassandra, Riak and Voldemort. The problem their designers set out to solve was, "reliability at massive scale" so the first focal point was distributed database algorithms. Underneath Dynamo there is a local transactional database; either Berkeley DB, Berkeley DB Java Edition, MySQL or an in-memory key/value data structure. Dynamo was an evolution of local key/value storage onto networks. Cassandra, Riak, and Voldemort all faced similar design decisions and one, Voldemort, choose Berkeley DB Java Edition for it's node-local storage. Riak at first was entirely in-memory, but has recently added write-once, append-only log-based on-disk storage similar type of storage as Berkeley DB except that it is based on a hash table which must reside entirely in-memory rather than a btree which can live in-memory or on disk. Berkeley DB evolved too, we added high availability (HA) and a replication manager that makes it easy to setup replica groups. Berkeley DB's replication doesn't partitioned the data, every node keeps an entire copy of the database. For consistency, there is a single node where writes are committed first - a master - then those changes are delivered to the replica nodes as log records. Applications can choose to wait until all nodes are consistent, or fire and forget allowing Berkeley DB to eventually become consistent. Berkeley DB's HA scales-out quite well for read-intensive applications and also effectively eliminates the central point of failure by allowing replica nodes to be elected (using a PAXOS algorithm) to mastership if the master should fail. This implementation covers a wide variety of use cases. MemcacheDB is a server that implements the Memcache network protocol but uses Berkeley DB for storage and HA to replicate the cache state across all the nodes in the cache group. Google Accounts, the user authentication layer for all Google properties, was until recently running Berkeley DB HA. That scaled to a globally distributed system. That said, most NoSQL solutions try to partition (shard) data across nodes in the replication group and some allow writes as well as reads at any node, Berkeley DB HA does not. So, is Berkeley DB a "NoSQL" solution? Not really, but it certainly is a component of many of the existing NoSQL solutions out there. Forgetting all the noise about how NoSQL solutions are complex distributed databases when you boil them down to a single node you still have to store the data to some form of stable local storage. DBMs solved that problem a long time ago. NoSQL has more to do with the layers on top of the DBM; the distributed, sometimes-consistent, partitioned, scale-out storage that manage key/value or document sets and generally have some form of simple HTTP/REST-style network API. Does Berkeley DB do that? Not really. Is Berkeley DB a "NoSQL" solution today? Nope, but it's the most robust solution on which to build such a system. Re-inventing the node-local data storage isn't easy. A lot of people are starting to come to appreciate the sophisticated features found in Berkeley DB, even mimic them in some cases. Could Berkeley DB grow into a NoSQL solution? Absolutely. Our key/value API could be extended over the net using any of a number of existing network protocols such as memcache or HTTP/REST. We could adapt our node-local data partitioning out over replicated nodes. We even have a nice query language and cost-based query optimizer in our BDB XML product that we could reuse were we to build out a document-based NoSQL-style product. XML and JSON are not so different that we couldn't adapt one to work with the other interchangeably. Without too much effort we could add what's missing, we could jump into this No SQL market withing a single product development cycle. Why isn't Berkeley DB already a NoSQL solution? Why aren't we working on it? Why indeed...

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• Company Review: Google Products

  Google, Inc offers an array of products and services to all of its end-users. However their search capabilities are the foundation for Google’s current success and their primary business focus. Currently, Google offers over twenty different search applications that allow users to search the internet for books, maps, videos, images, products and much more. Their product decisions have allowed users demands to be met while focusing on the free based model. This allows users to access Google data free of charge and indirectly gives Google a strong competitive advantage of other competitors along with the accuracy of the search results. According to Google, Inc, they offer the following types of searching capabilities: Alerts Get email updates on the topics of your choice Blog Search Find blogs on your favorite topics  Books Search the full text of books  Custom Search Create a customized search experience for your community  Desktop Search and personalize your computer  Dictionary Search for definitions of words and phrases Directory Search the web, organized by topic or category Earth Explore the world from your computer Finance Business info, news and interactive charts GOOG-411 Find and connect for free with businesses from your phone  Images Search for images on the web Maps View maps and directions News Search thousands of news stories Patent Search Search the full text of US Patents Product Search Search for stuff to buy Scholar Search scholarly papers Toolbar Add a search box to your browser Trends Explore past and present search trends Videos Search for videos on the web Web Search Search billions of web pages Web Search Features Find movies, music, stocks, books and more mapping Google’s free based business model is only one way it differentiates itself from its competition. There is also a strong focus on the accuracy of search results and the speed in which they are returned to the end-user. Quality function deployment (QFD) is a structured method used to help connect user needs to the design features of a project proposed to address those needs. This method is particularly useful in accounting for needs that are not easily articulated or precisely defined according to the U. S. Department of Transportation Federal Highway Administration. Due to the fact that QFD is so customer driven Google is always in a constant state of change in attempt to reengineer its search algorithms, and other dependant systems so that end-users requirements are constantly being met. Value engineering is a key example of this, Google is constantly trying to improve all aspects of its products, improve system maintainability, and system interoperability. Bridgefield Group defines value engineering as an organized methodology that identifies and selects the lowest lifecycle cost options in design, materials and processes that achieves the desired level of performance, reliability and customer satisfaction. In addition, it seeks to remove unnecessary costs in the above areas and is often a joint effort with cross-functional internal teams and relevant suppliers. Common issues that appear when developing large scale systems like Google’s search applications include modular design of a product and/or service and providing accurate value analysis. A design approach that adheres to four fundamental tenets of cohesiveness, encapsulation, self-containment, and high binding to design a system component as an independently operable unit subject to change is how the Open System Joint Task Force defines modular design. More specifically M. S. Schmaltz defines modular software design as having a large collection of statements strung together in one partition of in-line code; we segment or divide the statements into logical groups called modules. Each module performs one or two tasks, and then passes control to another module. By breaking up the code into "bite-sized chunks", so to speak, we are able to better control the flow of data and control. This is especially true in large software systems. Value analysis is a process to evaluate products and services based on effectiveness, safety, and cost. Value analysis involves assessing the quality as well as the cost of a product or service as defined by the Healthcare Financial Management Association.  “Operations Management deals with the design and management of products, processes, services and supply chains. It considers the acquisition, development, and utilization of resources that firms need to deliver the goods and services their clients want.” (MIT,2010) Google, Inc encourages an open environment between all employees, also known as Googlers. This is reinforced by a cross-section team or cross-functional teams comprised from multiple departments assigned to every project so that every department like marketing, finance, and quality assurance has input on every project. In addition, Google is known for their openness to new ideas regardless of the status or seniority of an employee. In fact, Google allows for 20% of an employee’s time can be devoted to developing new ideas and/or pet projects. HumTech.com defines a cross-functional team as a collection of people with varied levels of skills and experience brought together to accomplish a task. As the name implies, Cross-Functional Team members come from different organizational units. Cross-Functional Teams may be permanent or ad hoc. Google’s search application product strategy primarily focuses on mass customization. This is allows Google to create a base search application and allows results to be returned to the end-users quickly based on specific parameters and search settings. In addition, they also store the data that is returned in case other desire the same results based on other end-users supplying the same customized settings. This allows Google to appear to render search results in virtually real-time to the user while allowing for complete customization of the searching criteria. Greg Vogl, a professor at Uganda Martyrs University, defines mass customization as when a business gives its customers the opportunity to tailor its products or services to the customer's specifications. The IT staff at Google play a key role in ensuring that the search application’s product strategy is maintained simply because the IT staff designs, develops, and maintains all of their proprietary applications. In fact, they also maintain all network infrastructure to ensure that it is available to all end-users. References: http://www.google.com/intl/en/options/ http://ops.fhwa.dot.gov/freight/publications/ftat_user_guide/sec5.htm http://www.bridgefieldgroup.com/bridgefieldgroup/glos9.htm#V http://www.acq.osd.mil/osjtf/termsdef.html http://www.cise.ufl.edu/~mssz/Pascal-CGS2462/prog-dsn.html http://www.hfma.org/publications/business_caring_newsletter/exclusives/Supply+and+Inventory+Terms+Defined.htm http://mitsloan.mit.edu/omg/om-definition.php http://www.humtech.com/opm/grtl/ols/ols3.cfm http://www.gregvogl.net/courses/mis1/glossary.htm

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• Help me solve my problem with NPR Media Player

  - by Calcipher

  First of, let me apologize for this getting a bit technical. Several weeks ago, I found that while using NPR's media player (e.g. click on 'Listen to the Show' - this is what I've been using as a test) the stream would suddenly halt after a minute or three. I could not get the stream to restart without reloading the page. Now, I assumed this was an issue with NPR's player and Linux (or just a bug in their stuff in general) so I began to dig, the following is what I have tried to date (please note, the tldr; option is to skip to the latest thing as I think I know what is causing the problem). Note: All testing has been done, for consistency purposes, on a clean install of Chromium with no pluggins running. My machine is Ubuntu 10.10x64. First thing I always try, I disabled all firewall stuff on the system (UFW, default deny all, allow ssh). No change, firewall back up for all additional tests unless otherwise noted. In any case, UFW is stateful, so connections it started on a non-specified on different ports will continue to work. I deleted my ~/.macromeda and ~/.adobe folders, restarted (just to be sure) and tried. Program still froze. I decided the problem might be with my install of flash, so I purged the version I had (and the home folders again). I installed the x64 version of flash from a PPA. This had no effect. I decided that the problem might be with the version of flash, so I purged the x64 version and installed the standard x32 version that comes with Ubuntu. No luck. Back to the x64 version for consistency, I decided to set up a 64-bit mini 'clone' of my system in VirtualBox. I was able to run the media player with no problem. I rsynced (in archive mode) my home directory from my real machine to the virtual machine (with bridged networking, so it was fully visible on the network). I also used a few tricks to install ALL of the same software (and repositories) from the real machine to the virtual machine. I was still able to listen to the player. I decided that the problem was with my install (after all, it had gone through two major version upgrades). As I have /home/ on a separate partition it was easy to reinstall and use the same trick from #6 to have my system up and running again within about an hour. I continue to have issues with the NPR Media Player. By this point the weekend had come. At work, I use a wired connection while at home I use a wireless connection. For some reason I forgot that I was having problems and used the NPR Media Player over the weekend. Low and behold it worked just fine at home on wireless (note: for various reasons, I could not test this on wired at home). Following from #6, I decided that the problem was either something with the network at work or still something with my account. As the latter was easier to test, I created a new account on my system and used that at work. The Media Player worked. At a loss, I decided to watch the traffic with tshark (the text based brother of wireshark) - X's to protect the innocent, I am the XXX.24.200.XXX: sudo tshark -i eth0 -p -t a -R "ip.addr == XXX.24.200.XXX && ip.addr == XXX.166.98.XXX" As you would expect, there were tons and tons of packets, but each and every time the player froze, this is what I got 08:42:20.679200 XXX.166.98.XXX - XXX.24.200.XXX TCP macromedia-fcs 56371 [PSH, ACK] Seq=817686 Ack=6 Win=65535 Len=1448 TSV=495713325 TSER=396467 08:42:20.718602 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=396475 TSER=495713325 08:42:21.050183 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495713362 TSER=396475 08:42:21.050221 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=396508 TSER=495713362 08:42:21.680548 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495713425 TSER=396508 08:42:21.680605 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=396571 TSER=495713425 08:42:22.910354 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495713548 TSER=396571 08:42:22.910400 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=396694 TSER=495713548 08:42:25.340458 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495713791 TSER=396694 08:42:25.340517 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=396937 TSER=495713791 08:42:30.170698 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495714274 TSER=396937 08:42:30.170746 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=397420 TSER=495714274 08:42:39.801738 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495715237 TSER=397420 08:42:39.801784 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=398383 TSER=495715237 08:42:59.032648 XXX.166.98.XXX - XXX.24.200.XXX TCP [TCP ZeroWindowProbe] macromedia-fcs 56371 [ACK] Seq=819134 Ack=6 Win=65535 Len=1 TSV=495717160 TSER=398383 08:42:59.032696 XXX.24.200.XXX - XXX.166.98.XXX TCP [TCP ZeroWindowProbeAck] [TCP ZeroWindow] 56371 macromedia-fcs [ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=400306 TSER=495717160 08:43:00.267721 XXX.24.200.XXX - XXX.166.98.XXX TCP 56371 macromedia-fcs [FIN, ACK] Seq=6 Ack=819134 Win=0 Len=0 TSV=400430 TSER=495717160 08:43:00.267827 XXX.24.200.XXX - XXX.166.98.XXX TCP 56371 macromedia-fcs [RST, ACK] Seq=7 Ack=819134 Win=65535 Len=0 TSV=400430 TSER=495717160 So, as you can see, my machine is sending out a ZeroWindow packet (which I think means some buffer or another filled up) which causes the Media Player to halt (unfortunately, terminally - no controls on it really do anything anymore). Any ideas, at all, what would cause this? Why only on eth0 under my main account?

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• GoldenGate 12c Trail Encryption and Credentials with Oracle Wallet

  - by hamsun

  I have been asked more than once whether the Oracle Wallet supports GoldenGate trail encryption. Although GoldenGate has supported encryption with the ENCKEYS file for years, Oracle GoldenGate 12c now also supports encryption using the Oracle Wallet. This helps improve security and makes it easier to administer. Two types of wallets can be configured in Oracle GoldenGate 12c: The wallet that holds the master keys, used with trail or TCP/IP encryption and decryption, stored in the new 12c dirwlt/cwallet.sso file.   The wallet that holds the Oracle Database user IDs and passwords stored in the ‘credential store’ stored in the new 12c dircrd/cwallet.sso file.   A wallet can be created using a ‘create wallet’  command.  Adding a master key to an existing wallet is easy using ‘open wallet’ and ‘add masterkey’ commands.   GGSCI (EDLVC3R27P0) 42> open wallet Opened wallet at location 'dirwlt'. GGSCI (EDLVC3R27P0) 43> add masterkey Master key 'OGG_DEFAULT_MASTERKEY' added to wallet at location 'dirwlt'.   Existing GUI Wallet utilities that come with other products such as the Oracle Database “Oracle Wallet Manager” do not work on this version of the wallet. The default Oracle Wallet can be changed.   GGSCI (EDLVC3R27P0) 44> sh ls -ltr ./dirwlt/* -rw-r----- 1 oracle oinstall 685 May 30 05:24 ./dirwlt/cwallet.sso GGSCI (EDLVC3R27P0) 45> info masterkey Masterkey Name:                 OGG_DEFAULT_MASTERKEY Creation Date:                  Fri May 30 05:24:04 2014 Version:        Creation Date:                  Status: 1               Fri May 30 05:24:04 2014        Current   The second wallet file is used for the credential used to connect to a database, without exposing the user id or password. Once it is configured, this file can be copied so that credentials are available to connect to the source or target database.   GGSCI (EDLVC3R27P0) 48> sh cp ./dircrd/cwallet.sso $GG_EURO_HOME/dircrd GGSCI (EDLVC3R27P0) 49> sh ls -ltr ./dircrd/* -rw-r----- 1 oracle oinstall 709 May 28 05:39 ./dircrd/cwallet.sso   The encryption wallet file can also be copied to the target machine so the replicat has access to the master key to decrypt records that are encrypted in the trail. Similar to the old ENCKEYS file, the master keys wallet created on the source host must either be stored in a centrally available disk or copied to all GoldenGate target hosts. The wallet is in a platform-independent format, although it is not certified for the iSeries, z/OS, and NonStop platforms.   GGSCI (EDLVC3R27P0) 50> sh cp ./dirwlt/cwallet.sso $GG_EURO_HOME/dirwlt   The new 12c UserIdAlias parameter is used to locate the credential in the wallet so the source user id and password does not need to be stored as a parameter as long as it is in the wallet.   GGSCI (EDLVC3R27P0) 52> view param extwest extract extwest exttrail ./dirdat/ew useridalias gguamer table west.*; The EncryptTrail parameter is used to encrypt the trail using the Advanced Encryption Standard and can be used with a primary extract or pump extract. GGSCI (EDLVC3R27P0) 54> view param pwest extract pwest encrypttrail AES256 rmthost easthost, mgrport 15001 rmttrail ./dirdat/pe passthru table west.*;   Once the extracts are running, records can be encrypted using the wallet.   GGSCI (EDLVC3R27P0) 60> info extract *west EXTRACT    EXTWEST   Last Started 2014-05-30 05:26   Status RUNNING Checkpoint Lag       00:00:17 (updated 00:00:01 ago) Process ID           24982 Log Read Checkpoint  Oracle Integrated Redo Logs                      2014-05-30 05:25:53                      SCN 0.0 (0) EXTRACT    PWEST     Last Started 2014-05-30 05:26   Status RUNNING Checkpoint Lag       24:02:32 (updated 00:00:05 ago) Process ID           24983 Log Read Checkpoint  File ./dirdat/ew000004                      2014-05-29 05:23:34.748949  RBA 1483   The ‘info masterkey’ command is used to confirm the wallet contains the key after copying it to the target machine. The key is needed to decrypt the data in the trail before the replicat applies the changes to the target database.   GGSCI (EDLVC3R27P0) 41> open wallet Opened wallet at location 'dirwlt'. GGSCI (EDLVC3R27P0) 42> info masterkey Masterkey Name:                 OGG_DEFAULT_MASTERKEY Creation Date:                  Fri May 30 05:24:04 2014 Version:        Creation Date:                  Status: 1               Fri May 30 05:24:04 2014        Current   Once the replicat is running, records can be decrypted using the wallet.   GGSCI (EDLVC3R27P0) 44> info reast REPLICAT   REAST     Last Started 2014-05-30 05:28   Status RUNNING INTEGRATED Checkpoint Lag       00:00:00 (updated 00:00:02 ago) Process ID           25057 Log Read Checkpoint  File ./dirdat/pe000004                      2014-05-30 05:28:16.000000  RBA 1546   There is no need for the DecryptTrail parameter when using the Oracle Wallet, unlike when using the ENCKEYS file.   GGSCI (EDLVC3R27P0) 45> view params reast replicat reast assumetargetdefs discardfile ./dirrpt/reast.dsc, purge useridalias ggueuro map west.*, target east.*;   Once a record is inserted into the source table and committed, the encryption can be verified using logdump and then querying the target table.   AMER_SQL>insert into west.branch values (50, 80071); 1 row created.   AMER_SQL>commit; Commit complete.   The following encrypted record can be found using logdump. Logdump 40 >n 2014/05/30 05:28:30.001.154 Insert               Len    28 RBA 1546 Name: WEST.BRANCH After  Image:                                             Partition 4   G  s    0a3e 1ba3 d924 5c02 eade db3f 61a9 164d 8b53 4331 | .>...$\....?a..M.SC1   554f e65a 5185 0257                               | UO.ZQ..W  Bad compressed block, found length of  7075 (x1ba3), RBA 1546   GGS tokens: TokenID x52 'R' ORAROWID         Info x00  Length   20  4141 4157 7649 4141 4741 4141 4144 7541 4170 0001 | AAAWvIAAGAAAADuAAp..  TokenID x4c 'L' LOGCSN           Info x00  Length    7  3231 3632 3934 33                                 | 2162943  TokenID x36 '6' TRANID           Info x00  Length   10  3130 2e31 372e 3135 3031                          | 10.17.1501  The replicat automatically decrypted this record from the trail and then inserted the row to the target table using the wallet. This select verifies the row was inserted into the target database and the data is not encrypted. EURO_SQL>select * from branch where branch_number=50; BRANCH_NUMBER                  BRANCH_ZIP -------------                                   ----------    50                                              80071   Book a seat in an upcoming Oracle GoldenGate 12c: Fundamentals for Oracle course now to learn more about GoldenGate 12c new features including how to use GoldenGate with the Oracle wallet, credentials, integrated extracts, integrated replicats, the Oracle Universal Installer, and other new features. Looking for another course? View all Oracle GoldenGate training.   Randy Richeson joined Oracle University as a Senior Principal Instructor in March 2005. He is an Oracle Certified Professional (10g-12c) and a GoldenGate Certified Implementation Specialist (10-11g). He has taught GoldenGate since 2010 and also has experience teaching other technical curriculums including GoldenGate Monitor, Veridata, JD Edwards, PeopleSoft, and the Oracle Application Server.

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• MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

  - by Mat Keep

  0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE /* 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-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark What’s New in MySQL Cluster 7.2 MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use Once of the key enhancements delivered in MySQL Cluster 7.2 is extensions made to the multi-threading processes of the data nodes. Multi-Threaded Data Node Extensions The MySQL Cluster 7.2 data node is now functionally divided into seven thread types: 1) Local Data Manager threads (ldm). Note – these are sometimes also called LQH threads. 2) Transaction Coordinator threads (tc) 3) Asynchronous Replication threads (rep) 4) Schema Management threads (main) 5) Network receiver threads (recv) 6) Network send threads (send) 7) IO threads Each of these thread types are discussed in more detail below. MySQL Cluster 7.2 increases the maximum number of LDM threads from 4 to 16. The LDM contains the actual data, which means that when using 16 threads the data is more heavily partitioned (this is automatic in MySQL Cluster). Each LDM thread maintains its own set of data partitions, index partitions and REDO log. The number of LDM partitions per data node is not dynamically configurable, but it is possible, however, to map more than one partition onto each LDM thread, providing flexibility in modifying the number of LDM threads. The TC domain stores the state of in-flight transactions. This means that every new transaction can easily be assigned to a new TC thread. Testing has shown that in most cases 1 TC thread per 2 LDM threads is sufficient, and in many cases even 1 TC thread per 4 LDM threads is also acceptable. Testing also demonstrated that in some instances where the workload needed to sustain very high update loads it is necessary to configure 3 to 4 TC threads per 4 LDM threads. In the previous MySQL Cluster 7.1 release, only one TC thread was available. This limit has been increased to 16 TC threads in MySQL Cluster 7.2. The TC domain also manages the Adaptive Query Localization functionality introduced in MySQL Cluster 7.2 that significantly enhanced complex query performance by pushing JOIN operations down to the data nodes. Asynchronous Replication was separated into its own thread with the release of MySQL Cluster 7.1, and has not been modified in the latest 7.2 release. To scale the number of TC threads, it was necessary to separate the Schema Management domain from the TC domain. The schema management thread has little load, so is implemented with a single thread. The Network receiver domain was bound to 1 thread in MySQL Cluster 7.1. With the increase of threads in MySQL Cluster 7.2 it is also necessary to increase the number of recv threads to 8. This enables each receive thread to service one or more sockets used to communicate with other nodes the Cluster. The Network send thread is a new thread type introduced in MySQL Cluster 7.2. Previously other threads handled the sending operations themselves, which can provide for lower latency. To achieve highest throughput however, it has been necessary to create dedicated send threads, of which 8 can be configured. It is still possible to configure MySQL Cluster 7.2 to a legacy mode that does not use any of the send threads – useful for those workloads that are most sensitive to latency. The IO Thread is the final thread type and there have been no changes to this domain in MySQL Cluster 7.2. Multiple IO threads were already available, which could be configured to either one thread per open file, or to a fixed number of IO threads that handle the IO traffic. Except when using compression on disk, the IO threads typically have a very light load. Benchmarking the Scalability Enhancements The scalability enhancements discussed above have made it possible to scale CPU usage of each data node to more than 5x of that possible in MySQL Cluster 7.1. In addition, a number of bottlenecks have been removed, making it possible to scale data node performance by even more than 5x. Figure 2: MySQL Cluster 7.2 Delivers 8.4x Higher Performance than 7.1 The flexAsynch benchmark was used to compare MySQL Cluster 7.2 performance to 7.1 across an 8-node Intel Xeon x5670-based cluster of dual socket commodity servers (6 cores each). As the results demonstrate, MySQL Cluster 7.2 delivers over 8x higher performance per data nodes than MySQL Cluster 7.1. More details of this and other benchmarks will be published in a new whitepaper – coming soon, so stay tuned! In a following blog post, I’ll provide recommendations on optimum thread configurations for different types of server processor. You can also learn more from the Best Practices Guide to Optimizing Performance of MySQL Cluster Conclusion MySQL Cluster has achieved a range of impressive benchmark results, and set in context with the previous 7.1 release, is able to deliver over 8x higher performance per node. As a result, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs.

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• Combination of Operating Mode and Commit Strategy

  - by Kevin Yang

  If you want to populate a source into multiple targets, you may also want to ensure that every row from the source affects all targets uniformly (or separately). Let’s consider the Example Mapping below. If a row from SOURCE causes different changes in multiple targets (TARGET_1, TARGET_2 and TARGET_3), for example, it can be successfully inserted into TARGET_1 and TARGET_3, but failed to be inserted into TARGET_2, and the current Mapping Property TLO (target load order) is “TARGET_1 -> TARGET_2 -> TARGET_3”. What should Oracle Warehouse Builder do, in order to commit the appropriate data to all affected targets at the same time? If it doesn’t behave as you intended, the data could become inaccurate and possibly unusable.                                               Example Mapping In OWB, we can use Mapping Configuration Commit Strategies and Operating Modes together to achieve this kind of requirements. Below we will explore the combination of these two features and how they affect the results in the target tables Before going to the example, let’s review some of the terms we will be using (Details can be found in white paper Oracle® Warehouse Builder Data Modeling, ETL, and Data Quality Guide11g Release 2): Operating Modes: Set-Based Mode: Warehouse Builder generates a single SQL statement that processes all data and performs all operations. Row-Based Mode: Warehouse Builder generates statements that process data row by row. The select statement is in a SQL cursor. All subsequent statements are PL/SQL. Row-Based (Target Only) Mode: Warehouse Builder generates a cursor select statement and attempts to include as many operations as possible in the cursor. For each target, Warehouse Builder inserts each row into the target separately. Commit Strategies: Automatic: Warehouse Builder loads and then automatically commits data based on the mapping design. If the mapping has multiple targets, Warehouse Builder commits and rolls back each target separately and independently of other targets. Use the automatic commit when the consequences of multiple targets being loaded unequally are not great or are irrelevant. Automatic correlated: It is a specialized type of automatic commit that applies to PL/SQL mappings with multiple targets only. Warehouse Builder considers all targets collectively and commits or rolls back data uniformly across all targets. Use the correlated commit when it is important to ensure that every row in the source affects all affected targets uniformly. Manual: select manual commit control for PL/SQL mappings when you want to interject complex business logic, perform validations, or run other mappings before committing data. Combination of the commit strategy and operating mode To understand the effects of each combination of operating mode and commit strategy, I’ll illustrate using the following example Mapping. Firstly we insert 100 rows into the SOURCE table and make sure that the 99th row and 100th row have the same ID value. And then we create a unique key constraint on ID column for TARGET_2 table. So while running the example mapping, OWB tries to load all 100 rows to each of the targets. But the mapping should fail to load the 100th row to TARGET_2, because it will violate the unique key constraint of table TARGET_2. With different combinations of Commit Strategy and Operating Mode, here are the results ¦ Set-based/ Correlated Commit: Configuration of Example mapping:                                                     Result:                                                      What’s happening: A single error anywhere in the mapping triggers the rollback of all data. OWB encounters the error inserting into Target_2, it reports an error for the table and does not load the row. OWB rolls back all the rows inserted into Target_1 and does not attempt to load rows to Target_3. No rows are added to any of the target tables. ¦ Row-based/ Correlated Commit: Configuration of Example mapping:                                                   Result:                                                  What’s happening: OWB evaluates each row separately and loads it to all three targets. Loading continues in this way until OWB encounters an error loading row 100th to Target_2. OWB reports the error and does not load the row. It rolls back the row 100th previously inserted into Target_1 and does not attempt to load row 100 to Target_3. Then, if there are remaining rows, OWB will continue loading them, resuming with loading rows to Target_1. The mapping completes with 99 rows inserted into each target. ¦ Set-based/ Automatic Commit: Configuration of Example mapping: Result: What’s happening: When OWB encounters the error inserting into Target_2, it does not load any rows and reports an error for the table. It does, however, continue to insert rows into Target_3 and does not roll back the rows previously inserted into Target_1. The mapping completes with one error message for Target_2, no rows inserted into Target_2, and 100 rows inserted into Target_1 and Target_3 separately. ¦ Row-based/Automatic Commit: Configuration of Example mapping: Result: What’s happening: OWB evaluates each row separately for loading into the targets. Loading continues in this way until OWB encounters an error loading row 100 to Target_2 and reports the error. OWB does not roll back row 100th from Target_1, does insert it into Target_3. If there are remaining rows, it will continue to load them. The mapping completes with 99 rows inserted into Target_2 and 100 rows inserted into each of the other targets. Note: Automatic Correlated commit is not applicable for row-based (target only). If you design a mapping with the row-based (target only) and correlated commit combination, OWB runs the mapping but does not perform the correlated commit. In set-based mode, correlated commit may impact the size of your rollback segments. Space for rollback segments may be a concern when you merge data (insert/update or update/insert). Correlated commit operates transparently with PL/SQL bulk processing code. The correlated commit strategy is not available for mappings run in any mode that are configured for Partition Exchange Loading or that include a Queue, Match Merge, or Table Function operator. If you want to practice in your own environment, you can follow the steps: 1. Import the MDL file: commit_operating_mode.mdl 2. Fix the location for oracle module ORCL and deploy all tables under it. 3. Insert sample records into SOURCE table, using below plsql code: begin     for i in 1..99     loop         insert into source values(i, 'col_'||i);     end loop;     insert into source values(99, 'col_99'); end; 4. Configure MAPPING_1 to any combinations of operating mode and commit strategy you want to test. And make sure feature TLO of mapping is open. 5. Deploy Mapping “MAPPING_1”. 6. Run the mapping and check the result.

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• External usb 3.0 hard drive is not recognised when plugged into usb 3 port (ubuntu natty 64 bit).

  - by kimangroo

  I have an Iomega Prestige Portable External Hard Drive 1TB USB 3.0. It works fine on windows 7 as a usb 3.0 drive. It isn't detected on ubuntu natty 64bit, 2.6.38-8-generic. fdisk -l cannot see it at all: Disk /dev/sda: 500.1 GB, 500107862016 bytes 255 heads, 63 sectors/track, 60801 cylinders Units = cylinders of 16065 * 512 = 8225280 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x1bed746b Device Boot Start End Blocks Id System /dev/sda1 1 1689 13560832 27 Unknown /dev/sda2 * 1689 1702 102400 7 HPFS/NTFS /dev/sda3 1702 19978 146805760 7 HPFS/NTFS /dev/sda4 19978 60802 327914497 5 Extended /dev/sda5 25555 60802 283120640 7 HPFS/NTFS /dev/sda6 19978 23909 31571968 83 Linux /dev/sda7 23909 25555 13218816 82 Linux swap / Solaris Partition table entries are not in disk order lsusb can see it: Bus 003 Device 003: ID 059b:0070 Iomega Corp. Bus 003 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 002 Device 004: ID 05fe:0011 Chic Technology Corp. Browser Mouse Bus 002 Device 003: ID 0a12:0001 Cambridge Silicon Radio, Ltd Bluetooth Dongle (HCI mode) Bus 002 Device 002: ID 8087:0024 Intel Corp. Integrated Rate Matching Hub Bus 002 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 001 Device 005: ID 0489:e00f Foxconn / Hon Hai Bus 001 Device 004: ID 0c45:64b5 Microdia Bus 001 Device 003: ID 08ff:168f AuthenTec, Inc. Bus 001 Device 002: ID 8087:0024 Intel Corp. Integrated Rate Matching Hub Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub And dmesg | grep -i xhci (I may have unplugged the drive and plugged it back in again after booting): [ 1.659060] pci 0000:04:00.0: xHCI HW did not halt within 2000 usec status = 0x0 [ 11.484971] xhci_hcd 0000:04:00.0: PCI INT A -> GSI 18 (level, low) -> IRQ 18 [ 11.484997] xhci_hcd 0000:04:00.0: setting latency timer to 64 [ 11.485002] xhci_hcd 0000:04:00.0: xHCI Host Controller [ 11.485064] xhci_hcd 0000:04:00.0: new USB bus registered, assigned bus number 3 [ 11.636149] xhci_hcd 0000:04:00.0: irq 18, io mem 0xc5400000 [ 11.636241] xhci_hcd 0000:04:00.0: irq 43 for MSI/MSI-X [ 11.636246] xhci_hcd 0000:04:00.0: irq 44 for MSI/MSI-X [ 11.636251] xhci_hcd 0000:04:00.0: irq 45 for MSI/MSI-X [ 11.636256] xhci_hcd 0000:04:00.0: irq 46 for MSI/MSI-X [ 11.636261] xhci_hcd 0000:04:00.0: irq 47 for MSI/MSI-X [ 11.639654] xHCI xhci_add_endpoint called for root hub [ 11.639655] xHCI xhci_check_bandwidth called for root hub [ 11.956366] usb 3-1: new SuperSpeed USB device using xhci_hcd and address 2 [ 12.001073] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.007059] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.012932] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.018922] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.049139] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.056754] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.131607] xhci_hcd 0000:04:00.0: WARN no SS endpoint bMaxBurst [ 12.179717] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 12.686876] xhci_hcd 0000:04:00.0: WARN: babble error on endpoint [ 12.687058] xhci_hcd 0000:04:00.0: WARN Set TR Deq Ptr cmd invalid because of stream ID configuration [ 12.687152] xhci_hcd 0000:04:00.0: ERROR Transfer event for disabled endpoint or incorrect stream ring [ 43.330737] usb 3-1: reset SuperSpeed USB device using xhci_hcd and address 2 [ 43.422579] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 43.422658] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff88014669af00 [ 43.422665] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff88014669af40 [ 43.422671] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff88014669af80 [ 43.422677] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff88014669afc0 [ 43.531159] xhci_hcd 0000:04:00.0: WARN no SS endpoint bMaxBurst [ 125.160248] xhci_hcd 0000:04:00.0: WARN no SS endpoint bMaxBurst [ 903.766466] usb 3-1: new SuperSpeed USB device using xhci_hcd and address 3 [ 903.807789] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 903.813530] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 903.819400] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 903.825104] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 903.855067] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 903.862314] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 903.862597] xhci_hcd 0000:04:00.0: WARN no SS endpoint bMaxBurst [ 903.913211] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 904.424416] xhci_hcd 0000:04:00.0: WARN: babble error on endpoint [ 904.424599] xhci_hcd 0000:04:00.0: WARN Set TR Deq Ptr cmd invalid because of stream ID configuration [ 904.424700] xhci_hcd 0000:04:00.0: ERROR Transfer event for disabled endpoint or incorrect stream ring [ 935.139021] usb 3-1: reset SuperSpeed USB device using xhci_hcd and address 3 [ 935.226075] xhci_hcd 0000:04:00.0: WARN: short transfer on control ep [ 935.226140] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff880148186b00 [ 935.226148] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff880148186b40 [ 935.226153] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff880148186b80 [ 935.226159] xhci_hcd 0000:04:00.0: xHCI xhci_drop_endpoint called with disabled ep ffff880148186bc0 [ 935.343339] xhci_hcd 0000:04:00.0: WARN no SS endpoint bMaxBurst I thought it might be that the firmware wasn't compatible with linux or something, but when booting a live image of partedmagic, (2.6.38.4-pmagic), the drive was detected fine, I could mount it and got usb 3.0 speeds (at least they double the speeds I got from plugging same drive in usb 2 ports). dmesg in partedmagic did say something about no SuperSpeed endpoint which was an error I saw in a previous dmesg of ubuntu: Jun 27 15:49:02 (none) user.info kernel: [ 2.978743] xhci_hcd 0000:04:00.0: PCI INT A -> GSI 18 (level, low) -> IRQ 18 Jun 27 15:49:02 (none) user.debug kernel: [ 2.978771] xhci_hcd 0000:04:00.0: setting latency timer to 64 Jun 27 15:49:02 (none) user.info kernel: [ 2.978781] xhci_hcd 0000:04:00.0: xHCI Host Controller Jun 27 15:49:02 (none) user.info kernel: [ 2.978856] xhci_hcd 0000:04:00.0: new USB bus registered, assigned bus number 3 Jun 27 15:49:02 (none) user.info kernel: [ 3.089458] xhci_hcd 0000:04:00.0: irq 18, io mem 0xc5400000 Jun 27 15:49:02 (none) user.debug kernel: [ 3.089541] xhci_hcd 0000:04:00.0: irq 42 for MSI/MSI-X Jun 27 15:49:02 (none) user.debug kernel: [ 3.089544] xhci_hcd 0000:04:00.0: irq 43 for MSI/MSI-X Jun 27 15:49:02 (none) user.debug kernel: [ 3.089546] xhci_hcd 0000:04:00.0: irq 44 for MSI/MSI-X Jun 27 15:49:02 (none) user.debug kernel: [ 3.089548] xhci_hcd 0000:04:00.0: irq 45 for MSI/MSI-X Jun 27 15:49:02 (none) user.debug kernel: [ 3.089550] xhci_hcd 0000:04:00.0: irq 46 for MSI/MSI-X Jun 27 15:49:02 (none) user.warn kernel: [ 3.092857] usb usb3: No SuperSpeed endpoint companion for config 1 interface 0 altsetting 0 ep 129: using minimum values Jun 27 15:49:02 (none) user.info kernel: [ 3.092864] usb usb3: New USB device found, idVendor=1d6b, idProduct=0003 Jun 27 15:49:02 (none) user.info kernel: [ 3.092866] usb usb3: New USB device strings: Mfr=3, Product=2, SerialNumber=1 Jun 27 15:49:02 (none) user.info kernel: [ 3.092867] usb usb3: Product: xHCI Host Controller Jun 27 15:49:02 (none) user.info kernel: [ 3.092869] usb usb3: Manufacturer: Linux 2.6.38.4-pmagic xhci_hcd Jun 27 15:49:02 (none) user.info kernel: [ 3.092870] usb usb3: SerialNumber: 0000:04:00.0 Jun 27 15:49:02 (none) user.debug kernel: [ 3.092961] xHCI xhci_add_endpoint called for root hub Jun 27 15:49:02 (none) user.debug kernel: [ 3.092963] xHCI xhci_check_bandwidth called for root hub Well I have no idea what's going wrong, and I haven't had much luck from google and the forums so far. A number of unanswered threads with people with similar error messages and problems only. Hopefully someone here can help or point me in the right direction?!

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• Hard drive mounted at / , duplicate mounted hard drive after using MountManager

  - by HellHarvest

  possible duplicate post I'm running 12.04 64bit. My system is a dual boot for both Ubuntu and Windows7. Both operating systems are sharing the drive named "Elements". My volume named "Elements" is a 1TB SATA NTFS hard drive that shows up twice in the side bar in nautilus. One of the icons is functional and even has the convenient "eject" icon next to it. Below is a picture of the left menu in Nautilus, with System Monitor-File Systems tab open on top of it. Can someone advise me about how to get rid of this extra icon? I think the problem is much more deep-rooted than just a GUI glitch on Nautilus' part. The other icon does nothing but spit out the following error when I click on it (image below). This only happened AFTER I tried using Mount Manager to automate mounting the drive at start up. I've already uninstalled Mount Manager, and restarted, but the problem didn't go away. The hard drive does mount automatically now, so I guess that's cool. But now, every time I boot up now and open Nautilus, BOTH of these icons appear, one of which is fictitious and useless. According to the image above and the outputs of several other commands, it appears to be mounted at / In which case, no matter where I am in Nautilus when I try to click on that icon, of course it will tell me that that drive is in use by another program... Nautilus. I'm afraid of trying to unmount this hard drive (sdb6) because of where it appears to be mounted. I'm kind of a noob, and I have this gut feeling that tells me trying to unmount a drive at / will destroy my entire file system. This fear was further strengthened by the output of "$ fsck" at the very bottom of this post. Error immediately below when that 2nd "Elements" hard drive is clicked in Nautilus: Unable to mount Elements Mount is denied because the NTFS volume is already exclusively opened. The volume may be already mounted, or another software may use it which could be identified for example by the help of the 'fuser' command. It's odd to me that that error message above claims that it's an NTFS volume when everything else tell me that it's an ext4 volume. The actual hard drive "Elements" is in fact an NTFS volume. Here's the output of a few commands and configuration files that may be of interest: $ fuser -a / /: 2120r 2159rc 2160rc 2172r 2178rc 2180rc 2188r 2191rc 2200rc 2203rc 2205rc 2206r 2211r 2212r 2214r 2220r 2228r 2234rc 2246rc 2249rc 2254rc 2260rc 2261r 2262r 2277rc 2287rc 2291rc 2311rc 2313rc 2332rc 2334rc 2339rc 2343rc 2344rc 2352rc 2372rc 2389rc 2422r 2490r 2496rc 2501rc 2566r 2573rc 2581rc 2589rc 2592r 2603r 2611rc 2613rc 2615rc 2678rc 2927r 2981r 3104rc 4156rc 4196rc 4206rc 4213rc 4240rc 4297rc 5032rc 7609r 7613r 7648r 9593rc 18829r 18833r 19776r $ sudo df -h Filesystem Size Used Avail Use% Mounted on /dev/sdb6 496G 366G 106G 78% / udev 2.0G 4.0K 2.0G 1% /dev tmpfs 791M 1.5M 790M 1% /run none 5.0M 0 5.0M 0% /run/lock none 2.0G 672K 2.0G 1% /run/shm /dev/sda1 932G 312G 620G 34% /media/Elements /home/solderblob/.Private 496G 366G 106G 78% /home/solderblob /dev/sdb2 188G 100G 88G 54% /media/A2B24EACB24E852F /dev/sdb1 100M 25M 76M 25% /media/System Reserved $ sudo fdisk -l Disk /dev/sda: 1000.2 GB, 1000204886016 bytes 255 heads, 63 sectors/track, 121601 cylinders, total 1953525168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x00093cab Device Boot Start End Blocks Id System /dev/sda1 2048 1953519615 976758784 7 HPFS/NTFS/exFAT Disk /dev/sdb: 750.2 GB, 750156374016 bytes 255 heads, 63 sectors/track, 91201 cylinders, total 1465149168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x000e8d9b Device Boot Start End Blocks Id System /dev/sdb1 * 2048 206847 102400 7 HPFS/NTFS/exFAT /dev/sdb2 206848 392378768 196085960+ 7 HPFS/NTFS/exFAT /dev/sdb3 392380414 1465147391 536383489 5 Extended /dev/sdb5 1456762880 1465147391 4192256 82 Linux swap / Solaris /dev/sdb6 392380416 1448374271 527996928 83 Linux /dev/sdb7 1448376320 1456758783 4191232 82 Linux swap / Solaris Partition table entries are not in disk order $ cat /etc/fstab # <file system> <mount point> <type> <options> <dump> <pass> UUID=77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e / ext4 defaults 0 1 UUID=F6549CC4549C88CF /media/Elements ntfs-3g users 0 0 $ sudo blkid /dev/sda1: LABEL="Elements" UUID="F6549CC4549C88CF" TYPE="ntfs" /dev/sdb1: LABEL="System Reserved" UUID="5CDE130FDE12E156" TYPE="ntfs" /dev/sdb2: UUID="A2B24EACB24E852F" TYPE="ntfs" /dev/sdb6: UUID="77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e" TYPE="ext4" $ sudo blkid -c /dev/null (appears to be exactly the same as above) /dev/sda1: LABEL="Elements" UUID="F6549CC4549C88CF" TYPE="ntfs" /dev/sdb1: LABEL="System Reserved" UUID="5CDE130FDE12E156" TYPE="ntfs" /dev/sdb2: UUID="A2B24EACB24E852F" TYPE="ntfs" /dev/sdb6: UUID="77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e" TYPE="ext4" $ mount /dev/sdb6 on / type ext4 (rw) proc on /proc type proc (rw,noexec,nosuid,nodev) sysfs on /sys type sysfs (rw,noexec,nosuid,nodev) none on /sys/fs/fuse/connections type fusectl (rw) none on /sys/kernel/debug type debugfs (rw) none on /sys/kernel/security type securityfs (rw) udev on /dev type devtmpfs (rw,mode=0755) devpts on /dev/pts type devpts (rw,noexec,nosuid,gid=5,mode=0620) tmpfs on /run type tmpfs (rw,noexec,nosuid,size=10%,mode=0755) none on /run/lock type tmpfs (rw,noexec,nosuid,nodev,size=5242880) none on /run/shm type tmpfs (rw,nosuid,nodev) /dev/sda1 on /media/Elements type fuseblk (rw,noexec,nosuid,nodev,allow_other,blksize=4096) binfmt_misc on /proc/sys/fs/binfmt_misc type binfmt_misc (rw,noexec,nosuid,nodev) /home/solderblob/.Private on /home/solderblob type ecryptfs (ecryptfs_check_dev_ruid,ecryptfs_cipher=aes,ecryptfs_key_bytes=16,ecryptfs_unlink_sigs,ecryptfs_sig=76a47b0175afa48d,ecryptfs_fnek_sig=391b2d8b155215f7) gvfs-fuse-daemon on /home/solderblob/.gvfs type fuse.gvfs-fuse-daemon (rw,nosuid,nodev,user=solderblob) /dev/sdb2 on /media/A2B24EACB24E852F type fuseblk (rw,nosuid,nodev,allow_other,default_permissions,blksize=4096) /dev/sdb1 on /media/System Reserved type fuseblk (rw,nosuid,nodev,allow_other,default_permissions,blksize=4096) $ ls -a . A2B24EACB24E852F Ubuntu 12.04.1 LTS amd64 .. Elements System Reserved $ cat /proc/mounts rootfs / rootfs rw 0 0 sysfs /sys sysfs rw,nosuid,nodev,noexec,relatime 0 0 proc /proc proc rw,nosuid,nodev,noexec,relatime 0 0 udev /dev devtmpfs rw,relatime,size=2013000k,nr_inodes=503250,mode=755 0 0 devpts /dev/pts devpts rw,nosuid,noexec,relatime,gid=5,mode=620,ptmxmode=000 0 0 tmpfs /run tmpfs rw,nosuid,relatime,size=809872k,mode=755 0 0 /dev/disk/by-uuid/77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e / ext4 rw,relatime,user_xattr,acl,barrier=1,data=ordered 0 0 none /sys/fs/fuse/connections fusectl rw,relatime 0 0 none /sys/kernel/debug debugfs rw,relatime 0 0 none /sys/kernel/security securityfs rw,relatime 0 0 none /run/lock tmpfs rw,nosuid,nodev,noexec,relatime,size=5120k 0 0 none /run/shm tmpfs rw,nosuid,nodev,relatime 0 0 /dev/sda1 /media/Elements fuseblk rw,nosuid,nodev,noexec,relatime,user_id=0,group_id=0,allow_other,blksize=4096 0 0 binfmt_misc /proc/sys/fs/binfmt_misc binfmt_misc rw,nosuid,nodev,noexec,relatime 0 0 /home/solderblob/.Private /home/solderblob ecryptfs rw,relatime,ecryptfs_fnek_sig=391b2d8b155215f7,ecryptfs_sig=76a47b0175afa48d,ecryptfs_cipher=aes,ecryptfs_key_bytes=16,ecryptfs_unlink_sigs 0 0 gvfs-fuse-daemon /home/solderblob/.gvfs fuse.gvfs-fuse-daemon rw,nosuid,nodev,relatime,user_id=1000,group_id=1000 0 0 /dev/sdb2 /media/A2B24EACB24E852F fuseblk rw,nosuid,nodev,relatime,user_id=0,group_id=0,default_permissions,allow_other,blksize=4096 0 0 /dev/sdb1 /media/System\040Reserved fuseblk rw,nosuid,nodev,relatime,user_id=0,group_id=0,default_permissions,allow_other,blksize=4096 0 0 gvfs-fuse-daemon /root/.gvfs fuse.gvfs-fuse-daemon rw,nosuid,nodev,relatime,user_id=0,group_id=0 0 0 $ fsck fsck from util-linux 2.20.1 e2fsck 1.42 (29-Nov-2011) /dev/sdb6 is mounted. WARNING!!! The filesystem is mounted. If you continue you ***WILL*** cause ***SEVERE*** filesystem damage. Do you really want to continue<n>? no check aborted.

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• SQL SERVER – Weekly Series – Memory Lane – #050

  - by Pinal Dave

  Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Executing Remote Stored Procedure – Calling Stored Procedure on Linked Server In this example we see two different methods of how to call Stored Procedures remotely.  Connection Property of SQL Server Management Studio SSMS A very simple example of the how to build connection properties for SQL Server with the help of SSMS. Sample Example of RANKING Functions – ROW_NUMBER, RANK, DENSE_RANK, NTILE SQL Server has a total of 4 ranking functions. Ranking functions return a ranking value for each row in a partition. All the ranking functions are non-deterministic. T-SQL Script to Add Clustered Primary Key Jr. DBA asked me three times in a day, how to create Clustered Primary Key. I gave him following sample example. That was the last time he asked “How to create Clustered Primary Key to table?” 2008 2008 – TRIM() Function – User Defined Function SQL Server does not have functions which can trim leading or trailing spaces of any string at the same time. SQL does have LTRIM() and RTRIM() which can trim leading and trailing spaces respectively. SQL Server 2008 also does not have TRIM() function. User can easily use LTRIM() and RTRIM() together and simulate TRIM() functionality. http://www.youtube.com/watch?v=1-hhApy6MHM 2009 Earlier I have written two different articles on the subject Remove Bookmark Lookup. This article is as part 3 of original article. Please read the first two articles here before continuing reading this article. Query Optimization – Remove Bookmark Lookup – Remove RID Lookup – Remove Key Lookup Query Optimization – Remove Bookmark Lookup – Remove RID Lookup – Remove Key Lookup – Part 2 Query Optimization – Remove Bookmark Lookup – Remove RID Lookup – Remove Key Lookup – Part 3 Interesting Observation – Query Hint – FORCE ORDER SQL Server never stops to amaze me. As regular readers of this blog already know that besides conducting corporate training, I work on large-scale projects on query optimizations and server tuning projects. In one of the recent projects, I have noticed that a Junior Database Developer used the query hint Force Order; when I asked for details, I found out that the basic concept was not properly understood by him. Queries Waiting for Memory Allocation to Execute In one of the recent projects, I was asked to create a report of queries that are waiting for memory allocation. The reason was that we were doubtful regarding whether the memory was sufficient for the application. The following query can be useful in similar cases. Queries that do not have to wait on a memory grant will not appear in the result set of following query. 2010 Quickest Way to Identify Blocking Query and Resolution – Dirty Solution As the title suggests, this is quite a dirty solution; it’s not as elegant as you expect. However, it works totally fine. Simple Explanation of Data Type Precedence While I was working on creating a question for SQL SERVER – SQL Quiz – The View, The Table and The Clustered Index Confusion, I had actually created yet another question along with this question. However, I felt that the one which is posted on the SQL Quiz is much better than this one because what makes that more challenging question is that it has a multiple answer. Encrypted Stored Procedure and Activity Monitor I recently had received questionable if any stored procedure is encrypted can we see its definition in Activity Monitor.Answer is - No. Let us do a quick test. Let us create following Stored Procedure and then launch the Activity Monitor and check the text. Indexed View always Use Index on Table A single table can have maximum 249 non clustered indexes and 1 clustered index. In SQL Server 2008, a single table can have maximum 999 non clustered indexes and 1 clustered index. It is widely believed that a table can have only 1 clustered index, and this belief is true. I have some questions for all of you. Let us assume that I am creating view from the table itself and then create a clustered index on it. In my view, I am selecting the complete table itself. 2011 Detecting Database Case Sensitive Property using fn_helpcollations() I received a question on how to determine the case sensitivity of the database. The quick answer to this is to identify the collation of the database and check the properties of the collation. I have previously written how one can identify database collation. Once you have figured out the collation of the database, you can put that in the WHERE condition of the following T-SQL and then check the case sensitivity from the description. Server Side Paging in SQL Server CE (Compact Edition) SQL Server Denali is coming up with new T-SQL of Paging. I have written about the same earlier.SQL SERVER – Server Side Paging in SQL Server Denali – A Better Alternative,  SQL SERVER – Server Side Paging in SQL Server Denali Performance Comparison, SQL SERVER – Server Side Paging in SQL Server Denali – Part2 What is very interesting is that SQL Server CE 4.0 have the same feature introduced. Here is the quick example of the same. To run the script in the example, you will have to do installWebmatrix 4.0 and download sample database. Once done you can run following script. Why I am Going to Attend PASS Summit Unite 2011 The four-day event will be marked by a lot of learning, sharing, and networking, which will help me increase both my knowledge and contacts. Every year, PASS Summit provides me a golden opportunity to build my network as well as to identify and meet potential customers or employees. 2012 Manage Help Settings – CTRL + ALT + F1 This is very interesting read as my daughter once accidently came across a screen in SQL Server Management Studio. It took me 2-3 minutes to figure out how she has created the same screen. Recover the Accidentally Renamed Table “I accidentally renamed table in my SSMS. I was scrolling very fast and I made mistakes. It was either because I double clicked or clicked on F2 (shortcut key for renaming). However, I have made the mistake and now I have no idea how to fix this. If you have renamed the table, I think you pretty much is out of luck. Here are few things which you can do which can give you an idea about what your table name can be if you are lucky. Identify Numbers of Non Clustered Index on Tables for Entire Database Here is the script which will give you numbers of non clustered indexes on any table in entire database. Identify Most Resource Intensive Queries – SQL in Sixty Seconds #029 – Video Here is the complete complete script which I have used in the SQL in Sixty Seconds Video. Thanks Harsh for important Tip in the comment. http://www.youtube.com/watch?v=3kDHC_Tjrns Advanced Data Quality Services with Melissa Data – Azure Data Market For the purposes of the review, I used a database I had in an Excel spreadsheet with name and address information. Upon a cursory inspection, there are miscellaneous problems with these records; some addresses are missing ZIP codes, others missing a city, and some records are slightly misspelled or have unparsed suites. With DQS, I can easily add a knowledge base to help standardize my values, such as for state abbreviations. But how do I know that my address is correct? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• How can I remove old kernels/install new ones when /boot is full?

  - by Marcel

  I know this question is asked many times before, however with me it is just a bit different I guess. # df -h Filesystem Size Used Avail Use% Mounted on /dev/sda3 224G 5.2G 208G 3% / udev 1.9G 4.0K 1.9G 1% /dev tmpfs 777M 260K 777M 1% /run none 5.0M 0 5.0M 0% /run/lock none 1.9G 0 1.9G 0% /run/shm /dev/sda2 90M 88M 0 100% /boot /dev/sda6 1.9G 514M 1.3G 29% /tmp My boot partition is full. Current Kernel: # uname -r 3.2.0-35-generic All Kernels: # dpkg --list | grep linux-image ii linux-image-3.2.0-32-generic 3.2.0-32.51 Linux kernel image for version 3.2.0 on 64 bit x86 SMP ii linux-image-3.2.0-34-generic 3.2.0-34.53 Linux kernel image for version 3.2.0 on 64 bit x86 SMP ii linux-image-3.2.0-35-generic 3.2.0-35.55 Linux kernel image for version 3.2.0 on 64 bit x86 SMP iF linux-image-3.2.0-37-generic 3.2.0-37.58 Linux kernel image for version 3.2.0 on 64 bit x86 SMP iF linux-image-3.2.0-38-generic 3.2.0-38.60 Linux kernel image for version 3.2.0 on 64 bit x86 SMP iU linux-image-generic 3.2.0.37.45 Generic Linux kernel image So I thought of removing the 3.2.0.32-generic kernel with: # sudo apt-get purge linux-image-3.2.0-32-generic Reading package lists... Done Building dependency tree Reading state information... Done You might want to run 'apt-get -f install' to correct these: The following packages have unmet dependencies: linux-generic : Depends: linux-headers-generic (= 3.2.0.37.45) but 3.2.0.38.46 is to be installed E: Unmet dependencies. Try 'apt-get -f install' with no packages (or specify a solution). No success. When I try apt-get -f install it also fails: # apt-get -f install Reading package lists... Done Building dependency tree Reading state information... Done Correcting dependencies... Done The following packages were automatically installed and are no longer required: linux-headers-3.2.0-34 linux-headers-3.2.0-35 linux-headers-3.2.0-34-generic linux-headers-3.2.0-35-generic Use 'apt-get autoremove' to remove them. The following extra packages will be installed: linux-generic linux-image-generic The following packages will be upgraded: linux-generic linux-image-generic 2 upgraded, 0 newly installed, 0 to remove and 9 not upgraded. 5 not fully installed or removed. Need to get 0 B/4,334 B of archives. After this operation, 0 B of additional disk space will be used. Do you want to continue [Y/n]? y Setting up initramfs-tools (0.99ubuntu13.1) ... update-initramfs: deferring update (trigger activated) Setting up linux-image-3.2.0-37-generic (3.2.0-37.58) ... Running depmod. update-initramfs: deferring update (hook will be called later) The link /initrd.img is a dangling linkto /boot/initrd.img-3.2.0-38-generic Examining /etc/kernel/postinst.d. run-parts: executing /etc/kernel/postinst.d/initramfs-tools 3.2.0-37-generic /boot/vmlinuz-3.2.0-37-generic update-initramfs: Generating /boot/initrd.img-3.2.0-37-generic gzip: stdout: No space left on device E: mkinitramfs failure cpio 141 gzip 1 update-initramfs: failed for /boot/initrd.img-3.2.0-37-generic with 1. run-parts: /etc/kernel/postinst.d/initramfs-tools exited with return code 1 Failed to process /etc/kernel/postinst.d at /var/lib/dpkg/info/linux-image-3.2.0-37-generic.postinst line 1010. dpkg: error processing linux-image-3.2.0-37-generic (--configure): subprocess installed post-installation script returned error exit status 2 Setting up linux-image-3.2.0-38-generic (3.2.0-38.60) ... Running depmod. update-initramfs: deferring update (hook will be called later) The link /initrd.img is a dangling linkto /boot/initrd.img-3.2.0-37-generic Examining /etc/kernel/postinst.d. run-parts: executing /etc/kernel/postinst.d/initramfs-tools 3.2.0-38-generic /boot/vmlinuz-3.2.0-38-generic update-initramfs: Generating /boot/initrd.img-3.2.0-38-generic gzip: stdout: No space left on device E: mkinitramfs failure cpio 141 gzip 1 update-initramfs: failed for /boot/initrd.img-3.2.0-38-generic with 1. run-parts: /etc/kernel/postinst.d/initramfs-tools exited with return code 1 Failed to process /etc/kernel/postinst.d at /var/lib/dpkg/info/linux-image-3.2.0-38-generic.postinst line 1010. dpkg: error processing linux-image-3.2.0-38-generic (--configure): subprocess installed post-installation script returned error exit status 2 dpkg: dependency problems prevent configuration of linux-image-generic: linux-image-generic depends on linux-image-3.2.0-37-generic; however: Package linux-image-3.2.0-37-generic is not configured yet. dpkg: error processing linux-image-generic (--configure): dependency problems - leaving unconfigured dpkg: dependency problems prevent configuration of linux-generic: linux-generic depends on linux-image-generic (= 3.2.0.37.45); however: Package linux-image-generic is not configured yet. linux-generic depends on linux-headers-generic (= 3.2.0.37.45); however: Version of linux-headers-generic on system is 3.2.0.38.46. dpkg: error processing linux-generic (--configure): dependency problems - leaving unconfigured Processing triggers for initramfs-tools ... No apport report written because the error message indicates its a followup error from a previous failure. No apport report written because MaxReports is reached already update-initramfs: Generating /boot/initrd.img-3.2.0-35-generic gzip: stdout: No space left on device E: mkinitramfs failure cpio 141 gzip 1 update-initramfs: failed for /boot/initrd.img-3.2.0-35-generic with 1. dpkg: error processing initramfs-tools (--configure): subprocess installed post-installation script returned error exit status 1 No apport report written because MaxReports is reached already Errors were encountered while processing: linux-image-3.2.0-37-generic linux-image-3.2.0-38-generic linux-image-generic linux-generic initramfs-tools E: Sub-process /usr/bin/dpkg returned an error code (1) Any help would really be appreciated. Update: I did: sudo rm /boot/*-3.2.0-32-generic /boot/*-3.2.0-34-generic After that the following problem with apt-get -f install: root@localhost:/# apt-get -f install Reading package lists... Done Building dependency tree Reading state information... Done Correcting dependencies... Done The following extra packages will be installed: linux-generic The following packages will be upgraded: linux-generic 1 upgraded, 0 newly installed, 0 to remove and 9 not upgraded. 1 not fully installed or removed. Need to get 0 B/1,722 B of archives. After this operation, 0 B of additional disk space will be used. Do you want to continue [Y/n]? y dpkg: dependency problems prevent configuration of linux-generic: linux-generic depends on linux-image-generic (= 3.2.0.37.45); however: Version of linux-image-generic on system is 3.2.0.38.46. linux-generic depends on linux-headers-generic (= 3.2.0.37.45); however: Version of linux-headers-generic on system is 3.2.0.38.46. dpkg: error processing linux-generic (--configure): dependency problems - leaving unconfigured No apport report written because the error message indicates its a followup error from a previous failure. Errors were encountered while processing: linux-generic E: Sub-process /usr/bin/dpkg returned an error code (1)

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• DBCC CHECKDB on VVLDB and latches (Or: My Pain is Your Gain)

  - by Argenis

    Does your CHECKDB hurt, Argenis? There is a classic blog series by Paul Randal [blog|twitter] called “CHECKDB From Every Angle” which is pretty much mandatory reading for anybody who’s even remotely considering going for the MCM certification, or its replacement (the Microsoft Certified Solutions Master: Data Platform – makes my fingers hurt just from typing it). Of particular interest is the post “Consistency Options for a VLDB” – on it, Paul provides solid, timeless advice (I use the word “timeless” because it was written in 2007, and it all applies today!) on how to perform checks on very large databases. Well, here I was trying to figure out how to make CHECKDB run faster on a restored copy of one of our databases, which happens to exceed 7TB in size. The whole thing was taking several days on multiple systems, regardless of the storage used – SAS, SATA or even SSD…and I actually didn’t pay much attention to how long it was taking, or even bothered to look at the reasons why - as long as it was finishing okay and found no consistency errors. Yes – I know. That was a huge mistake, as corruption found in a database several days after taking place could only allow for further spread of the corruption – and potentially large data loss. In the last two weeks I increased my attention towards this problem, as we noticed that CHECKDB was taking EVEN LONGER on brand new all-flash storage in the SAN! I couldn’t really explain it, and were almost ready to blame the storage vendor. The vendor told us that they could initially see the server driving decent I/O – around 450Mb/sec, and then it would settle at a very slow rate of 10Mb/sec or so. “Hum”, I thought – “CHECKDB is just not pushing the I/O subsystem hard enough”. Perfmon confirmed the vendor’s observations. Dreaded @BlobEater What was CHECKDB doing all the time while doing so little I/O? Eating Blobs. It turns out that CHECKDB was taking an extremely long time on one of our frankentables, which happens to be have 35 billion rows (yup, with a b) and sucks up several terabytes of space in the database. We do have a project ongoing to purge/split/partition this table, so it’s just a matter of time before we deal with it. But the reality today is that CHECKDB is coming to a screeching halt in performance when dealing with this particular table. Checking sys.dm_os_waiting_tasks and sys.dm_os_latch_stats showed that LATCH_EX (DBCC_OBJECT_METADATA) was by far the top wait type. I remembered hearing recently about that wait from another post that Paul Randal made, but that was related to computed-column indexes, and in fact, Paul himself reminded me of his article via twitter. But alas, our pathologic table had no non-clustered indexes on computed columns. I knew that latches are used by the database engine to do internal synchronization – but how could I help speed this up? After all, this is stuff that doesn’t have a lot of knobs to tweak. (There’s a fantastic level 500 talk by Bob Ward from Microsoft CSS [blog|twitter] called “Inside SQL Server Latches” given at PASS 2010 – and you can check it out here. DISCLAIMER: I assume no responsibility for any brain melting that might ensue from watching Bob’s talk!) Failed Hypotheses Earlier on this week I flew down to Palo Alto, CA, to visit our Headquarters – and after having a great time with my Monkey peers, I was relaxing on the plane back to Seattle watching a great talk by SQL Server MVP and fellow MCM Maciej Pilecki [twitter] called “Masterclass: A Day in the Life of a Database Transaction” where he discusses many different topics related to transaction management inside SQL Server. Very good stuff, and when I got home it was a little late – that slow DBCC CHECKDB that I had been dealing with was way in the back of my head. As I was looking at the problem at hand earlier on this week, I thought “How about I set the database to read-only?” I remembered one of the things Maciej had (jokingly) said in his talk: “if you don’t want locking and blocking, set the database to read-only” (or something to that effect, pardon my loose memory). I immediately killed the CHECKDB which had been running painfully for days, and set the database to read-only mode. Then I ran DBCC CHECKDB against it. It started going really fast (even a bit faster than before), and then throttled down again to around 10Mb/sec. All sorts of expletives went through my head at the time. Sure enough, the same latching scenario was present. Oh well. I even spent some time trying to figure out if NUMA was hurting performance. Folks on Twitter made suggestions in this regard (thanks, Lonny! [twitter]) …Eureka? This past Friday I was still scratching my head about the whole thing; I was ready to start profiling with XPERF to see if I could figure out which part of the engine was to blame and then get Microsoft to look at the evidence. After getting a bunch of good news I’ll blog about separately, I sat down for a figurative smack down with CHECKDB before the weekend. And then the light bulb went on. A sparse column. I thought that I couldn’t possibly be experiencing the same scenario that Paul blogged about back in March showing extreme latching with non-clustered indexes on computed columns. Did I even have a non-clustered index on my sparse column? As it turns out, I did. I had one filtered non-clustered index – with the sparse column as the index key (and only column). To prove that this was the problem, I went and setup a test. Yup, that'll do it The repro is very simple for this issue: I tested it on the latest public builds of SQL Server 2008 R2 SP2 (CU6) and SQL Server 2012 SP1 (CU4). First, create a test database and a test table, which only needs to contain a sparse column: CREATE DATABASE SparseColTest; GO USE SparseColTest; GO CREATE TABLE testTable (testCol smalldatetime SPARSE NULL); GO INSERT INTO testTable (testCol) VALUES (NULL); GO 1000000 That’s 1 million rows, and even though you’re inserting NULLs, that’s going to take a while. In my laptop, it took 3 minutes and 31 seconds. Next, we run DBCC CHECKDB against the database: DBCC CHECKDB('SparseColTest') WITH NO_INFOMSGS, ALL_ERRORMSGS; This runs extremely fast, as least on my test rig – 198 milliseconds. Now let’s create a filtered non-clustered index on the sparse column: CREATE NONCLUSTERED INDEX [badBadIndex] ON testTable (testCol) WHERE testCol IS NOT NULL; With the index in place now, let’s run DBCC CHECKDB one more time: DBCC CHECKDB('SparseColTest') WITH NO_INFOMSGS, ALL_ERRORMSGS; In my test system this statement completed in 11433 milliseconds. 11.43 full seconds. Quite the jump from 198 milliseconds. I went ahead and dropped the filtered non-clustered indexes on the restored copy of our production database, and ran CHECKDB against that. We went down from 7+ days to 19 hours and 20 minutes. Cue the “Argenis is not impressed” meme, please, Mr. LaRock. My pain is your gain, folks. Go check to see if you have any of such indexes – they’re likely causing your consistency checks to run very, very slow. Happy CHECKDBing, -Argenis ps: I plan to file a Connect item for this issue – I consider it a pretty serious bug in the engine. After all, filtered indexes were invented BECAUSE of the sparse column feature – and it makes a lot of sense to use them together. Watch this space and my twitter timeline for a link.

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• Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

  - by aspiringgeek

  Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario   Conventional Structures   Columnstore   Δ SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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