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  • C#: Parallel forms, multithreading and "applications in application"

    - by Harry
    First, what I need is - n WebBrowser-s, each in its own window doing its own job. The user should be able to see them all, or just one of them (or none), and to execute commands on each one. There is a main form, without a browser, this one contains control panel for my application. The key feautre is, each browser logs on to secured web page and it needs to stay logged in as long as possible. Well, I've done it, but I'm afraid something is wrong with my approach. The question is: Is code below valid, or rather a nasty hack which can cause problems: internal class SessionList : List<Session> { public SessionList(Server main) { MyRecords.ForEach(record => { var st = new System.Threading.Thread((data) => { var s = new Session(main, data as MyRecord); this.Add(s); Application.Run(s); Application.ExitThread(); }); st.SetApartmentState(System.Threading.ApartmentState.STA); st.Start(record); }); } // some other uninteresting methods here... } What's going on here? Session inherits from Form, so it creates a form, puts WebBrowser into it, and has methods to operate on websites. WebBrowser requires to be run in STA thread, so we provide one for each browser. The most interesting part of it is Application.Run(s). It makes the newly created forms alive and interactive. The next Application.ExitThread() is called after browser window is closed and its controls disposed. Main application stays alive to perform the rest of the cleanup job. When user select "Exit" or "Shutdown" option - first the browser threads are ended, so Application.ExitThread() is called. It all works, but everywhere I can read about "main GUI thread" - and here - I've created many GUI threads. I handle communication between main form and my new forms (sessions) with thread-safe methods using Invoke(). It all works, so is it right or is it wrong? Is everything right with using Application.Run() more than once in one application? :) An ugly hack or a normal practice? This code dies if I start a WebBrowser from the session form thread. It beats me why. It works however if I start WebBrowser (by changing its Url property) from any other thread. I'd like to know more what is really happening in such application. But most of all - I'd like to know if my idea of "applications in application" is OK. I'm not sure what exactly does Application.Run() do. Without it forms created in new threads were dead unresponsive. How is it possible I can call Application.Run() many times? It seems to do exactly what it should, but it seems a little undocumented feature to me. I'm almost sure, that the crashes are caused by WebBrowser component itself (since it's not completely "managed" and "native"). But maybe it's something else.

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  • "FOR UPDATE" v/s "LOCK IN SHARE MODE" : Allow concurrent threads to read updated "state" value of locked row

    - by shadesco
    I have the following scenario: User X logs in to the application from location lc1: call it Ulc1 User X (has been hacked, or some friend of his knows his login credential, or he just logs in from a different browser on his machine,etc.. u got the point) logs in at the same time from location lc2: call it Ulc2 I am using a main servlet which : - gets a connection from database pooling - sets autocommit to false - executes a command that goes through app layers: if all successful, set autocommit to true in a "finally" statement, and closes connection. Else if an exception happens, rollback(). In my database (mysql/innoDb) i have a "history" table, with row columns: id(primary key) |username | date | topic | locked The column "locked" has by default value "false" and it serves as a flag that marks if a specific row is locked or not. Each row is specific to a user (as u can see from the username column) So back to the scenario: --Ulc1 sends the command to update his history from the db for date "D" and topic "T". --Ulc2 sends the same command to update history from the db for the same date "D" and same topic "T" at the exact same time. I want to implement an mysql/innoDB locking system that will enable whichever thread arriving to do the following check: Is column "locked" for this row true or not? if true, return a message to the user that " he is already updating the same data from another location" if not true (ie not locked) : flag it as locked and update then reset locked to false once finished. Which of these two mysql locking techniques, will actually allow the 2nd arriving thread from reading the "updated" value of the locked column to decide wt action to take?Should i use "FOR UPDATE" or "LOCK IN SHARE MODE"? This scenario explains what i want to accomplish: - Ulc1 thread arrives first: column "locked" is false, set it to true and continue updating process - Ulc2 thread arrives while Ulc1's transaction is still in process, and even though the row is locked through innoDb functionalities, it doesn't have to wait but in fact reads the "new" value of column locked which is "true", and so doesn't in fact have to wait till Ulc1 transaction commits to read the value of the "locked" column(anyway by that time the value of this column will already have been reset to false). I am not very experienced with the 2 types of locking mechanisms, what i understand so far is that LOCK IN SHARE MODE allow other transaction to read the locked row while FOR UPDATE doesn't even allow reading. But does this read gets on the updated value? or the 2nd arriving thread has to wait the first thread to commit to then read the value? Any recommendations about which locking mechanism to use for this scenario is appreciated. Also if there's a better way to "check" if the row has been locked (other than using a true/false column flag) please let me know about it. thank you SOLUTION (Jdbc pseudocode example based on @Darhazer's answer) Table : [ id(primary key) |username | date | topic | locked ] connection.setautocommit(false); //transaction-1 PreparedStatement ps1 = "Select locked from tableName for update where id="key" and locked=false); ps1.executeQuery(); //transaction 2 PreparedStatement ps2 = "Update tableName set locked=true where id="key"; ps2.executeUpdate(); connection.setautocommit(true);// here we allow other transactions threads to see the new value connection.setautocommit(false); //transaction 3 PreparedStatement ps3 = "Update tableName set aField="Sthg" where id="key" And date="D" and topic="T"; ps3.executeUpdate(); // reset locked to false PreparedStatement ps4 = "Update tableName set locked=false where id="key"; ps4.executeUpdate(); //commit connection.setautocommit(true);

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  • Con Oracle l’Azienda Sanitaria della Provincia di Trento vince l'HR Innovation Award

    - by Lara Ermacora
    Il 14 giugno, si è tenuto il Convegno di presentazione dei risultati della Ricerca 2011 dell'Osservatorio HR Innovation Practice della School of Management del Politecnico di Milano. La Ricerca ha coinvolto 108 Direttori HR delle più importanti aziende operanti in Italia con l'obiettivo di comprendere l'evoluzione dei modelli organizzativi e promuovere l'innovazione dei processi di gestione e sviluppo delle Risorse Umane attraverso l'utilizzo di nuove tecnologie ICT. La presentazione dei risultati della Ricerca è stata seguita da una Tavola Rotonda a cui hanno partecipato i referenti di alcune delle principali aziende che offrono servizi e soluzioni in ambito HR e dalla consegna dei Premi “HR Innovation Award”, un’importante occasione di confronto su casi di eccellenza nell’innovazione dei processi HR . L’Azienda per i Servizi Sanitari di Trento (APSS) ha ricevuto il premio HR Innovation Award nella categoria “Valutazione delle prestazioni e gestione delle carriere”. Riconoscimento conseguito grazie al progetto di miglioramento della gestione del personale portato avanti facendo leva su Oracle PeopleSoft HCM (Human Capital Management) , la soluzione applicativa integrata di Oracle a supporto della direzione risorse umane. Il progetto nasce da una chiara esigenza dell'azienda sanitaria ad utilizzare un sistema applicativo che consentisse di migliorare i processi di gestione delle risorse umane fornendo una visione univoca delle informazioni relative a ciascun dipendente, contrariamente a quanto accadeva in passato. La scelta è caduta su Oracle Peoplesoft HCM per varie motivazioni. Prima di tutto perchè si tratta di una piattaforma unica e integrata che permette una gestione del personale snella. Questo avviene soprattutto perchè la piattaforma, ricostruendo la soria di ciascun dipendente, lo storico delle sue valutazioni e un quadro chiaro delle gerarchie aziendali, mette l’individuo al centro del sistema e consente di sviluppare assetti organizzativi e modalità operative in grado di garantire il collegamento tra tutte le fasi del processo di gestione delle risorse umane. Per maggiori informazioni sul progetto ecco una breve intervista di cui aveva già parlato ad Ettore Turra , responsabile del programma Sviluppo Risorse Umane APPS Trento:

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  • How do I align my partition table properly?

    - by Jorge Castro
    I am in the process of building my first RAID5 array. I've used mdadm to create the following set up: root@bondigas:~# mdadm --detail /dev/md1 /dev/md1: Version : 00.90 Creation Time : Wed Oct 20 20:00:41 2010 Raid Level : raid5 Array Size : 5860543488 (5589.05 GiB 6001.20 GB) Used Dev Size : 1953514496 (1863.02 GiB 2000.40 GB) Raid Devices : 4 Total Devices : 4 Preferred Minor : 1 Persistence : Superblock is persistent Update Time : Wed Oct 20 20:13:48 2010 State : clean, degraded, recovering Active Devices : 3 Working Devices : 4 Failed Devices : 0 Spare Devices : 1 Layout : left-symmetric Chunk Size : 64K Rebuild Status : 1% complete UUID : f6dc829e:aa29b476:edd1ef19:85032322 (local to host bondigas) Events : 0.12 Number Major Minor RaidDevice State 0 8 16 0 active sync /dev/sdb 1 8 32 1 active sync /dev/sdc 2 8 48 2 active sync /dev/sdd 4 8 64 3 spare rebuilding /dev/sde While that's going I decided to format the beast with the following command: root@bondigas:~# mkfs.ext4 /dev/md1p1 mke2fs 1.41.11 (14-Mar-2010) /dev/md1p1 alignment is offset by 63488 bytes. This may result in very poor performance, (re)-partitioning suggested. Filesystem label= OS type: Linux Block size=4096 (log=2) Fragment size=4096 (log=2) Stride=16 blocks, Stripe width=48 blocks 97853440 inodes, 391394047 blocks 19569702 blocks (5.00%) reserved for the super user First data block=0 Maximum filesystem blocks=0 11945 block groups 32768 blocks per group, 32768 fragments per group 8192 inodes per group Superblock backups stored on blocks: 32768, 98304, 163840, 229376, 294912, 819200, 884736, 1605632, 2654208, 4096000, 7962624, 11239424, 20480000, 23887872, 71663616, 78675968, 102400000, 214990848 Writing inode tables: ^C 27/11945 root@bondigas:~# ^C I am unsure what to do about "/dev/md1p1 alignment is offset by 63488 bytes." and how to properly partition the disks to match so I can format it properly.

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  • Ubuntu 10.04 - unable to install Arduino

    - by Newbie
    Hello! At the moment, I try to install Arduino on my Ubuntu 10.04 (32 Bit) computer. I downloaded the latest release at http://arduino.cc/en/Main/Software, cd'ed to the directory and unziped the package. When I try to run ./arduino , I get following error: Exception in thread "main" java.lang.ExceptionInInitializerError at processing.app.Base.main(Base.java:112) Caused by: java.awt.HeadlessException at sun.awt.HeadlessToolkit.getMenuShortcutKeyMask(HeadlessToolkit.java:231) at processing.core.PApplet.<clinit>(Unknown Source) ... 1 more Here is my java -version output: java version "1.6.0_20" OpenJDK Runtime Environment (IcedTea6 1.9.5) (6b20-1.9.5-0ubuntu1~10.04.1) OpenJDK Server VM (build 19.0-b09, mixed mode) Any suggestions on this? I try to install arduino without the 'arduino' package. I tried to install it with apt-get (sudo apt-get install arduino). When I try to start arduino (using arduino command) will cause following error: Exception in thread "main" java.lang.ExceptionInInitializerError at processing.app.Preferences.load(Preferences.java:553) at processing.app.Preferences.load(Preferences.java:549) at processing.app.Preferences.init(Preferences.java:142) at processing.app.Base.main(Base.java:188) Caused by: java.awt.HeadlessException at sun.awt.HeadlessToolkit.getMenuShortcutKeyMask(HeadlessToolkit.java:231) at processing.core.PApplet.<clinit>(PApplet.java:224) ... 4 more Update: I saw that I installed several versions of jre (sun and open). So I uninstalled the open jre. Now, when calling arduino I get a new error: java.lang.UnsatisfiedLinkError: no rxtxSerial in java.library.path thrown while loading gnu.io.RXTXCommDriver Exception in thread "main" java.lang.UnsatisfiedLinkError: no rxtxSerial in java.library.path at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1734) at java.lang.Runtime.loadLibrary0(Runtime.java:823) at java.lang.System.loadLibrary(System.java:1028) at gnu.io.CommPortIdentifier.<clinit>(CommPortIdentifier.java:123) at processing.app.Editor.populateSerialMenu(Editor.java:965) at processing.app.Editor.buildToolsMenu(Editor.java:717) at processing.app.Editor.buildMenuBar(Editor.java:502) at processing.app.Editor.<init>(Editor.java:194) at processing.app.Base.handleOpen(Base.java:698) at processing.app.Base.handleOpen(Base.java:663) at processing.app.Base.handleNew(Base.java:578) at processing.app.Base.<init>(Base.java:318) at processing.app.Base.main(Base.java:207)

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  • Glenn Fiedler's fixed timestep with fake threads

    - by kaoD
    I've implemented Glenn Fiedler's Fix Your Timestep! quite a few times in single-threaded games. Now I'm facing a different situation: I'm trying to do this in JavaScript. I know JS is single-threaded, but I plan on using requestAnimationFrame for the rendering part. This leaves me with two independent fake threads: simulation and rendering (I suppose requestAnimationFrame isn't really threaded, is it? I don't think so, it would BREAK JS.) Timing in these threads is independent too: dt for simulation and render is not the same. If I'm not mistaken, simulation should be up to Fiedler's while loop end. After the while loop, accumulator < dt so I'm left with some unspent time (dt) in the simulation thread. The problem comes in the draw/interpolation phase: const double alpha = accumulator / dt; State state = currentState*alpha + previousState * ( 1.0 - alpha ); render( state ); In my render callback, I have the current timestamp to which I can subtract the last-simulated-in-physics-timestamp to have a dt for the current frame. Should I just forget about this dt and draw using the physics thread's dt? It seems weird, since, well, I want to interpolate for the unspent time between simulation and render too, right? Of course, I want simulation and rendering to be completely independent, but I can't get around the fact that in Glenn's implementation the renderer produces time and the simulation consumes it in discrete dt sized chunks. A similar question was asked in Semi Fixed-timestep ported to javascript but the question doesn't really get to the point, and answers there point to removing physics from the render thread (which is what I'm trying to do) or just keeping physics in the render callback too (which is what I'm trying to avoid.)

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  • Compare Your Internet Cost and Speed to Global Averages [Infographic]

    - by ETC
    Internet pricing and speed varies wildly across the world. The US, for instance, currently ranks 15th in speed but enjoys reasonably priced internet access. How reasonably priced? If you’re a US citizen you likely have an average internet access speed of 4.8 mbps and you pay a little over $3 per mbps. If you’re in Sweden, however, you likely have an 18 mbps connection and you pay a scant 63 cents per mpbs. The real envy of the internet speed Olympics by far is Japan with a mighty 61 mbps at a mere 27 cents per mbps. Hit up the link below for the full infographic (or use this local mirror if you need to dodge a firewall), then sound off in the comments with how you compare on the international scale. Internet Speeds and Costs Around the World [via Daily Infographic] Latest Features How-To Geek ETC Should You Delete Windows 7 Service Pack Backup Files to Save Space? What Can Super Mario Teach Us About Graphics Technology? Windows 7 Service Pack 1 is Released: But Should You Install It? How To Make Hundreds of Complex Photo Edits in Seconds With Photoshop Actions How to Enable User-Specific Wireless Networks in Windows 7 How to Use Google Chrome as Your Default PDF Reader (the Easy Way) Manage Your Favorite Social Accounts in Chrome and Iron with Seesmic E.T. II – Extinction [Fake Movie Sequel Video] Remastered King’s Quest Games Offer Classic Gaming on Modern Machines Compare Your Internet Cost and Speed to Global Averages [Infographic] Orbital Battle for Terra Wallpaper WizMouse Enables Mouse Over Scrolling on Any Window

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  • How to improve batching performance

    - by user4241
    Hello, I am developing a sprite based 2D game for mobile platform(s) and I'm using OpenGL (well, actually Irrlicht) to render graphics. First I implemented sprite rendering in a simple way: every game object is rendered as a quad with its own GPU draw call, meaning that if I had 200 game objects, I made 200 draw calls per frame. Of course this was a bad choice and my game was completely CPU bound because there is a little CPU overhead assosiacted in every GPU draw call. GPU stayed idle most of the time. Now, I thought I could improve performance by collecting objects into large batches and rendering these batches with only a few draw calls. I implemented batching (so that every game object sharing the same texture is rendered in same batch) and thought that my problems are gone... only to find out that my frame rate was even lower than before. Why? Well, I have 200 (or more) game objects, and they are updated 60 times per second. Every frame I have to recalculate new position (translation and rotation) for vertices in CPU (GPU on mobile platforms does not support instancing so I can't do it there), and doing this calculation 48000 per second (200*60*4 since every sprite has 4 vertices) simply seems to be too slow. What I could do to improve performance? All game objects are moving/rotating (almost) every frame so I really have to recalculate vertex positions. Only optimization that I could think of is a look-up table for rotations so that I wouldn't have to calculate them. Would point sprites help? Any nasty hacks? Anything else? Thanks.

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  • How do I align my partition table properly?

    - by Jorge Castro
    I am in the process of building my first RAID5 array. I've used mdadm to create the following set up: root@bondigas:~# mdadm --detail /dev/md1 /dev/md1: Version : 00.90 Creation Time : Wed Oct 20 20:00:41 2010 Raid Level : raid5 Array Size : 5860543488 (5589.05 GiB 6001.20 GB) Used Dev Size : 1953514496 (1863.02 GiB 2000.40 GB) Raid Devices : 4 Total Devices : 4 Preferred Minor : 1 Persistence : Superblock is persistent Update Time : Wed Oct 20 20:13:48 2010 State : clean, degraded, recovering Active Devices : 3 Working Devices : 4 Failed Devices : 0 Spare Devices : 1 Layout : left-symmetric Chunk Size : 64K Rebuild Status : 1% complete UUID : f6dc829e:aa29b476:edd1ef19:85032322 (local to host bondigas) Events : 0.12 Number Major Minor RaidDevice State 0 8 16 0 active sync /dev/sdb 1 8 32 1 active sync /dev/sdc 2 8 48 2 active sync /dev/sdd 4 8 64 3 spare rebuilding /dev/sde While that's going I decided to format the beast with the following command: root@bondigas:~# mkfs.ext4 /dev/md1p1 mke2fs 1.41.11 (14-Mar-2010) /dev/md1p1 alignment is offset by 63488 bytes. This may result in very poor performance, (re)-partitioning suggested. Filesystem label= OS type: Linux Block size=4096 (log=2) Fragment size=4096 (log=2) Stride=16 blocks, Stripe width=48 blocks 97853440 inodes, 391394047 blocks 19569702 blocks (5.00%) reserved for the super user First data block=0 Maximum filesystem blocks=0 11945 block groups 32768 blocks per group, 32768 fragments per group 8192 inodes per group Superblock backups stored on blocks: 32768, 98304, 163840, 229376, 294912, 819200, 884736, 1605632, 2654208, 4096000, 7962624, 11239424, 20480000, 23887872, 71663616, 78675968, 102400000, 214990848 Writing inode tables: ^C 27/11945 root@bondigas:~# ^C I am unsure what to do about "/dev/md1p1 alignment is offset by 63488 bytes." and how to properly partition the disks to match so I can format it properly.

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  • Magento - How to manage multiple base currencies and multiple payment gateways?

    - by Diego
    I have two requirements to satisfy, I hope someone with more experience can help me sorting them out. Multiple Base Currencies My client wants to allow visitors to place orders in whatever currency they prefer, choosing from the ones he’ll configure. Magento only supports one Base Currency, and this is, obviously, not what I need. I checked the solution involving multiple websites, but I need a customer to be registered once and stay on the same website, not to switch from one to the other and have to register/log in on each. Manage multiple Payment Gateways per currency and per payment method This is another crucial requirement, and it’s tied to the first one. My client wants to “route” payments in different currencies to different accounts. He’ll thus have one for Euro, one for USD and one for GBP. Whenever a customer pays with one of these currencies, the payment gateway has to be chosen accordingly. Additionally, the gateway should be different depending on other rules. For example, if customer pays with a Debit Card, my client will have a payment gateway configured especially for it. If customer pays with MasterCard, the gateway will be different, and so on. The complication, in this case, arises from the fact that my client uses Realex Payments and, although it would be possible for him to open multiple accounts, the Realex module expects one single gateway. In a normal scenario, we would need up to six instead: Payment with Debit Card in Euro Payment with Credit Card in Euro Payment with Debit Card in US Dollars Payment with Credit Card in US Dollars Payment with Debit Card in GB Pounds Payment with Credit Card in GB Pounds This, of course, if he doesn’t decide to accept other payment methods, such as bank transfer, which would add one more gateway per currency. Is there a way to achieve the above in Magento? I never had such complicated requirements before, and I’m a bit lost. Thanks in advance for the help.

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  • New Enhancements for InnoDB Memcached

    - by Calvin Sun
    In MySQL 5.6, we continued our development on InnoDB Memcached and completed a few widely desirable features that make InnoDB Memcached a competitive feature in more scenario. Notablely, they are 1) Support multiple table mapping 2) Added background thread to auto-commit long running transactions 3) Enhancement in binlog performance  Let’s go over each of these features one by one. And in the last section, we will go over a couple of internally performed performance tests. Support multiple table mapping In our earlier release, all InnoDB Memcached operations are mapped to a single InnoDB table. In the real life, user might want to use this InnoDB Memcached features on different tables. Thus being able to support access to different table at run time, and having different mapping for different connections becomes a very desirable feature. And in this GA release, we allow user just be able to do both. We will discuss the key concepts and key steps in using this feature. 1) "mapping name" in the "get" and "set" command In order to allow InnoDB Memcached map to a new table, the user (DBA) would still require to "pre-register" table(s) in InnoDB Memcached “containers” table (there is security consideration for this requirement). If you would like to know about “containers” table, please refer to my earlier blogs in blogs.innodb.com. Once registered, the InnoDB Memcached will then be able to look for such table when they are referred. Each of such registered table will have a unique "registration name" (or mapping_name) corresponding to the “name” field in the “containers” table.. To access these tables, user will include such "registration name" in their get or set commands, in the form of "get @@new_mapping_name.key", prefix "@@" is required for signaling a mapped table change. The key and the "mapping name" are separated by a configurable delimiter, by default, it is ".". So the syntax is: get [@@mapping_name.]key_name set [@@mapping_name.]key_name  or  get @@mapping_name set @@mapping_name Here is an example: Let's set up three tables in the "containers" table: The first is a map to InnoDB table "test/demo_test" table with mapping name "setup_1" INSERT INTO containers VALUES ("setup_1", "test", "demo_test", "c1", "c2", "c3", "c4", "c5", "PRIMARY");  Similarly, we set up table mappings for table "test/new_demo" with name "setup_2" and that to table "mydatabase/my_demo" with name "setup_3": INSERT INTO containers VALUES ("setup_2", "test", "new_demo", "c1", "c2", "c3", "c4", "c5", "secondary_index_x"); INSERT INTO containers VALUES ("setup_3", "my_database", "my_demo", "c1", "c2", "c3", "c4", "c5", "idx"); To switch to table "my_database/my_demo", and get the value corresponding to “key_a”, user will do: get @@setup_3.key_a (this will also output the value that corresponding to key "key_a" or simply get @@setup_3 Once this is done, this connection will switch to "my_database/my_demo" table until another table mapping switch is requested. so it can continue issue regular command like: get key_b  set key_c 0 0 7 These DMLs will all be directed to "my_database/my_demo" table. And this also implies that different connections can have different bindings (to different table). 2) Delimiter: For the delimiter "." that separates the "mapping name" and key value, we also added a configure option in the "config_options" system table with name of "table_map_delimiter": INSERT INTO config_options VALUES("table_map_delimiter", "."); So if user wants to change to a different delimiter, they can change it in the config_option table. 3) Default mapping: Once we have multiple table mapping, there should be always a "default" map setting. For this, we decided if there exists a mapping name of "default", then this will be chosen as default mapping. Otherwise, the first row of the containers table will chosen as default setting. Please note, user tables can be repeated in the "containers" table (for example, user wants to access different columns of the table in different settings), as long as they are using different mapping/configure names in the first column, which is enforced by a unique index. 4) bind command In addition, we also extend the protocol and added a bind command, its usage is fairly straightforward. To switch to "setup_3" mapping above, you simply issue: bind setup_3 This will switch this connection's InnoDB table to "my_database/my_demo" In summary, with this feature, you now can direct access to difference tables with difference session. And even a single connection, you can query into difference tables. Background thread to auto-commit long running transactions This is a feature related to the “batch” concept we discussed in earlier blogs. This “batch” feature allows us batch the read and write operations, and commit them only after certain calls. The “batch” size is controlled by the configure parameter “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size”. This could significantly boost performance. However, it also comes with some disadvantages, for example, you will not be able to view “uncommitted” operations from SQL end unless you set transaction isolation level to read_uncommitted, and in addition, this will held certain row locks for extend period of time that might reduce the concurrency. To deal with this, we introduce a background thread that “auto-commits” the transaction if they are idle for certain amount of time (default is 5 seconds). The background thread will wake up every second and loop through every “connections” opened by Memcached, and check for idle transactions. And if such transaction is idle longer than certain limit and not being used, it will commit such transactions. This limit is configurable by change “innodb_api_bk_commit_interval”. Its default value is 5 seconds, and minimum is 1 second, and maximum is 1073741824 seconds. With the help of such background thread, you will not need to worry about long running uncommitted transactions when set daemon_memcached_w_batch_size and daemon_memcached_r_batch_size to a large number. This also reduces the number of locks that could be held due to long running transactions, and thus further increase the concurrency. Enhancement in binlog performance As you might all know, binlog operation is not done by InnoDB storage engine, rather it is handled in the MySQL layer. In order to support binlog operation through InnoDB Memcached, we would have to artificially create some MySQL constructs in order to access binlog handler APIs. In previous lab release, for simplicity consideration, we open and destroy these MySQL constructs (such as THD) for each operations. This required us to set the “batch” size always to 1 when binlog is on, no matter what “daemon_memcached_w_batch_size” and “daemon_memcached_r_batch_size” are configured to. This put a big restriction on our capability to scale, and also there are quite a bit overhead in creating destroying such constructs that bogs the performance down. With this release, we made necessary change that would keep MySQL constructs as long as they are valid for a particular connection. So there will not be repeated and redundant open and close (table) calls. And now even with binlog option is enabled (with innodb_api_enable_binlog,), we still can batch the transactions with daemon_memcached_w_batch_size and daemon_memcached_r_batch_size, thus scale the write/read performance. Although there are still overheads that makes InnoDB Memcached cannot perform as fast as when binlog is turned off. It is much better off comparing to previous release. And we are continuing optimize the solution is this area to improve the performance as much as possible. Performance Study: Amerandra of our System QA team have conducted some performance studies on queries through our InnoDB Memcached connection and plain SQL end. And it shows some interesting results. The test is conducted on a “Linux 2.6.32-300.7.1.el6uek.x86_64 ix86 (64)” machine with 16 GB Memory, Intel Xeon 2.0 GHz CPU X86_64 2 CPUs- 4 Core Each, 2 RAID DISKS (1027 GB,733.9GB). Results are described in following tables: Table 1: Performance comparison on Set operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8*** 5.6.7-RC* X faster Set (QPS) Set** 8 30,000 5,600 5.36 32 59,000 13,000 4.54 128 68,000 8,000 8.50 512 63,000 6.800 9.23 * mysql-5.6.7-rc-linux2.6-x86_64 ** The “set” operation when implemented in InnoDB Memcached involves a couple of DMLs: it first query the table to see whether the “key” exists, if it does not, the new key/value pair will be inserted. If it does exist, the “value” field of matching row (by key) will be updated. So when used in above query, it is a precompiled store procedure, and query will just execute such procedures. *** added “–daemon_memcached_option=-t8” (default is 4 threads) So we can see with this “set” query, InnoDB Memcached can run 4.5 to 9 time faster than MySQL server. Table 2: Performance comparison on Get operations Connections 5.6.7-RC-Memcached-plugin ( TPS / Qps) with memcached-threads=8 5.6.7-RC* X faster Get (QPS) Get 8 42,000 27,000 1.56 32 101,000 55.000 1.83 128 117,000 52,000 2.25 512 109,000 52,000 2.10 With the “get” query (or the select query), memcached performs 1.5 to 2 times faster than normal SQL. Summary: In summary, we added several much-desired features to InnoDB Memcached in this release, allowing user to operate on different tables with this Memcached interface. We also now provide a background commit thread to commit long running idle transactions, thus allow user to configure large batch write/read without worrying about large number of rows held or not being able to see (uncommit) data. We also greatly enhanced the performance when Binlog is enabled. We will continue making efforts in both performance enhancement and functionality areas to make InnoDB Memcached a good demo case for our InnoDB APIs. Jimmy Yang, September 29, 2012

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  • Change power button to 'Ask' in Xubuntu 13.10

    - by Gully.Moy
    I have recently installed Xubuntu 13.10 on my Vaio vpcea making me a Linux beginner. The problem is that laptop's power button is right on the edge of the bezel making it far too easy to press accidentally, in my opinion a design fault by Sony. At present, when I press the power button it shuts down strait away and as you can imagine, when I'm accidentally pressing it all the time it gets very annoying! So I planned to change it to ask what I would like to do when I press it or at least ask if I'm sure. So I went through the xfce GUI options "Settings Manager" - "Power Manager" to the field "When power button is pressed", but it was already set to "Ask". So I did some digging and found a thread telling me to navigate to /etc/xdg/xfce4/xfconf/xfce-perchannel-xml/xfce4-power-manager.xml where it said to find power-button-action and check that value="3". It already did. So I looked some more and found this thread which focuses on acpi scripts. I tried solution 1 & 2 using sudoedit to change the files accordingly (I have made executable bash shell scripts already so I think I followed them correctly), but still no difference. I also found this thread which instructed me to edit /etc/systemd/logind.conf so that HandlePowerKey=ignore. Still no luck. I even tried my own approach to completely disable /etc/acpi/powerbtn.sh by renaming it powerbtn.sh.bak hoping for at least no response from the power button... and I have done many reboots in between... but still it shuts down! I have also read that some people have the file /etc/acpi/events/power_button, but I do not. So does anyone have any other ideas? What else could be executing the shutdown sequence Is there something I'm missing? I haven't undone any of these actions so every one of the above files is currently edited on my computer, with the exception that "Solution 2" automatically undone "Solution 1" above. Thanks guys.

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  • Bash Script help required

    - by Sunil J
    I am trying to get this bash script that i found on a forum to work. Copied it to text editor. Saved it as script.sh chmod 700 and tried to run it. rootdir="/usr/share/malware" day=`date +%Y%m%d` url=`echo "wget -qO - http://lists.clean-mx.com/pipermail/viruswatch/$day/thread.html |\ awk '/\[Virus/'|tail -n 1|sed 's:\": :g' |\ awk '{print \"http://lists.clean-mx.com/pipermail/viruswatch/$day/\"$3}'"|sh` filename=`wget -qO - http://lists.clean-mx.com/pipermail/viruswatch/$day/thread.html |\ awk '/\[Virus/'|tail -n 1|sed 's:": :g' |awk '{print $3}'` links -dump $url$filename | awk '/Up/'|grep "TR\|exe" | awk '{print $2,$8,$10,$11,$12"\n"}' > $rootdir/>$filename dirname=`wget -qO - http://lists.clean-mx.com/pipermail/viruswatch/$day/thread.html |\ awk '/\[Virus/'|tail -n 1|sed 's:": :g' |awk '{print $3}'|sed 's:.html::g'` rm -rf $rootdir/$dirname mkdir $rootdir/$dirname cd $rootdir grep "exe$" $filename |awk '{print "wget \""$5"\""}' | sh ls *.exe | xargs md5 >> checksums mv *.exe $dirname rm -r $rootdir/*exe* mv checksums $rootdir/$dirname mv $filename $rootdir/$dirname I get the following message.. script.sh: line 11: /usr/share/malware/: Is a directory script.sh: line 11: links: command not found

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  • Tuning B2B Server Engine Threads in SOA Suite 11g

    - by Shub Lahiri, A-Team
    Background B2B 11g has a number of parameters that can be tweaked to tune the engine for handling high volumes of messages. These parameters are also known as B2B server properties and managed via the EM console.  This note highlights one aspect of the tuning exercise and describes the different threads, that can be configured to tune the performance of a B2B server. Symptoms The most common indicator of a B2B engine in need of a tuning is reflected in the constant build-up of messages in an internal JMS queue within the B2B server. It is called B2B_EVENT_QUEUE and can be monitored via the Weblogic server console. Whenever such a behaviour is seen, it usually results in general degradation of performance. Remedy There could be many contributing factors behind a B2B server's degradation of performance. However, one of the first places to tune the server from the out-of-the-box, default configuration is to change the number of internal engine threads allocated within the B2B server. Usually the default configuration for the B2B server engine threads is not suitable for high-volume of messaging loads. So, it is necessary to increase the counts for 3 types of such threads, by specifying the appropriate B2B server properties via the EM console, namely, Inbound - b2b.inboundThreadCount Outbound - b2b.outboundThreadCount Default - b2b.defaultThreadCount The function of these threads are fairly self-explanatory. In other words, the inbound threads process the inbound messages that are coming into the B2B server from an external endpoint. Similarly, the outbound threads processes the messages that are sent out from the B2B server. The default threads are responsible for certain B2B server-specific special tasks. In case the inbound and outbound thread counts are not specified, the default thread count also dictates the total number of inbound and outbound threads. As found in any tuning exercise, the optimisation of these threads is usually reached via an iterative process. The best working combination of the thread counts are directly related to the system infrastructure, traffic load and several other environmental factors.

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  • Does concurrency inherently introduce "randomness" into a game?

    - by Jeff
    When a game is implemented with concurrency (as most games are), does this necessarily, by its very nature, introduce an element of randomness into the game that is outside of the players' control? Note that when I use the word "random", I'm not meaning to launch into a philosophical debate about the deterministic nature of the system. I understand that concurrency is deterministic in the sense that the operating system decides which processes to allow time on the CPU and in what order (or the JVM controls which Thread's turn it is to execute, etc). But my understanding of this is that there is no way to control or predict whether one thread's next command will execute before or after another. The reason I'm asking is because this seems like a fundamental difficulty for game development where a game is supposedly designed around a player's skill. Consider a game like League of Legends. Assume that two players are battling it out. It's a very close contest between the two and it's coming down to the wire -- so much so that whoever gets their last attack off will be the one to kill the other and win the game for their team. If the players are implemented using concurrency and the situation really was like this, is it essentially out of the players' hands at this point? Is the outcome of this match all up to whatever system is arbitrarily deciding which player's thread/process will execute next? If not, what am I misunderstanding about concurrency? If so, is there any way around this problem so that a game of skill can always be a game of skill, especially in those most crucial moments?

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  • Pattern for Accessing MySQL connection

    - by Dipan Mehta
    We have an application which is C++ trying to access MySQL database. There are several (about 5 or so) threads in the application (with Boost library for threading) and in each thread has a few objects, each of which is trying to access Database for its' own purpose. It has a simple ORM kind of model but that really is not an important factor here. There are three potential access patterns i can think of: There could be single connection object per application or thread and is shared between all (or group). The object needs to be thread safe and there will be contentions but MySQL will not be fired with too many connections. Every object could initiate connection on its own. The database needs to take care of concurrency (which i think MySQL can) and the design could be much simpler. There could be two possibilities here. a. either object keeps a persistent connection for its life OR b. object initiate connection as and when needed. To simplify the contention as in case of 1 and not to create too many sockets as in case of 2, we can have group/set based connections. So there could be there could be more than one connection (say N), each of this connection could be shared connection across M objects. Naturally, each of the pattern has different resource cost and would work under different constraints and objectives. What criteria should i use to choose the pattern of this for my own application? What are some of the advantages and disadvantages of each of these pattern over the other? Are there any other pattern which is better? PS: I have been through these questions: mysql, one connection vs multiple and MySQL with mutiple threads and processes But they don't quite answer exactly what i am trying to ask.

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  • MightyMintyBoost Is a 3-in-1 Gadget Charger

    - by ETC
    If you’re looking for a versatile battery booster, this DIY 3-in-1 solar/usb/wall current charger known as the MightyMintyBoost will top of your phone, mp3 player, and other gadgets with ease. Instructables user Honus didn’t just build the MightMintyBoost to geek out and show off his electronics project skills (although it’s certainly a nifty little project to do so), he’s serious about solar power and the impact clean energy has: Apple has sold over 30 million iPodTouch/iPhone units- imagine charging all of them via solar power…. If every iPhone/iPodTouch sold was fully charged every day (averaging the battery capacity) via solar power instead of fossil fuel power we would save approximately 50.644gWh of energy, roughly equivalent to 75,965,625 lbs. of CO2 in the atmosphere per year. Granted that’s a best case scenario (assuming you can get enough sunlight per day and approximately 1.5 lbs. CO2 produced per kWh used.) Of course, that doesn’t even figure in all the other iPods, cell phones, PDAs, microcontrollers (I use it to power my Arduino projects) and other USB devices that can be powered by this charger- one little solar cell charger may not seem like it can make a difference but add all those millions of devices together and that’s a lot of energy! His MightyMintyBoost is a battery booster for devices that can charge via USB and it accepts incoming current from the solar panel on top (or, on cloudy days can be charged via a wall charger or the USB port on your computer). Hit up the link below to see his full build guide and create your own MightyMintyBoost. MightyMintyBoost [Instructables] Latest Features How-To Geek ETC Internet Explorer 9 RC Now Available: Here’s the Most Interesting New Stuff Here’s a Super Simple Trick to Defeating Fake Anti-Virus Malware How to Change the Default Application for Android Tasks Stop Believing TV’s Lies: The Real Truth About "Enhancing" Images The How-To Geek Valentine’s Day Gift Guide Inspire Geek Love with These Hilarious Geek Valentines MyPaint is an Open-Source Graphics App for Digital Painters Can the Birds and Pigs Really Be Friends in the End? [Angry Birds Video] Add the 2D Version of the New Unity Interface to Ubuntu 10.10 and 11.04 MightyMintyBoost Is a 3-in-1 Gadget Charger Watson Ties Against Human Jeopardy Opponents Peaceful Tropical Cavern Wallpaper

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  • Big Data Appliance X4-2 Release Announcement

    - by Jean-Pierre Dijcks
    Today we are announcing the release of the 3rd generation Big Data Appliance. Read the Press Release here. Software Focus The focus for this 3rd generation of Big Data Appliance is: Comprehensive and Open - Big Data Appliance now includes all Cloudera Software, including Back-up and Disaster Recovery (BDR), Search, Impala, Navigator as well as the previously included components (like CDH, HBase and Cloudera Manager) and Oracle NoSQL Database (CE or EE). Lower TCO then DIY Hadoop Systems Simplified Operations while providing an open platform for the organization Comprehensive security including the new Audit Vault and Database Firewall software, Apache Sentry and Kerberos configured out-of-the-box Hardware Update A good place to start is to quickly review the hardware differences (no price changes!). On a per node basis the following is a comparison between old and new (X3-2) hardware: Big Data Appliance X3-2 Big Data Appliance X4-2 CPU 2 x 8-Core Intel® Xeon® E5-2660 (2.2 GHz) 2 x 8-Core Intel® Xeon® E5-2650 V2 (2.6 GHz) Memory 64GB 64GB Disk 12 x 3TB High Capacity SAS 12 x 4TB High Capacity SAS InfiniBand 40Gb/sec 40Gb/sec Ethernet 10Gb/sec 10Gb/sec For all the details on the environmentals and other useful information, review the data sheet for Big Data Appliance X4-2. The larger disks give BDA X4-2 33% more capacity over the previous generation while adding faster CPUs. Memory for BDA is expandable to 512 GB per node and can be done on a per-node basis, for example for NameNodes or for HBase region servers, or for NoSQL Database nodes. Software Details More details in terms of software and the current versions (note BDA follows a three monthly update cycle for Cloudera and other software): Big Data Appliance 2.2 Software Stack Big Data Appliance 2.3 Software Stack Linux Oracle Linux 5.8 with UEK 1 Oracle Linux 6.4 with UEK 2 JDK JDK 6 JDK 7 Cloudera CDH CDH 4.3 CDH 4.4 Cloudera Manager CM 4.6 CM 4.7 And like we said at the beginning it is important to understand that all other Cloudera components are now included in the price of Oracle Big Data Appliance. They are fully supported by Oracle and available for all BDA customers. For more information: Big Data Appliance Data Sheet Big Data Connectors Data Sheet Oracle NoSQL Database Data Sheet (CE | EE) Oracle Advanced Analytics Data Sheet

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  • Se non ti sei unito alla Customer Experience Revolution? Il materiale è tutto qui!

    - by Silvia Valgoi
    Se ti sei perso questo interesante Executive workshop, non preoccuparti, qui puoi trovare gli interventi dei relatori.Durante l'evento Oracle, Accenture ed il professor Enrico Finzi hanno condiviso l'approccio alla Customer Experience vista come strategia per dare vita a processi più completi ed innovativi, per generare e gestire l’interazione con i consumatori, su tutti i canali. E' stato un momento importante per: comprendere perché la Customer Experience è diventata la componente più importante e strategica del tuo business scoprire come la Customer Experience accelleri l’acquisizione di nuovi clienti, incrementi la fidelizzazione ad un brand/prodotto/servizio, migliori l’efficienza operativa e sostenga le vendite conoscere come le soluzioni di Customer Experience possono aiutare le aziende a far vivere questa esperienza in modo coerente, personalizzata, attraverso tutti i canali e su tutti i dispositivi, ottenendo risultati misurabile Ecco le presentazioni e i video presentati durante i lavori: &amp;lt;p&amp;gt; &amp;lt;/p&amp;gt; Oracle Customer Experience - Empowering People. Powering Brands - Armando Janigro, Sales Development Manager, Oracle         How to win with Customer Experience - Nadia Dallafiore, Senior Manager CRM Retail  Accenture   Customer Experience e selezione Darwiniana della marca - Enrico Finzi, Sociologo, Presidente AstraRicerche   Engage.Win.Develop.Keep LinkedIn: Customer Concepts Exchange Facebook: Oracle Customer Experience

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  • Parallel Classloading Revisited: Fully Concurrent Loading

    - by davidholmes
    Java 7 introduced support for parallel classloading. A description of that project and its goals can be found here: http://openjdk.java.net/groups/core-libs/ClassLoaderProposal.html The solution for parallel classloading was to add to each class loader a ConcurrentHashMap, referenced through a new field, parallelLockMap. This contains a mapping from class names to Objects to use as a classloading lock for that class name. This was then used in the following way: protected Class loadClass(String name, boolean resolve) throws ClassNotFoundException { synchronized (getClassLoadingLock(name)) { // First, check if the class has already been loaded Class c = findLoadedClass(name); if (c == null) { long t0 = System.nanoTime(); try { if (parent != null) { c = parent.loadClass(name, false); } else { c = findBootstrapClassOrNull(name); } } catch (ClassNotFoundException e) { // ClassNotFoundException thrown if class not found // from the non-null parent class loader } if (c == null) { // If still not found, then invoke findClass in order // to find the class. long t1 = System.nanoTime(); c = findClass(name); // this is the defining class loader; record the stats sun.misc.PerfCounter.getParentDelegationTime().addTime(t1 - t0); sun.misc.PerfCounter.getFindClassTime().addElapsedTimeFrom(t1); sun.misc.PerfCounter.getFindClasses().increment(); } } if (resolve) { resolveClass(c); } return c; } } Where getClassLoadingLock simply does: protected Object getClassLoadingLock(String className) { Object lock = this; if (parallelLockMap != null) { Object newLock = new Object(); lock = parallelLockMap.putIfAbsent(className, newLock); if (lock == null) { lock = newLock; } } return lock; } This approach is very inefficient in terms of the space used per map and the number of maps. First, there is a map per-classloader. As per the code above under normal delegation the current classloader creates and acquires a lock for the given class, checks if it is already loaded, then asks its parent to load it; the parent in turn creates another lock in its own map, checks if the class is already loaded and then delegates to its parent and so on till the boot loader is invoked for which there is no map and no lock. So even in the simplest of applications, you will have two maps (in the system and extensions loaders) for every class that has to be loaded transitively from the application's main class. If you knew before hand which loader would actually load the class the locking would only need to be performed in that loader. As it stands the locking is completely unnecessary for all classes loaded by the boot loader. Secondly, once loading has completed and findClass will return the class, the lock and the map entry is completely unnecessary. But as it stands, the lock objects and their associated entries are never removed from the map. It is worth understanding exactly what the locking is intended to achieve, as this will help us understand potential remedies to the above inefficiencies. Given this is the support for parallel classloading, the class loader itself is unlikely to need to guard against concurrent load attempts - and if that were not the case it is likely that the classloader would need a different means to protect itself rather than a lock per class. Ultimately when a class file is located and the class has to be loaded, defineClass is called which calls into the VM - the VM does not require any locking at the Java level and uses its own mutexes for guarding its internal data structures (such as the system dictionary). The classloader locking is primarily needed to address the following situation: if two threads attempt to load the same class, one will initiate the request through the appropriate loader and eventually cause defineClass to be invoked. Meanwhile the second attempt will block trying to acquire the lock. Once the class is loaded the first thread will release the lock, allowing the second to acquire it. The second thread then sees that the class has now been loaded and will return that class. Neither thread can tell which did the loading and they both continue successfully. Consider if no lock was acquired in the classloader. Both threads will eventually locate the file for the class, read in the bytecodes and call defineClass to actually load the class. In this case the first to call defineClass will succeed, while the second will encounter an exception due to an attempted redefinition of an existing class. It is solely for this error condition that the lock has to be used. (Note that parallel capable classloaders should not need to be doing old deadlock-avoidance tricks like doing a wait() on the lock object\!). There are a number of obvious things we can try to solve this problem and they basically take three forms: Remove the need for locking. This might be achieved by having a new version of defineClass which acts like defineClassIfNotPresent - simply returning an existing Class rather than triggering an exception. Increase the coarseness of locking to reduce the number of lock objects and/or maps. For example, using a single shared lockMap instead of a per-loader lockMap. Reduce the lifetime of lock objects so that entries are removed from the map when no longer needed (eg remove after loading, use weak references to the lock objects and cleanup the map periodically). There are pros and cons to each of these approaches. Unfortunately a significant "con" is that the API introduced in Java 7 to support parallel classloading has essentially mandated that these locks do in fact exist, and they are accessible to the application code (indirectly through the classloader if it exposes them - which a custom loader might do - and regardless they are accessible to custom classloaders). So while we can reason that we could do parallel classloading with no locking, we can not implement this without breaking the specification for parallel classloading that was put in place for Java 7. Similarly we might reason that we can remove a mapping (and the lock object) because the class is already loaded, but this would again violate the specification because it can be reasoned that the following assertion should hold true: Object lock1 = loader.getClassLoadingLock(name); loader.loadClass(name); Object lock2 = loader.getClassLoadingLock(name); assert lock1 == lock2; Without modifying the specification, or at least doing some creative wordsmithing on it, options 1 and 3 are precluded. Even then there are caveats, for example if findLoadedClass is not atomic with respect to defineClass, then you can have concurrent calls to findLoadedClass from different threads and that could be expensive (this is also an argument against moving findLoadedClass outside the locked region - it may speed up the common case where the class is already loaded, but the cost of re-executing after acquiring the lock could be prohibitive. Even option 2 might need some wordsmithing on the specification because the specification for getClassLoadingLock states "returns a dedicated object associated with the specified class name". The question is, what does "dedicated" mean here? Does it mean unique in the sense that the returned object is only associated with the given class in the current loader? Or can the object actually guard loading of multiple classes, possibly across different class loaders? So it seems that changing the specification will be inevitable if we wish to do something here. In which case lets go for something that more cleanly defines what we want to be doing: fully concurrent class-loading. Note: defineClassIfNotPresent is already implemented in the VM as find_or_define_class. It is only used if the AllowParallelDefineClass flag is set. This gives us an easy hook into existing VM mechanics. Proposal: Fully Concurrent ClassLoaders The proposal is that we expand on the notion of a parallel capable class loader and define a "fully concurrent parallel capable class loader" or fully concurrent loader, for short. A fully concurrent loader uses no synchronization in loadClass and the VM uses the "parallel define class" mechanism. For a fully concurrent loader getClassLoadingLock() can return null (or perhaps not - it doesn't matter as we won't use the result anyway). At present we have not made any changes to this method. All the parallel capable JDK classloaders become fully concurrent loaders. This doesn't require any code re-design as none of the mechanisms implemented rely on the per-name locking provided by the parallelLockMap. This seems to give us a path to remove all locking at the Java level during classloading, while retaining full compatibility with Java 7 parallel capable loaders. Fully concurrent loaders will still encounter the performance penalty associated with concurrent attempts to find and prepare a class's bytecode for definition by the VM. What this penalty is depends on the number of concurrent load attempts possible (a function of the number of threads and the application logic, and dependent on the number of processors), and the costs associated with finding and preparing the bytecodes. This obviously has to be measured across a range of applications. Preliminary webrevs: http://cr.openjdk.java.net/~dholmes/concurrent-loaders/webrev.hotspot/ http://cr.openjdk.java.net/~dholmes/concurrent-loaders/webrev.jdk/ Please direct all comments to the mailing list [email protected].

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  • Data Pump: Consistent Export?

    - by Mike Dietrich
    Ouch ... I have to admit as I did say in several workshops in the past weeks that a data pump export with expdp is per se consistent. Well ... I thought it is ... but it's not. Thanks to a customer who is doing a large unicode migration at the moment. We were discussing parameters in the expdp's par file. And I did ask my colleagues after doing some research on MOS. And here are the results of my "research": MOS Note 377218.1 has a nice example showing a data pump export of a partitioned table with DELETEs on that table as inconsistent Background:Back in the old 9i days when Data Pump was designed flashback technology wasn't as popular and well known as today - and UNDO usage was the major concern as a consistent per default export would have heavily relied on UNDO. That's why - similar to good ol' exp - the export won't operate per default in consistency mode To get a consistent data pump export with expdp you'll have to set: FLASHBACK_TIME=SYSTIMESTAMPin your parameter file. Then it will be consistent according to the timestamp when the process has been started. You could use FLASHBACK_SCN instead and determine the SCN beforehand if you'd like to be exact. So sorry if I had proclaimed a feature which unfortunately is not there by default - Mike

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  • NHibernate Tools: Visual NHibernate

    - by Ricardo Peres
    You probably know that I’m a big fan of Slyce Software’s Visual NHibernate. To me, it is the best tool for generating your entities and mappings from an existing database (it also allows you to go the other way, but I honestly have never used it that way). What I like most about it: Great support: folks at Slyce always listen to your suggestions, give you feedback in a timely manner, and I was even lucky enough to have some of my suggestions implemented! The templating engine, which is very powerful, and more user-friendly than, for example, MyGeneration’s; one of the included templates is Sharp Architecture; Advanced model validations: it even warns you about having lazy properties declared in non-lazy entities; Integration with NHibernate Validator and generation of validation rules automatically based on the database, or on user-defined model settings; The designer: they opted for not displaying all entities in a single screen, which I think was a good decision; has support for all inheritance strategies (table per class hierarchy, table per class, table per concrete class); Generation of FluentNHibernate mappings as well as hbm.xml. I could name others, but… why don’t you see for yourself? There is a demo version available for downloading. By the way, I am in no way related to Slyce, I just happen to like their software!

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  • Introducing Oracle Multitenant

    - by OracleMultitenant
    0 0 1 1142 6510 Oracle Corporation 54 15 7637 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:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-fareast-language:JA;} The First Database Designed for the Cloud Today Oracle announced the general availability (GA) of Oracle Database 12c, the first database designed for the Cloud. Oracle Multitenant, new with Oracle Database 12c, is a key component of this – a new architecture for consolidating databases and simplifying operations in the Cloud. With this, the inaugural post in the Multitenant blog, my goal is to start the conversation about Oracle Multitenant. We are very proud of this new architecture, which we view as a major advance for Oracle. Customers, partners and analysts who have had previews are very excited about its capabilities and its flexibility. This high level review of Oracle Multitenant will touch on our design considerations and how we re-architected our database for the cloud. I’ll briefly describe our new multitenant architecture and explain it’s key benefits. Finally I’ll mention some of the major use cases we see for Oracle Multitenant. Industry Trends We always start by talking to our customers about the pressures and challenges they’re facing and what trends they’re seeing in the industry. Some things don’t change. They face the same pressures and the same requirements as ever: Pressure to do more with less; be faster, leaner, cheaper, and deliver services 24/7. Big companies have achieved scale. Now they want to realize economies of scale. As ever, DBAs are faced with the challenges of patching and upgrading large numbers of databases, and provisioning new ones.  Requirements are familiar: Performance, scalability, reliability and high availability are non-negotiable. They need ever more security in this threatening climate. There’s no time to stop and retool with new applications. What’s new are the trends. These are the techniques to use to respond to these pressures within the constraints of the requirements. With the advent of cloud computing and availability of massively powerful servers – even engineered systems such as Exadata – our customers want to consolidate many applications into fewer larger servers. There’s a move to standardized services – even self-service. Consolidation Consolidation is not new; companies have tried various different approaches to consolidation of databases in the cloud. One approach is to partition a powerful server between several virtual machines, one per application. A downside of this is that you have the resource and management overheads of OS and RDBMS per VM – that is, per application. Another is that you have replaced physical sprawl with virtual sprawl and virtual sprawl is still expensive to manage. In the dedicated database model, we have a single physical server supporting multiple databases, one per application. So there’s a shared OS overhead, but RDBMS process and memory overhead are replicated per application. Let's think about our traditional Oracle Database architecture. Every time we create a database, be it a production database, a development or a test database, what do we do? We create a set of files, we allocate a bunch of memory for managing the data, and we kick off a series of background processes. This is replicated for every one of the databases that we create. As more and more databases are fired up, these replicated overheads quickly consume the available server resources and this limits the number of applications we can run on any given server. In Oracle Database 11g and earlier the highest degree of consolidation could be achieved by what we call schema consolidation. In this model we have one big server with one big database. Individual applications are installed in separate schemas or table-owners. Database overheads are shared between all applications, which affords maximum consolidation. The shortcomings are that application changes are often required. There is no tenant isolation. One bad apple can spoil the whole batch. New Architecture & Benefits In Oracle Database 12c, we have a new multitenant architecture, featuring pluggable databases. This delivers all the resource utilization advantages of schema consolidation with none of the downsides. There are two parts to the term “pluggable database”: "pluggable", which is new, and "database", which is familiar.  Before we get to the exciting new stuff let’s discuss what hasn’t changed. A pluggable database is a fully functional Oracle database. It’s not watered down in any way. From the perspective of an application or an end user it hasn’t changed at all. This is very important because it means that no application changes are required to adopt this new architecture. There are many thousands of applications built on Oracle databases and they are all ready to run on Oracle Multitenant. So we have these self-contained pluggable databases (PDBs), and as their name suggests, they are plugged into a multitenant container database (CDB). The CDB behaves as a single database from the operations point of view. Very much as we had with the schema consolidation model, we only have a single set of Oracle background processes and a single, shared database memory requirement. This gives us very high consolidation density, which affords maximum reduction in capital expenses (CapEx). By performing management operations at the CDB level – “managing many as one” – we can achieve great reductions in operating expenses (OpEx) as well, but we retain granular control where appropriate. Furthermore, the “pluggability” capability gives us portability and this adds a tremendous amount of agility. We can simply unplug a PDB from one CDB and plug it into another CDB, for example to move it from one SLA tier to another. I'll explore all these new capabilities in much more detail in a future posting.  Use Cases We can identify a number of use cases for Oracle Multitenant. Here are a few of the major ones. 0 0 1 113 650 Oracle Corporation 5 1 762 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:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-fareast-language:JA;} Development / Testing where individual engineers need rapid provisioning and recycling of private copies of a few "master test databases" Consolidation of disparate applications using fewer, more powerful servers Software as a Service deploying separate copies of identical applications to individual tenants Database as a Service typically self-service provisioning of databases on the private cloud Application Distribution from ISV / Installation by Customer Eliminating many typical installation steps (create schema, import seed data, import application code PL/SQL…) - just plug in a PDB! High volume data distribution literally via disk drives in envelopes distributed by truck! - distribution of things like GIS or MDM master databases …various others! Benefits Previous approaches to consolidation have involved a trade-off between reductions in Capital Expenses (CapEx) and Operating Expenses (OpEx), and they’ve usually come at the expense of agility. With Oracle Multitenant you can have your cake and eat it: Minimize CapEx More Applications per server Minimize OpEx Manage many as one Standardized procedures and services Rapid provisioning Maximize Agility Cloning for development and testing Portability through pluggability Scalability with RAC Ease of Adoption Applications run unchanged It’s a pure deployment choice. Neither the database backend nor the application needs to be changed. In future postings I’ll explore various aspects in more detail. However, if you feel compelled to devour everything you can about Oracle Multitenant this very minute, have no fear. Visit the Multitenant page on OTN and explore the various resources we have available there. Among these, Oracle Distinguished Product Manager Bryn Llewellyn has written an excellent, thorough, and exhaustively detailed White Paper about Oracle Multitenant, which is available here.  Follow me  I tweet @OraclePDB #OracleMultitenant

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  • How do I backup my customer's data?

    - by marcamillion
    If you run a SaaS app, or work on one, I would love to hear from you. Where the safety and security of your customer's data is paramount, how do you secure it and back it up? I would love to know your main host (e.g. Heroku, Engine Yard, Rackspace, MediaTemple, etc.) and who you use for your backup. Be as detailed as possible - e.g. a quick overview of your service and the data you store (images for instance), what happens with the images when the user uploads them (e.g. they go to your Linode VPS, and posted to the site for them to see - then they are automatically sent to AWS or wherever, then once a week they are backed up to tape by the managed hosting provider, and you also back them up to your house/office). If you could also give some idea as to what the unit cost (per GB/per user/per month) of storage is - on average, I would really appreciate that. Getting ready to launch my app, and I would love to get some more perspective on the nitty gritty details involved. Thanks!

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  • Design pattern for an automated mechanical test bench

    - by JJS
    Background I have a test fixture with a number of communication/data acquisition devices on it that is used as an end of line test for a product. Because of all the various sensors used in the bench and the need to run the test procedure in near real-time, I'm having a hard time structuring the program to be more friendly to modify later on. For example, a National Instruments USB data acquisition device is used to control an analog output (load) and monitor an analog input (current), a digital scale with a serial data interface measures position, an air pressure gauge with a different serial data interface, and the product is interfaced through a proprietary DLL that handles its own serial communication. The hard part The "real-time" aspect of the program is my biggest tripping point. For example, I need to time how long the product needs to go from position 0 to position 10,000 to the tenth of a second. While it's traveling, I need to ramp up an output of the NI DAQ when it reaches position 6,000 and ramp it down when it reaches position 8,000. This sort of control looks easy from browsing NI's LabVIEW docs but I'm stuck with C# for now. All external communication is done by polling which makes for lots of annoying loops. I've slapped together a loose Producer Consumer model where the Producer thread loops through reading the sensors and sets the outputs. The Consumer thread executes functions containing timed loops that poll the Producer for current data and execute movement commands as required. The UI thread polls both threads for updating some gauges indicating current test progress. Unsure where to start Is there a more appropriate pattern for this type of application? Are there any good resources for writing control loops in software (non-LabVIEW) that interface with external sensors and whatnot?

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