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  • Should i keep css of home page and landing pages in seperate css?

    - by metal-gear-solid
    Should i keep CSS of home page and landing pages in separate CSS file of big sites. ? If i make site with a 7-8 different templates where 1 templates of home pages 1 is for inner content pages and other template for different type of landing pages. and different style needed for same HTML elements in website , For example : for inner pages H2 has different style but for landing pages H2 is different in color, font -size, line height, top bottom margin How i should manage all this ? any tips to make good,easily manageable, scan-able CSS. Thanks in advance.

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  • How to keep Lucene index synchronized with Mysql database?

    - by ?????
    I am trying to utilize Lucene to develop full text search in my application, which need to build index based on my mysql database. I was wondering is how to keep these index synchronized with db? I came up with to ways: 1) add extra code in business logic tightly to update the search index . 2) running a separated task to rebuild the index periodically. do you have any other approaches? and what do you think is the best way? Any comments would be appreciate, thanks in advance!

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  • The best approach to customize Bootstrap Less files and keep it easy to be updated to future versions

    - by user322896
    I'm wondering what the best way would be to customize the less files in Bootstrap and, at the mean time, keep it easy to be updated to future Bootstrap versions. It's straightforward to just modify the less files, but the problem is that when the next version of Bootstrap comes out, it might be painful to upgrade (because all the changes are already deeply mixed with the original sources.) Another approach would be similar to the open closed principle, that is, keeping the original less files unchanged, and adding my customized less files to overwrite the CSS rules I need. When Bootstrap gets updated, (hopefully) I can simply replace the less files and everything would work magically. However, regardless of the correctness of my assumption, the same CSS rules would be scattered in even more places and hard to manage. Also, the more we overwrite the CSS (not for compatibility or other purposes), the more bandwidth we waste. I know this highly depends on how the author of Bootstrap would handle the structure of the framework or even the naming of CSS rules, but I'd still like to hear everybody's opinions. Thanks.

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  • c language:make fgets to keep taking input until I press enter twice?

    - by wello horld
    hi I would like to ask how I would modify this code for the question: (It only accepts one input then prints it out. I want it to keep going until I hit enter (\n) twice. #include <stdio.h> #define MAXLENGTH 1000 int main(void) { char string[MAXLENGTH]; fgets(string, MAXLENGTH, stdin ); printf("%s\n", string); return 0; } I'm confused at the fgets(string, MAXLENGTH, stdin ); line, what does stdin mean/do?

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  • Managing Database Clusters - A Whole Lot Simpler

    - by mat.keep(at)oracle.com
    Clustered computing brings with it many benefits: high performance, high availability, scalable infrastructure, etc.  But it also brings with it more complexity.Why ?  Well, by its very nature, there are more "moving parts" to monitor and manage (from physical, virtual and logical hosts) to fault detection and failover software to redundant networking components - the list goes on.  And a cluster that isn't effectively provisioned and managed will cause more downtime than the standalone systems it is designed to improve upon.  Not so great....When it comes to the database industry, analysts already estimate that 50% of a typical database's Total Cost of Ownership is attributable to staffing and downtime costs.  These costs will only increase if a database cluster is to hard to properly administer.Over the past 9 months, monitoring and management has been a major focus in the development of the MySQL Cluster database, and on Tuesday 12th January, the product team will be presenting the output of that development in a new webinar.Even if you can't make the date, it is still worth registering so you will receive automatic notification when the on-demand replay is availableIn the webinar, the team will cover:    * NDBINFO: released with MySQL Cluster 7.1, NDBINFO presents real-time status and usage statistics, providing developers and DBAs with a simple means of pro-actively monitoring and optimizing database performance and availability.    * MySQL Cluster Manager (MCM): available as part of the commercial MySQL Cluster Carrier Grade Edition, MCM simplifies the creation and management of MySQL Cluster by automating common management tasks, delivering higher administration productivity and enhancing cluster agility. Tasks that used to take 46 commands can be reduced to just one!    * MySQL Cluster Advisors & Graphs: part of the MySQL Enterprise Monitor and available in the commercial MySQL Cluster Carrier Grade Edition, the Enterprise Advisor includes automated best practice rules that alert on key performance and availability metrics from MySQL Cluster data nodes.You'll also learn how you can get started evaluating and using all of these tools to simplify MySQL Cluster management.This session will last round an hour and will include interactive Q&A throughout. You can learn more about MySQL Cluster Manager from this whitepaper and on-line demonstration.  You can also download the packages from eDelivery (just select "MySQL Database" as the product pack, select your platform, click "Go" and then scroll down to get the software).While managing clusters will never be easy, the webinar will show hou how it just got a whole lot simpler !

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  • New MySQL Cluster 7.3 Previews: Foreign Keys, NoSQL Node.js API and Auto-Tuned Clusters

    - by Mat Keep
    At this weeks MySQL Connect conference, Oracle previewed an exciting new wave of developments for MySQL Cluster, further extending its simplicity and flexibility by expanding the range of use-cases, adding new NoSQL options, and automating configuration. What’s new: Development Release 1: MySQL Cluster 7.3 with Foreign Keys Early Access “Labs” Preview: MySQL Cluster NoSQL API for Node.js Early Access “Labs” Preview: MySQL Cluster GUI-Based Auto-Installer In this blog, I'll introduce you to the features being previewed. Review the blogs listed below for more detail on each of the specific features discussed. Save the date!: A live webinar is scheduled for Thursday 25th October at 0900 Pacific Time / 1600UTC where we will discuss each of these enhancements in more detail. Registration will be open soon and published to the MySQL webinars page MySQL Cluster 7.3: Development Release 1 The first MySQL Cluster 7.3 Development Milestone Release (DMR) previews Foreign Keys, bringing powerful new functionality to MySQL Cluster while eliminating development complexity. Foreign Key support has been one of the most requested enhancements to MySQL Cluster – enabling users to simplify their data models and application logic – while extending the range of use-cases for both custom projects requiring referential integrity and packaged applications, such as eCommerce, CRM, CMS, etc. Implementation The Foreign Key functionality is implemented directly within the MySQL Cluster data nodes, allowing any client API accessing the cluster to benefit from them – whether they are SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA, HTTP/REST or the new Node.js API - discussed later.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation.  This represents a further enhancement to MySQL Cluster's support for on0line schema changes, ie adding and dropping indexes, adding columns, etc.  Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  Getting Started with MySQL Cluster 7.3 DMR1: Users can download either the source or binary and evaluate the MySQL Cluster 7.3 DMR with Foreign Keys now! (Select the Development Release tab). MySQL Cluster NoSQL API for Node.js Node.js is hot! In a little over 3 years, it has become one of the most popular environments for developing next generation web, cloud, mobile and social applications. Bringing JavaScript from the browser to the server, the design goal of Node.js is to build new real-time applications supporting millions of client connections, serviced by a single CPU core. Making it simple to further extend the flexibility and power of Node.js to the database layer, we are previewing the Node.js Javascript API for MySQL Cluster as an Early Access release, available for download now from http://labs.mysql.com/. Select the following build: MySQL-Cluster-NoSQL-Connector-for-Node-js Alternatively, you can clone the project at the MySQL GitHub page.  Implemented as a module for the V8 engine, the new API provides Node.js with a native, asynchronous JavaScript interface that can be used to both query and receive results sets directly from MySQL Cluster, without transformations to SQL. Figure 1: MySQL Cluster NoSQL API for Node.js enables end-to-end JavaScript development Rather than just presenting a simple interface to the database, the Node.js module integrates the MySQL Cluster native API library directly within the web application itself, enabling developers to seamlessly couple their high performance, distributed applications with a high performance, distributed, persistence layer delivering 99.999% availability. The new Node.js API joins a rich array of NoSQL interfaces available for MySQL Cluster. Whichever API is chosen for an application, SQL and NoSQL can be used concurrently across the same data set, providing the ultimate in developer flexibility.  Get started with MySQL Cluster NoSQL API for Node.js tutorial MySQL Cluster GUI-Based Auto-Installer Compatible with both MySQL Cluster 7.2 and 7.3, the Auto-Installer makes it simple for DevOps teams to quickly configure and provision highly optimized MySQL Cluster deployments – whether on-premise or in the cloud. Implemented with a standard HTML GUI and Python-based web server back-end, the Auto-Installer intelligently configures MySQL Cluster based on application requirements and auto-discovered hardware resources Figure 2: Automated Tuning and Configuration of MySQL Cluster Developed by the same engineering team responsible for the MySQL Cluster database, the installer provides standardized configurations that make it simple, quick and easy to build stable and high performance clustered environments. The auto-installer is previewed as an Early Access release, available for download now from http://labs.mysql.com/, by selecting the MySQL-Cluster-Auto-Installer build. You can read more about getting started with the MySQL Cluster auto-installer here. Watch the YouTube video for a demonstration of using the MySQL Cluster auto-installer Getting Started with MySQL Cluster If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3 and the Early Access previews). Or use the new MySQL Cluster Auto-Installer! Download the Guide to Scaling Web Databases with MySQL Cluster (to learn more about its architecture, design and ideal use-cases). Post any questions to the MySQL Cluster forum where our Engineering team and the MySQL Cluster community will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section here or in the blogs referenced in this article. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. The first Development Release of MySQL Cluster 7.3 and the Early Access previews give you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases, by using the comments of this blog.

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  • MySQL Connect: What to Expect From the Wondrous Land of MySQL Cluster

    - by Mat Keep
    The MySQL Connect conference is only a couple of weeks away, with MySQL engineers, support teams, consultants and community aces busy putting the final touches to their talks. There will be many exciting new announcements and sharing of best practices at the conference, covering the range of MySQL technologies. MySQL Cluster will a big part of this, so I wanted to share some key sessions for those of you who plan on attending, as well as some resources for those who are not lucky enough to be able to make the trip, but who can't afford to miss the key news. Of course, this is no substitute to actually being there….and the good news is that registration is still open ;-) Roadmap: Whats New in MySQL Cluster Saturday 29th, 1300-1400, in Golden Gate room 5.                                                                                        Bernd Ocklin, director of MySQL Cluster development, and myself will be taking a look at what follows the latest MySQL Cluster 7.2 release. I don't want to give to much away - lets just say its not often you can add powerful new functionality to a product while at the same time making life radically simpler for its users. For those not making it to the Conference, a live webinar repeating the talk is scheduled for Thursday 25th October at 09.00 pacific time. Hold the date, registration will be open for that soon and published to our MySQL Webinars page Best Practices Getting Started with MySQL Cluster, Hands-On Lab Saturday 29th, 1600-1700, in Plaza Room A.                                                              Santo Leto, one of our lead MySQL Cluster support engineers, regularly works with users new to MySQL Cluster, assisting them in installation, configuration, scaling, etc. In this lab, Santo will share best-practices in getting started. Delivering Breakthrough Performance with MySQL Cluster Saturday 29th, 1730-1830, in Golden Gate room 5. Frazer Clement, lead MySQL Cluster software engineer, will demonstrate how to translate the awesome Cluster benchmarks (remember 1 BILLION UPDATEs per minute ?!) into real-world performance. You can also get some best practices from our new MySQL Cluster performance guide  MySQL Cluster BoF Saturday 29th, 1900-2000, room Golden Gate 5.                                                                                                           Come and get a demonstration of new tools for the installation and configuration of MySQL Cluster, and spend time with the engineering team discussing any questions or issues you may have. Developing High-Throughput Services with NoSQL APIs to InnoDB and MySQL Cluster Sunday 30th, 1145 - 1245, in Golden Gate room 7.   In this session, JD Duncan and Andrew Morgan will present how to get started with both Memcached and new NoSQL APIs. JD and I recently ran a webinar demonstrating how to build simple Twitter-like services with Memcached and MySQL Cluster. The replay is available for download.  Case Studies: MySQL Cluster @ El Chavo, Latin America’s #1 Facebook Game Sunday 30th, 1745 - 1845, in Golden Gate room 4.                             Playful Play deployed MySQL Cluster CGE to power their market leading social game. This session will discuss the challenges they faced, why they selected MySQL Cluster and their experiences to date. You can read more about Playful Play and MySQL Cluster here  A Journey into NoSQLand: MySQL’s NoSQL Implementation Sunday 30th, 1345 - 1445, in Golden Gate room 4.                                          Lig Turmelle, web DBA at Kaplan Professional and esteemed Oracle Ace, will discuss her experiences working with the NoSQL interfaces for both MySQL Cluster and InnoDB Evaluating MySQL HA Alternatives Saturday 29th, 1430-1530, room Golden Gate 5                                                                                   Henrik Ingo, former member of the MySQL sales engineering team, will provide an overview of various HA technologies for MySQL, starting with replication, progressing to InnoDB, Galera and MySQL Cluster What about the other stuff? Of course MySQL Connect has much, much more than MySQL Cluster. There will be lots on replication (which I'll blog about soon), MySQL 5.6, InnoDB, cloud, etc, etc. Take a look at the full Content Catalog to see more. If you are attending, I hope to see you at one of the Cluster sessions...and remember, registration is still open

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  • MySQL at Mobile World Congress (on Valentine's Day...)

    - by mat.keep(at)oracle.com
    It is that time of year again when the mobile communications industry converges on Barcelona for what many regard as the premier telecommunications show of the year.Starting on February 14th, what better way for a Brit like me to spend Valentines Day with 50,000 mobile industry leaders (my wife doesn't tend to read this blog, so I'm reasonably safe with that statement).As ever, Oracle has an extensive presence at the show, and part of that presence this year includes MySQL.We will be running a live demonstration of the MySQL Cluster database on Booth 7C18 in the App Planet.The demonstration will show how the MySQL Cluster Connector for Java is implemented to provide native connectivity to the carrier grade MySQL Cluster database from Java ME clients via Java SE virtual machines and Java EE servers.  The demonstration will show how end-to-end Java services remain continuously available during both catastrophic failures and scheduled maintenance activities.The MySQL Cluster Connector for Java provides both a native Java API and JPA plug-in that directly maps Java objects to relational tables stored in the MySQL Cluster database, without the overhead and complexity of having to transform objects to JDBC, and then SQL  The result is 10x higher throughput, and a simpler development model for Java engineers.Stop by the stand for a demonstration, and an opportunity to speak with the MySQL telecoms team who will share experiences on how MySQL is being used to bring the innovation of the web to the carrier network.Of course, if you can't make it to Barcelona, you can still learn more about the MySQL Cluster Connector for Java from this whitepaper and are free to download it as part of MySQL Cluster Community Edition  Let us know via the comments if you have Java applications that you think will benefit from the MySQL Cluster Connector for JavaI can't promise that Valentines Day at MWC will be the time you fall in love with MySQL Cluster...but I'm confident you will at least develop a healthy respect for it  

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  • How to keep track of TextPointer in WPF RichTextBox?

    - by Alan Spark
    I'm trying to get my head around the TextPointer class in a WPF RichTextBox. I would like to be able to keep track of them so that I can associate information with areas in the text. I am currently working with a very simple example to try and figure out what is going on. In the PreviewKeyDown event I am storing the caret position and then in the PreviewKeyUp event I am creating a TextRange based on the before and after caret positions. Here is a code sample that illustrates what I am trying to do: // The caret position before typing private TextPointer caretBefore = null; private void rtbTest_PreviewKeyDown(object sender, KeyEventArgs e) { // Store caret position caretBefore = rtbTest.CaretPosition; } private void rtbTest_PreviewKeyUp(object sender, KeyEventArgs e) { // Get text between before and after caret positions TextRange tr = new TextRange(caretBefore, rtbTest.CaretPosition); MessageBox.Show(tr.Text); } The problem is that the text that I get is blank. For example, if I type the character 'a' then I would expect to find the text "a" in the TextRange. Does anyone know what is going wrong? It could be something very simple but I've spent an afternoon getting nowhere. I am trying to embrace the new WPF technology but find that the RichTextBox in particular is so complicated that it makes even doing simple things like this difficult. If anyone has any links that do a good job of explaining the TextPointer, I would appreciate it if you can let me know.

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  • MySQL Connect 8 Days Away - Replication Sessions

    - by Mat Keep
    Following on from my post about MySQL Cluster sessions at the forthcoming Connect conference, its now the turn of MySQL Replication - another technology at the heart of scaling and high availability for MySQL. Unless you've only just returned from a 6-month alien abduction, you will know that MySQL 5.6 includes the largest set of replication enhancements ever packaged into a single new release: - Global Transaction IDs + HA utilities for self-healing cluster..(yes both automatic failover and manual switchover available!) - Crash-safe slaves and binlog - Binlog Group Commit and Multi-Threaded Slaves for high performance - Replication Event Checksums and Time-Delayed replication - and many more There are a number of sessions dedicated to learn more about these important new enhancements, delivered by the same engineers who developed them. Here is a summary Saturday 29th, 13.00 Replication Tips and Tricks, Mats Kindahl In this session, the developers of MySQL Replication present a bag of useful tips and tricks related to the MySQL 5.5 GA and MySQL 5.6 development milestone releases, including multisource replication, using logs for auditing, handling filtering, examining the binary log, using relay slaves, splitting the replication stream, and handling failover. Saturday 29th, 17.30 Enabling the New Generation of Web and Cloud Services with MySQL 5.6 Replication, Lars Thalmann This session showcases the new replication features, including • High performance (group commit, multithreaded slave) • High availability (crash-safe slaves, failover utilities) • Flexibility and usability (global transaction identifiers, annotated row-based replication [RBR]) • Data integrity (event checksums) Saturday 29th, 1900 MySQL Replication Birds of a Feather In this session, the MySQL Replication engineers discuss all the goodies, including global transaction identifiers (GTIDs) with autofailover; multithreaded, crash-safe slaves; checksums; and more. The team discusses the design behind these enhancements and how to get started with them. You will get the opportunity to present your feedback on how these can be further enhanced and can share any additional replication requirements you have to further scale your critical MySQL-based workloads. Sunday 30th, 10.15 Hands-On Lab, MySQL Replication, Luis Soares and Sven Sandberg But how do you get started, how does it work, and what are the best practices and tools? During this hands-on lab, you will learn how to get started with replication, how it works, architecture, replication prerequisites, setting up a simple topology, and advanced replication configurations. The session also covers some of the new features in the MySQL 5.6 development milestone releases. Sunday 30th, 13.15 Hands-On Lab, MySQL Utilities, Chuck Bell Would you like to learn how to more effectively manage a host of MySQL servers and manage high-availability features such as replication? This hands-on lab addresses these areas and more. Participants will get familiar with all of the MySQL utilities, using each of them with a variety of options to configure and manage MySQL servers. Sunday 30th, 14.45 Eliminating Downtime with MySQL Replication, Luis Soares The presentation takes a deep dive into new replication features such as global transaction identifiers and crash-safe slaves. It also showcases a range of Python utilities that, combined with the Release 5.6 feature set, results in a self-healing data infrastructure. By the end of the session, attendees will be familiar with the new high-availability features in the whole MySQL 5.6 release and how to make use of them to protect and grow their business. Sunday 30th, 17.45 Scaling for the Web and the Cloud with MySQL Replication, Luis Soares In a Replication topology, high performance directly translates into improving read consistency from slaves and reducing the risk of data loss if a master fails. MySQL 5.6 introduces several new replication features to enhance performance. In this session, you will learn about these new features, how they work, and how you can leverage them in your applications. In addition, you will learn about some other best practices that can be used to improve performance. So how can you make sure you don't miss out - the good news is that registration is still open ;-) And just to whet your appetite, listen to the On-Demand webinar that presents an overview of MySQL 5.6 Replication.  

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  • Injection with google guice does not work anymore after obfuscation with proguard

    - by sme
    Has anyone ever tried to combine the use of google guice with obfuscation (in particular proguard)? The obfuscated version of my code does not work with google guice as guice complains about missing type parameters. This information seems to be erased by the transformation step that proguard does, even when the relevant classes are excluded from the obfuscation. The stack trace looks like this: com.google.inject.CreationException: Guice creation errors: 1) Cannot inject a Provider that has no type parameter while locating com.google.inject.Provider for parameter 0 at de.repower.lvs.client.admin.user.administration.AdminUserCommonPanel.setPasswordPanelProvider(SourceFile:499) at de.repower.lvs.client.admin.user.administration.AdminUserCommonPanel.setPasswordPanelProvider(SourceFile:499) while locating de.repower.lvs.client.admin.user.administration.AdminUserCommonPanel for parameter 0 at de.repower.lvs.client.admin.user.administration.b.k.setParentPanel(SourceFile:65) at de.repower.lvs.client.admin.user.administration.b.k.setParentPanel(SourceFile:65) at de.repower.lvs.client.admin.user.administration.o.a(SourceFile:38) 2) Cannot inject a Provider that has no type parameter while locating com.google.inject.Provider for parameter 0 at de.repower.lvs.client.admin.user.administration.AdminUserCommonPanel.setWindTurbineAccessGroupProvider(SourceFile:509) at de.repower.lvs.client.admin.user.administration.AdminUserCommonPanel.setWindTurbineAccessGroupProvider(SourceFile:509) while locating de.repower.lvs.client.admin.user.administration.AdminUserCommonPanel for parameter 0 at de.repower.lvs.client.admin.user.administration.b.k.setParentPanel(SourceFile:65) at de.repower.lvs.client.admin.user.administration.b.k.setParentPanel(SourceFile:65) at de.repower.lvs.client.admin.user.administration.o.a(SourceFile:38) 2 errors at com.google.inject.internal.Errors.throwCreationExceptionIfErrorsExist(Errors.java:354) at com.google.inject.InjectorBuilder.initializeStatically(InjectorBuilder.java:152) at com.google.inject.InjectorBuilder.build(InjectorBuilder.java:105) at com.google.inject.Guice.createInjector(Guice.java:92) at com.google.inject.Guice.createInjector(Guice.java:69) at com.google.inject.Guice.createInjector(Guice.java:59) I tried to create a small example (without using guice) that seems to reproduce the problem: package de.repower.common; import java.lang.reflect.Method; import java.lang.reflect.ParameterizedType; import java.lang.reflect.Type; class SomeClass<S> { } public class ParameterizedTypeTest { public void someMethod(SomeClass<Integer> param) { System.out.println("value: " + param); System.setProperty("my.dummmy.property", "hallo"); } private static void checkParameterizedMethod(ParameterizedTypeTest testObject) { System.out.println("checking parameterized method ..."); Method[] methods = testObject.getClass().getMethods(); for (Method method : methods) { if (method.getName().equals("someMethod")) { System.out.println("Found method " + method.getName()); Type[] types = method.getGenericParameterTypes(); Type parameterType = types[0]; if (parameterType instanceof ParameterizedType) { Type parameterizedType = ((ParameterizedType) parameterType).getActualTypeArguments()[0]; System.out.println("Parameter: " + parameterizedType); System.out.println("Class: " + ((Class) parameterizedType).getName()); } else { System.out.println("Failed: type ist not instance of ParameterizedType"); } } } } public static void main(String[] args) { System.out.println("Starting ..."); try { ParameterizedTypeTest someInstance = new ParameterizedTypeTest(); checkParameterizedMethod(someInstance); } catch (SecurityException e) { e.printStackTrace(); } } } If you run this code unsbfuscated, the output looks like this: Starting ... checking parameterized method ... Found method someMethod Parameter: class java.lang.Integer Class: java.lang.Integer But running the version obfuscated with proguard yields: Starting ... checking parameterized method ... Found method someMethod Failed: type ist not instance of ParameterizedType These are the options I used for obfuscation: -injars classes_eclipse\methodTest.jar -outjars classes_eclipse\methodTestObfuscated.jar -libraryjars 'C:\Program Files\Java\jre6\lib\rt.jar' -dontskipnonpubliclibraryclasses -dontskipnonpubliclibraryclassmembers -dontshrink -printusage classes_eclipse\shrink.txt -dontoptimize -dontpreverify -verbose -keep class **.ParameterizedTypeTest.class { <fields>; <methods>; } -keep class ** { <fields>; <methods>; } # Keep - Applications. Keep all application classes, along with their 'main' # methods. -keepclasseswithmembers public class * { public static void main(java.lang.String[]); } # Also keep - Enumerations. Keep the special static methods that are required in # enumeration classes. -keepclassmembers enum * { public static **[] values(); public static ** valueOf(java.lang.String); } # Also keep - Database drivers. Keep all implementations of java.sql.Driver. -keep class * extends java.sql.Driver # Also keep - Swing UI L&F. Keep all extensions of javax.swing.plaf.ComponentUI, # along with the special 'createUI' method. -keep class * extends javax.swing.plaf.ComponentUI { public static javax.swing.plaf.ComponentUI createUI(javax.swing.JComponent); } # Keep names - Native method names. Keep all native class/method names. -keepclasseswithmembers,allowshrinking class * { native <methods>; } # Keep names - _class method names. Keep all .class method names. This may be # useful for libraries that will be obfuscated again with different obfuscators. -keepclassmembers,allowshrinking class * { java.lang.Class class$(java.lang.String); java.lang.Class class$(java.lang.String,boolean); } Does anyone have an idea of how to solve this (apart from the obvious workaround to put the relevant files into a seperate jar and not obfuscate it)? Best regards, Stefan

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  • How do I keep a CALayer, sublayer of a CATiledLayer, from changing it's scale after a zoom ?

    - by David
    I have a CATiledLayer that is used to display a PDF page (this CATiledLayer is the layer type of my UIView which is a subview of a UIScrollView). I want to add overlay markers on this page. So I add a sublayer to my CATiledLayer. This sublayer again hosts the different marker's layers and acts as a grouping layer. So graphically, I have: (keep in mind that I have multiple markers which are CALayers also, this is ascii art after all) pdf page (CATiledLayer) ---------------------- | CALayer | | +---------+ | | | +----+ | | | | |mker| | | | | +----+ | | | +---------+ | | | ---------------------- I have set up the canonical drawLayer:inContext: in my view for drawing the pdf. When I zoom to have more detail, the pdf gets rendered correctly, but the markers get scaled. No matter what I do to the bounds of the CALayer, my markers always become bigger and appear jagged. I would like to have the markers always the same size, as when they were initialized and first shown when the view was drawn. Is this possible ? or am I using a wrong approach ? Should I do special drawing for my contained CALayer in the drawLAyer:inContext: message ? As you see, there are things that I am missing to resolve my problem. Thank you for any help you provide.

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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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  • MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!

    - by Mat Keep
    0 0 1 1097 6254 Homework 52 14 7337 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 (aka TL/DR): Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build) In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release. Pace of Innovation It was only a couple of months ago that we announced the General Availability (GA) of MySQL Cluster 7.2, delivering 1 billion Queries per Minute, with 70x higher cross-shard JOIN performance, Memcached NoSQL key-value API and cross-data center replication.  This release has been a huge hit, with downloads and deployments quickly reaching record levels. The announcement of the first MySQL Cluster 7.3 Early Access lab release at today's MySQL Innovation Day event demonstrates the continued pace in Cluster development, and provides an opportunity for the community to evaluate and feedback on new features they want to see. What’s the Plan for MySQL Cluster 7.3? Well, Foreign Keys, as you may have gathered by now (!), and this is the focus of this first Labs Release. As with MySQL Cluster 7.2, we plan to publish a series of preview releases for 7.3 that will incrementally add new candidate features for a final GA release (subject to usual safe harbor statement below*), including: - New NoSQL APIs; - Features to automate the configuration and provisioning of multi-node clusters, on premise or in the cloud; - Performance and scalability enhancements; - Taking advantage of features in the latest MySQL 5.x Server GA. Design Rationale MySQL Cluster is designed as a “Not-Only-SQL” database. It combines attributes that enable users to blend the best of both relational and NoSQL technologies into solutions that deliver web scalability with 99.999% availability and real-time performance, including: Concurrent NoSQL and SQL access to the database; Auto-sharding with simple scale-out across commodity hardware; Multi-master replication with failover and recovery both within and across data centers; Shared-nothing architecture with no single point of failure; Online scaling and schema changes; ACID compliance and support for complex queries, across shards. Native support for Foreign Key constraints enables users to extend the benefits of MySQL Cluster into a broader range of use-cases, including: - Packaged applications in areas such as eCommerce and Web Content Management that prescribe databases with Foreign Key support. - In-house developments benefiting from Foreign Key constraints to simplify data models and eliminate the additional application logic needed to maintain data consistency and integrity between tables. Implementation The Foreign Key functionality is implemented directly within MySQL Cluster’s data nodes, allowing any client API accessing the cluster to benefit from them – whether using SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA or HTTP/REST.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation. An important difference to note with the Foreign Key implementation in InnoDB is that MySQL Cluster does not support the updating of Primary Keys from within the Data Nodes themselves - instead the UPDATE is emulated with a DELETE followed by an INSERT operation. Therefore an UPDATE operation will return an error if the parent reference is using a Primary Key, unless using CASCADE action, in which case the delete operation will result in the corresponding rows in the child table being deleted. The Engineering team plans to change this behavior in a subsequent preview release. Also note that when using InnoDB "NO ACTION" is identical to "RESTRICT". In the case of MySQL Cluster “NO ACTION” means “deferred check”, i.e. the constraint is checked before commit, allowing user-defined triggers to automatically make changes in order to satisfy the Foreign Key constraints. Configuration There is nothing special you have to do here – Foreign Key constraint checking is enabled by default. If you intend to migrate existing tables from another database or storage engine, for example from InnoDB, there are a couple of best practices to observe: 1. Analyze the structure of the Foreign Key graph and run the ALTER TABLE ENGINE=NDB in the correct sequence to ensure constraints are enforced 2. Alternatively drop the Foreign Key constraints prior to the import process and then recreate when complete. Getting Started Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  You can download MySQL Cluster 7.3 Labs Release with Foreign Keys today - (select the mysql-cluster-7.3-labs-June-2012 build) If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3) Post any questions to the MySQL Cluster forum where our Engineering team will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section of this blog. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. This first Labs Release of MySQL Cluster 7.3 gives you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases. * Safe Harbor Statement This information is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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  • MySQL Cluster 7.3: On-Demand Webinar and Q&A Available

    - by Mat Keep
    The on-demand webinar for the MySQL Cluster 7.3 Development Release is now available. You can learn more about the design, implementation and getting started with all of the new MySQL Cluster 7.3 features from the comfort and convenience of your own device, including: - Foreign Key constraints in MySQL Cluster - Node.js NoSQL API  - Auto-installation of higher performance distributed, clusters We received some great questions over the course of the webinar, and I wanted to share those for the benefit of a broader audience. Q. What Foreign Key actions are supported: A. The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL Q. Where are Foreign Keys implemented, ie data nodes or SQL nodes? A. They are implemented in the data nodes, therefore can be enforced for both the SQL and NoSQL APIs Q. Are they compatible with the InnoDB Foreign Key implementation? A. Yes, with the following exceptions: - InnoDB doesn’t support “No Action” constraints, MySQL Cluster does - You can choose to suspend FK constraint enforcement with InnoDB using the FOREIGN_KEY_CHECKS parameter; at the moment, MySQL Cluster ignores that parameter. - You cannot set up FKs between 2 tables where one is stored using MySQL Cluster and the other InnoDB. - You cannot change primary keys through the NDB API which means that the MySQL Server actually has to simulate such operations by deleting and re-adding the row. If the PK in the parent table has a FK constraint on it then this causes non-ideal behaviour. With Restrict or No Action constraints, the change will result in an error. With Cascaded constraints, you’d want the rows in the child table to be updated with the new FK value but, the implicit delete of the row from the parent table would remove the associated rows from the child table and the subsequent implicit insert into the parent wouldn’t reinstate the child rows. For this reason, an attempt to add an ON UPDATE CASCADE where the parent column is a primary key will be rejected. Q. Does adding or dropping Foreign Keys cause downtime due to a schema change? A. Nope, this is an online operation. MySQL Cluster supports a number of on-line schema changes, ie adding and dropping indexes, adding columns, etc. Q. Where can I see an example of node.js with MySQL Cluster? A. Check out the tutorial and download the code from GitHub Q. Can I use the auto-installer to support remote deployments? How about setting up MySQL Cluster 7.2? A. Yes to both! Q. Can I get a demo Check out the tutorial. You can download the code from http://labs.mysql.com/ Go to Select Build drop-down box Q. What is be minimum internet speen required for Geo distributed cluster with synchronous replication? A. if you're splitting you cluster between sites then we recommend a network latency of 20ms or less. Alternatively, use MySQL asynchronous replication where the latency of your WAN doesn't impact the latency of your reads/writes. Q. Where you can one learn more about the PayPal project with MySQL Cluster? A. Take a look at the following - you'll find press coverage, a video and slides from their keynote presentation  So, if you want to learn more, listen to the new MySQL Cluster 7.3 on-demand webinar  MySQL Cluster 7.3 is still in the development phase, so it would be great to get your feedback on these new features, and things you want to see!

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  • MySQL Cluster 7.3 - Join This Week's Webinar to Learn What's New

    - by Mat Keep
    The first Development Milestone and Early Access releases of MySQL Cluster 7.3 were announced just several weeks ago. To provide more detail and demonstrate the new features, Andrew Morgan and I will be hosting a live webinar this coming Thursday 25th October at 0900 Pacific Time / 16.00 UTC Even if you can't make the live webinar, it is still worth registering for the event as you will receive a notification when the replay will be available, to view on-demand at your convenience In the webinar, we will discuss the enhancements being previewed as part of MySQL Cluster 7.3, including: - Foreign Key Constraints: Yes, we've looked into the future and decided Foreign Keys are it ;-) You can read more about the implementation of Foreign Keys in MySQL Cluster 7.3 here - Node.js NoSQL API: Allowing web, mobile and cloud services to query and receive results sets from MySQL Cluster, natively in JavaScript, enables developers to seamlessly couple high performance, distributed applications with a high performance, distributed, persistence layer delivering 99.999% availability. You can study the Node.js / MySQL Cluster tutorial here - Auto-Installer: This new web-based GUI makes it simple for DevOps teams to quickly configure and provision highly optimized MySQL Cluster deployments on-premise or in the cloud You can view a YouTube tutorial on the MySQL Cluster Auto-Installer here  So we have a lot to cover in our 45 minute session. It will be time well spent if you want to know more about the future direction of MySQL Cluster and how it can help you innovate faster, with greater simplicity. Registration is open 

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  • Redehost Transforms Cloud & Hosting Services with MySQL Enterprise Edition

    - by Mat Keep
    RedeHost are one of Brazil's largest cloud computing and web hosting providers, with more than 60,000 customers and 52,000 web sites running on its infrastructure. As the company grew, Redehost needed to automate operations, such as system monitoring, making the operations team more proactive in solving problems. Redehost also sought to improve server uptime, robustness, and availability, especially during backup windows, when performance would often dip. To address the needs of the business, Redehost migrated from the community edition of MySQL to MySQL Enterprise Edition, which has delivered a host of benefits: - Pro-active database management and monitoring using MySQL Enterprise Monitor, enabling Redehost to fulfil customer SLAs. Using the Query Analyzer, Redehost were able to more rapidly identify slow queries, improving customer support - Quadrupled backup speed with MySQL Enterprise Backup, leading to faster data recovery and improved system availability - Reduced DBA overhead by 50% due to the improved support capabilities offered by MySQL Enterprise Edition. - Enabled infrastructure consolidation, avoiding unnecessary energy costs and premature hardware acquisition You can learn more from the full Redehost Case Study Also, take a look at the recently updated MySQL in the Cloud whitepaper for the latest developments that are making it even simpler and more efficient to develop and deploy new services with MySQL in the cloud

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  • NoSQL Java API for MySQL Cluster: Questions & Answers

    - by Mat Keep
    The MySQL Cluster engineering team recently ran a live webinar, available now on-demand demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster, and how these can be used in building real-time, high scale Java-based services that require continuous availability. Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs. First, a little bit about why we developed these APIs and why they are interesting to Java developers. ClusterJ and Cluster JPA ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used by JDO, JPA, and Hibernate. A simple API gives users extremely high performance for common operations: insert, delete, update, and query. ClusterJPA works with ClusterJ to extend functionality, including - Persistent classes - Relationships - Joins in queries - Lazy loading - Table and index creation from object model By eliminating data transformations via SQL, users get lower data access latency and higher throughput. In addition, Java developers have a more natural programming method to directly manage their data, with a complete, feature-rich solution for Object/Relational Mapping. As a result, the development of Java applications is simplified with faster development cycles resulting in accelerated time to market for new services. MySQL Cluster offers multiple NoSQL APIs alongside Java: - Memcached for a persistent, high performance, write-scalable Key/Value store, - HTTP/REST via an Apache module - C++ via the NDB API for the lowest absolute latency. Developers can use SQL as well as NoSQL APIs for access to the same data set via multiple query patterns – from simple Primary Key lookups or inserts to complex cross-shard JOINs using Adaptive Query Localization Marrying NoSQL and SQL access to an ACID-compliant database offers developers a number of benefits. MySQL Cluster’s distributed, shared-nothing architecture with auto-sharding and real time performance makes it a great fit for workloads requiring high volume OLTP. Users also get the added flexibility of being able to run real-time analytics across the same OLTP data set for real-time business insight. OK – hopefully you now have a better idea of why ClusterJ and JPA are available. Now, for the Q&A. Q & A Q. Why would I use Connector/J vs. ClusterJ? A. Partly it's a question of whether you prefer to work with SQL (Connector/J) or objects (ClusterJ). Performance of ClusterJ will be better as there is no need to pass through the MySQL Server. A ClusterJ operation can only act on a single table (e.g. no joins) - ClusterJPA extends that capability Q. Can I mix different APIs (ie ClusterJ, Connector/J) in our application for different query types? A. Yes. You can mix and match all of the API types, SQL, JDBC, ODBC, ClusterJ, Memcached, REST, C++. They all access the exact same data in the data nodes. Update through one API and new data is instantly visible to all of the others. Q. How many TCP connections would a SessionFactory instance create for a cluster of 8 data nodes? A. SessionFactory has a connection to the mgmd (management node) but otherwise is just a vehicle to create Sessions. Without using connection pooling, a SessionFactory will have one connection open with each data node. Using optional connection pooling allows multiple connections from the SessionFactory to increase throughput. Q. Can you give details of how Cluster J optimizes sharding to enhance performance of distributed query processing? A. Each data node in a cluster runs a Transaction Coordinator (TC), which begins and ends the transaction, but also serves as a resource to operate on the result rows. While an API node (such as a ClusterJ process) can send queries to any TC/data node, there are performance gains if the TC is where most of the result data is stored. ClusterJ computes the shard (partition) key to choose the data node where the row resides as the TC. Q. What happens if we perform two primary key lookups within the same transaction? Are they sent to the data node in one transaction? A. ClusterJ will send identical PK lookups to the same data node. Q. How is distributed query processing handled by MySQL Cluster ? A. If the data is split between data nodes then all of the information will be transparently combined and passed back to the application. The session will connect to a data node - typically by hashing the primary key - which then interacts with its neighboring nodes to collect the data needed to fulfil the query. Q. Can I use Foreign Keys with MySQL Cluster A. Support for Foreign Keys is included in the MySQL Cluster 7.3 Early Access release Summary The NoSQL Java APIs are packaged with MySQL Cluster, available for download here so feel free to take them for a spin today! Key Resources MySQL Cluster on-line demo  MySQL ClusterJ and JPA On-demand webinar  MySQL ClusterJ and JPA documentation MySQL ClusterJ and JPA whitepaper and tutorial

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  • How to keep track of a private messaging system using MongoDB?

    - by luckytaxi
    Take facebook's private messaging system where you have to keep track of sender and receiver along w/ the message content. If I were using MySQL I would have multiple tables, but with MongoDB I'll try to avoid all that. I'm trying to come up with a "good" schema that can scale and is easy to maintain. If I were using mysql, I would have a separate table to reference the user and and message. See below ... profiles table user_id first_name last_name message table message_id message_body time_stamp user_message_ref table user_id (FK) message_id (FK) is_sender (boolean) With the schema listed above, I can query for any messages that "Bob" may have regardless if he's the recipient or sender. Now how to turn that into a schema that works with MongoDB. I'm thinking I'll have a separate collection to hold the messages. Problem is, how can I differentiate between the sender and the recipient? If Bob logs in, what do I query against? Depending on whether Bob initiated the email, I don't want to have to query against "sender" and "receiver" just to see if the message belongs to the user.

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  • MySQL and Hadoop Integration - Unlocking New Insight

    - by Mat Keep
    “Big Data” offers the potential for organizations to revolutionize their operations. With the volume of business data doubling every 1.2 years, analysts and business users are discovering very real benefits when integrating and analyzing data from multiple sources, enabling deeper insight into their customers, partners, and business processes. As the world’s most popular open source database, and the most deployed database in the web and cloud, MySQL is a key component of many big data platforms, with Hadoop vendors estimating 80% of deployments are integrated with MySQL. The new Guide to MySQL and Hadoop presents the tools enabling integration between the two data platforms, supporting the data lifecycle from acquisition and organisation to analysis and visualisation / decision, as shown in the figure below The Guide details each of these stages and the technologies supporting them: Acquire: Through new NoSQL APIs, MySQL is able to ingest high volume, high velocity data, without sacrificing ACID guarantees, thereby ensuring data quality. Real-time analytics can also be run against newly acquired data, enabling immediate business insight, before data is loaded into Hadoop. In addition, sensitive data can be pre-processed, for example healthcare or financial services records can be anonymized, before transfer to Hadoop. Organize: Data is transferred from MySQL tables to Hadoop using Apache Sqoop. With the MySQL Binlog (Binary Log) API, users can also invoke real-time change data capture processes to stream updates to HDFS. Analyze: Multi-structured data ingested from multiple sources is consolidated and processed within the Hadoop platform. Decide: The results of the analysis are loaded back to MySQL via Apache Sqoop where they inform real-time operational processes or provide source data for BI analytics tools. So how are companies taking advantage of this today? As an example, on-line retailers can use big data from their web properties to better understand site visitors’ activities, such as paths through the site, pages viewed, and comments posted. This knowledge can be combined with user profiles and purchasing history to gain a better understanding of customers, and the delivery of highly targeted offers. Of course, it is not just in the web that big data can make a difference. Every business activity can benefit, with other common use cases including: - Sentiment analysis; - Marketing campaign analysis; - Customer churn modeling; - Fraud detection; - Research and Development; - Risk Modeling; - And more. As the guide discusses, Big Data is promising a significant transformation of the way organizations leverage data to run their businesses. MySQL can be seamlessly integrated within a Big Data lifecycle, enabling the unification of multi-structured data into common data platforms, taking advantage of all new data sources and yielding more insight than was ever previously imaginable. Download the guide to MySQL and Hadoop integration to learn more. I'd also be interested in hearing about how you are integrating MySQL with Hadoop today, and your requirements for the future, so please use the comments on this blog to share your insights.

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  • New Options for MySQL High Availability

    - by Mat Keep
    Data is the currency of today’s web, mobile, social, enterprise and cloud applications. Ensuring data is always available is a top priority for any organization – minutes of downtime will result in significant loss of revenue and reputation. There is not a “one size fits all” approach to delivering High Availability (HA). Unique application attributes, business requirements, operational capabilities and legacy infrastructure can all influence HA technology selection. And then technology is only one element in delivering HA – “People and Processes” are just as critical as the technology itself. For this reason, MySQL Enterprise Edition is available supporting a range of HA solutions, fully certified and supported by Oracle. MySQL Enterprise HA is not some expensive add-on, but included within the core Enterprise Edition offering, along with the management tools, consulting and 24x7 support needed to deliver true HA. At the recent MySQL Connect conference, we announced new HA options for MySQL users running on both Linux and Solaris: - DRBD for MySQL - Oracle Solaris Clustering for MySQL DRBD (Distributed Replicated Block Device) is an open source Linux kernel module which leverages synchronous replication to deliver high availability database applications across local storage. DRBD synchronizes database changes by mirroring data from an active node to a standby node and supports automatic failover and recovery. Linux, DRBD, Corosync and Pacemaker, provide an integrated stack of mature and proven open source technologies. DRBD Stack: Providing Synchronous Replication for the MySQL Database with InnoDB Download the DRBD for MySQL whitepaper to learn more, including step-by-step instructions to install, configure and provision DRBD with MySQL Oracle Solaris Cluster provides high availability and load balancing to mission-critical applications and services in physical or virtualized environments. With Oracle Solaris Cluster, organizations have a scalable and flexible solution that is suited equally to small clusters in local datacenters or larger multi-site, multi-cluster deployments that are part of enterprise disaster recovery implementations. The Oracle Solaris Cluster MySQL agent integrates seamlessly with MySQL offering a selection of configuration options in the various Oracle Solaris Cluster topologies. Putting it All Together When you add MySQL Replication and MySQL Cluster into the HA mix, along with 3rd party solutions, users have extensive choice (and decisions to make) to deliver HA services built on MySQL To make the decision process simpler, we have also published a new MySQL HA Solutions Guide. Exploring beyond just the technology, the guide presents a methodology to select the best HA solution for your new web, cloud and mobile services, while also discussing the importance of people and process in ensuring service continuity. This is subject recently presented at Oracle Open World, and the slides are available here. Whatever your uptime requirements, you can be sure MySQL has an HA solution for your needs Please don't hesitate to let us know of your HA requirements in the comments section of this blog. You can also contact MySQL consulting to learn more about their HA Jumpstart offering which will help you scope out your scaling and HA requirements.

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  • Guide to MySQL & NoSQL, Webinar Q&A

    - by Mat Keep
    0 0 1 959 5469 Homework 45 12 6416 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;} Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful. Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar. Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL: - On-Demand webinar (coming soon!) - Slides used during the webinar - Guide to MySQL and NoSQL whitepaper  - MySQL Cluster demo, including NoSQL interfaces, auto-sharing, high availability, etc.  So here is the Q&A from the event  Q. Where does MySQL Cluster fit in to the CAP theorem? A. MySQL Cluster is flexible. A single Cluster will prefer consistency over availability in the presence of network partitions. A pair of Clusters can be configured to prefer availability over consistency. A full explanation can be found on the MySQL Cluster & CAP Theorem blog post.  Q. Can you configure the number of replicas? (the slide used a replication factor of 1) Yes. A cluster is configured by an .ini file. The option NoOfReplicas sets the number of originals and replicas: 1 = no data redundancy, 2 = one copy etc. Usually there's no benefit in setting it >2. Q. Interestingly most (if not all) of the NoSQL databases recommend having 3 copies of data (the replication factor).    Yes, with configurable quorum based Reads and writes. MySQL Cluster does not need a quorum of replicas online to provide service. Systems that require a quorum need > 2 replicas to be able to tolerate a single failure. Additionally, many NoSQL systems take liberal inspiration from the original GFS paper which described a 3 replica configuration. MySQL Cluster avoids the need for a quorum by using a lightweight arbitrator. You can configure more than 2 replicas, but this is a tradeoff between incrementally improved availability, and linearly increased cost. Q. Can you have cross node group JOINS? Wouldn't that run into the risk of flooding the network? MySQL Cluster 7.2 supports cross nodegroup joins. A full cross-join can require a large amount of data transfer, which may bottleneck on network bandwidth. However, for more selective joins, typically seen with OLTP and light analytic applications, cross node-group joins give a great performance boost and network bandwidth saving over having the MySQL Server perform the join. Q. Are the details of the benchmark available anywhere? According to my calculations it results in approx. 350k ops/sec per processor which is the largest number I've seen lately The details are linked from Mikael Ronstrom's blog The benchmark uses a benchmarking tool we call flexAsynch which runs parallel asynchronous transactions. It involved 100 byte reads, of 25 columns each. Regarding the per-processor ops/s, MySQL Cluster is particularly efficient in terms of throughput/node. It uses lock-free minimal copy message passing internally, and maximizes ID cache reuse. Note also that these are in-memory tables, there is no need to read anything from disk. Q. Is access control (like table) planned to be supported for NoSQL access mode? Currently we have not seen much need for full SQL-like access control (which has always been overkill for web apps and telco apps). So we have no plans, though especially with memcached it is certainly possible to turn-on connection-level access control. But specifically table level controls are not planned. Q. How is the performance of memcached APi with MySQL against memcached+MySQL or any other Object Cache like Ecache with MySQL DB? With the memcache API we generally see a memcached response in less than 1 ms. and a small cluster with one memcached server can handle tens of thousands of operations per second. Q. Can .NET can access MemcachedAPI? Yes, just use a .Net memcache client such as the enyim or BeIT memcache libraries. Q. Is the row level locking applicable when you update a column through memcached API? An update that comes through memcached uses a row lock and then releases it immediately. Memcached operations like "INCREMENT" are actually pushed down to the data nodes. In most cases the locks are not even held long enough for a network round trip. Q. Has anyone published an example using something like PHP? I am assuming that you just use the PHP memcached extension to hook into the memcached API. Is that correct? Not that I'm aware of but absolutely you can use it with php or any of the other drivers Q. For beginner we need more examples. Take a look here for a fully worked example Q. Can I access MySQL using Cobol (Open Cobol) or C and if so where can I find the coding libraries etc? A. There is a cobol implementation that works well with MySQL, but I do not think it is Open Cobol. Also there is a MySQL C client library that is a standard part of every mysql distribution Q. Is there a place to go to find help when testing and/implementing the NoSQL access? If using Cluster then you can use the [email protected] alias or post on the MySQL Cluster forum Q. Are there any white papers on this?  Yes - there is more detail in the MySQL Guide to NoSQL whitepaper If you have further questions, please don’t hesitate to use the comments below!

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  • Benchmarking MySQL Replication with Multi-Threaded Slaves

    - by Mat Keep
    0 0 1 1145 6530 Homework 54 15 7660 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;} The objective of this benchmark is to measure the performance improvement achieved when enabling the Multi-Threaded Slave enhancement delivered as a part MySQL 5.6. As the results demonstrate, Multi-Threaded Slaves delivers 5x higher replication performance based on a configuration with 10 databases/schemas. For real-world deployments, higher replication performance directly translates to: · Improved consistency of reads from slaves (i.e. reduced risk of reading "stale" data) · Reduced risk of data loss should the master fail before replicating all events in its binary log (binlog) The multi-threaded slave splits processing between worker threads based on schema, allowing updates to be applied in parallel, rather than sequentially. This delivers benefits to those workloads that isolate application data using databases - e.g. multi-tenant systems deployed in cloud environments. Multi-Threaded Slaves are just one of many enhancements to replication previewed as part of the MySQL 5.6 Development Release, which include: · Global Transaction Identifiers coupled with MySQL utilities for automatic failover / switchover and slave promotion · Crash Safe Slaves and Binlog · Optimized Row Based Replication · Replication Event Checksums · Time Delayed Replication These and many more are discussed in the “MySQL 5.6 Replication: Enabling the Next Generation of Web & Cloud Services” Developer Zone article  Back to the benchmark - details are as follows. Environment The test environment consisted of two Linux servers: · one running the replication master · one running the replication slave. Only the slave was involved in the actual measurements, and was based on the following configuration: - Hardware: Oracle Sun Fire X4170 M2 Server - CPU: 2 sockets, 6 cores with hyper-threading, 2930 MHz. - OS: 64-bit Oracle Enterprise Linux 6.1 - Memory: 48 GB Test Procedure Initial Setup: Two MySQL servers were started on two different hosts, configured as replication master and slave. 10 sysbench schemas were created, each with a single table: CREATE TABLE `sbtest` (    `id` int(10) unsigned NOT NULL AUTO_INCREMENT,    `k` int(10) unsigned NOT NULL DEFAULT '0',    `c` char(120) NOT NULL DEFAULT '',    `pad` char(60) NOT NULL DEFAULT '',    PRIMARY KEY (`id`),    KEY `k` (`k`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 10,000 rows were inserted in each of the 10 tables, for a total of 100,000 rows. When the inserts had replicated to the slave, the slave threads were stopped. The slave data directory was copied to a backup location and the slave threads position in the master binlog noted. 10 sysbench clients, each configured with 10 threads, were spawned at the same time to generate a random schema load against each of the 10 schemas on the master. Each sysbench client executed 10,000 "update key" statements: UPDATE sbtest set k=k+1 WHERE id = <random row> In total, this generated 100,000 update statements to later replicate during the test itself. Test Methodology: The number of slave workers to test with was configured using: SET GLOBAL slave_parallel_workers=<workers> Then the slave IO thread was started and the test waited for all the update queries to be copied over to the relay log on the slave. The benchmark clock was started and then the slave SQL thread was started. The test waited for the slave SQL thread to finish executing the 100k update queries, doing "select master_pos_wait()". When master_pos_wait() returned, the benchmark clock was stopped and the duration calculated. The calculated duration from the benchmark clock should be close to the time it took for the SQL thread to execute the 100,000 update queries. The 100k queries divided by this duration gave the benchmark metric, reported as Queries Per Second (QPS). Test Reset: The test-reset cycle was implemented as follows: · the slave was stopped · the slave data directory replaced with the previous backup · the slave restarted with the slave threads replication pointer repositioned to the point before the update queries in the binlog. The test could then be repeated with identical set of queries but a different number of slave worker threads, enabling a fair comparison. The Test-Reset cycle was repeated 3 times for 0-24 number of workers and the QPS metric calculated and averaged for each worker count. MySQL Configuration The relevant configuration settings used for MySQL are as follows: binlog-format=STATEMENT relay-log-info-repository=TABLE master-info-repository=TABLE As described in the test procedure, the slave_parallel_workers setting was modified as part of the test logic. The consequence of changing this setting is: 0 worker threads:    - current (i.e. single threaded) sequential mode    - 1 x IO thread and 1 x SQL thread    - SQL thread both reads and executes the events 1 worker thread:    - sequential mode    - 1 x IO thread, 1 x Coordinator SQL thread and 1 x Worker thread    - coordinator reads the event and hands it to the worker who executes 2+ worker threads:    - parallel execution    - 1 x IO thread, 1 x Coordinator SQL thread and 2+ Worker threads    - coordinator reads events and hands them to the workers who execute them Results Figure 1 below shows that Multi-Threaded Slaves deliver ~5x higher replication performance when configured with 10 worker threads, with the load evenly distributed across our 10 x schemas. This result is compared to the current replication implementation which is based on a single SQL thread only (i.e. zero worker threads). Figure 1: 5x Higher Performance with Multi-Threaded Slaves The following figure shows more detailed results, with QPS sampled and reported as the worker threads are incremented. The raw numbers behind this graph are reported in the Appendix section of this post. Figure 2: Detailed Results As the results above show, the configuration does not scale noticably from 5 to 9 worker threads. When configured with 10 worker threads however, scalability increases significantly. The conclusion therefore is that it is desirable to configure the same number of worker threads as schemas. Other conclusions from the results: · Running with 1 worker compared to zero workers just introduces overhead without the benefit of parallel execution. · As expected, having more workers than schemas adds no visible benefit. Aside from what is shown in the results above, testing also demonstrated that the following settings had a very positive effect on slave performance: relay-log-info-repository=TABLE master-info-repository=TABLE For 5+ workers, it was up to 2.3 times as fast to run with TABLE compared to FILE. Conclusion As the results demonstrate, Multi-Threaded Slaves deliver significant performance increases to MySQL replication when handling multiple schemas. This, and the other replication enhancements introduced in MySQL 5.6 are fully available for you to download and evaluate now from the MySQL Developer site (select Development Release tab). You can learn more about MySQL 5.6 from the documentation  Please don’t hesitate to comment on this or other replication blogs with feedback and questions. Appendix – Detailed Results

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  • WPF: How can I KEEP the same ItemTemplate instance once its created ??

    - by Samir Sabri
    Hello, Here is a cinario: I have a ListView, with ItemsSource = ProjectModel.Instance.PagesModelsCollection; where PagesModelsCollection is an ObservableCollection In the ListView XAML part: <ListView.ItemTemplate> <DataTemplate x:Name="PagesViewDataTemplate"> <DataTemplate.Resources> <Style x:Key="PageHostStyle" TargetType="{x:Type p:KPage}"> </Style> </DataTemplate.Resources> <StackPanel x:Name="MarginStack" Margin="50,50,50,50" > <p:KPage x:Name="PageHost" > </p:KPage> </StackPanel> </DataTemplate> </ListView.ItemTemplate> The problem is the ITemTemplate is re-created each time we refresh the Items. So, if we have 100 Item in the list view, another 100 new ItemTemplate instance will be created if we refresh the items! As a result, if we add UIElements on one of the ItemTemplate intances, those added UIElements will be lost, because the old ITemTemplate is replaced with a new one! How can I KEEP the ItemTemplate instance once its created ??

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  • Using Interop.Word, is there a way to do a replace (using Find.Execute) and keep the original text's

    - by AJ
    I'm attempting to write find/replace code for Word documents using Word Automation through Interop.Word (11.0). My documents all have various fields (that don't show up in Document.Fields) that are surrounded with brackets, eg., <DATE> needs to be replaced with DateTime.Now.Format("MM/dd/yyyy"). The find/replace works fine. However, some of the text being replaced is right-justified, and upon replacement, the text wraps to the next line. Is there any way that I can keep the justification when I perform the replace? Code is below: using Word = Microsoft.Office.Interop.Word; Word.Application wordApp = null; try { wordApp = new Word.Application {Visible = false}; //.... open the document .... object unitsStory = Word.WdUnits.wdStory; object moveType = Word.WdMovementType.wdMove; wordApp.Selection.HomeKey(ref unitsStory, ref moveType); wordApp.Selection.Find.ClearFormatting(); wordApp.Selection.Find.Replacement.ClearFormatting(); //tried removing this, no luck object replaceTextWith = DateTime.Now.ToString("MM/dd/yyyy"); object textToReplace = "<DATE>"; object replaceAll = Word.WdReplace.wdReplaceAll; object typeMissing = System.Reflection.Missing.Value; wordApp.Selection.Find.Execute(ref textToReplace, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing, ref replaceTextWith, ref replaceAll, ref typeMissing, ref typeMissing, ref typeMissing, ref typeMissing); // ... save quit etc.... } finally { //clean up wordApp } TIA.

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