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• A python random function acts differently when assigned to a list or called directly...

  - by Dror Hilman

  I have a python function that randomize a dictionary representing a position specific scoring matrix. for example: mat = { 'A' : [ 0.53, 0.66, 0.67, 0.05, 0.01, 0.86, 0.03, 0.97, 0.33, 0.41, 0.26 ] 'C' : [ 0.14, 0.04, 0.13, 0.92, 0.99, 0.04, 0.94, 0.00, 0.07, 0.23, 0.35 ] 'T' : [ 0.25, 0.07, 0.01, 0.01, 0.00, 0.04, 0.00, 0.03, 0.06, 0.12, 0.14 ] 'G' : [ 0.08, 0.23, 0.20, 0.02, 0.00, 0.06, 0.04, 0.00, 0.54, 0.24, 0.25 ] } The scambling function: def scramble_matrix(matrix, iterations): mat_len = len(matrix["A"]) pos1 = pos2 = 0 for count in range(iterations): pos1,pos2 = random.sample(range(mat_len), 2) #suffle the matrix: for nuc in matrix.keys(): matrix[nuc][pos1],matrix[nuc][pos2] = matrix[nuc][pos2],matrix[nuc][pos1] return matrix def print_matrix(matrix): for nuc in matrix.keys(): print nuc+"[", for count in matrix[nuc]: print "%.2f"%count, print "]" now to the problem... When I try to scramble a matrix directly, It's works fine: print_matrix(mat) print "" print_matrix(scramble_matrix(mat,10)) gives: A[ 0.53 0.66 0.67 0.05 0.01 0.86 0.03 0.97 0.33 0.41 0.26 ] C[ 0.14 0.04 0.13 0.92 0.99 0.04 0.94 0.00 0.07 0.23 0.35 ] T[ 0.25 0.07 0.01 0.01 0.00 0.04 0.00 0.03 0.06 0.12 0.14 ] G[ 0.08 0.23 0.20 0.02 0.00 0.06 0.04 0.00 0.54 0.24 0.25 ] A[ 0.41 0.97 0.03 0.86 0.53 0.66 0.33.05 0.67 0.26 0.01 ] C[ 0.23 0.00 0.94 0.04 0.14 0.04 0.07 0.92 0.13 0.35 0.99 ] T[ 0.12 0.03 0.00 0.04 0.25 0.07 0.06 0.01 0.01 0.14 0.00 ] G[ 0.24 0.00 0.04 0.06 0.08 0.23 0.54 0.02 0.20 0.25 0.00 ] but when I try to assign this scrambling to a list , it does not work!!! ... print_matrix(mat) s=[] for x in range(3): s.append(scramble_matrix(mat,10)) for matrix in s: print "" print_matrix(matrix) result: A[ 0.53 0.66 0.67 0.05 0.01 0.86 0.03 0.97 0.33 0.41 0.26 ] C[ 0.14 0.04 0.13 0.92 0.99 0.04 0.94 0.00 0.07 0.23 0.35 ] T[ 0.25 0.07 0.01 0.01 0.00 0.04 0.00 0.03 0.06 0.12 0.14 ] G[ 0.08 0.23 0.20 0.02 0.00 0.06 0.04 0.00 0.54 0.24 0.25 ] A[ 0.01 0.66 0.97 0.67 0.03 0.05 0.33 0.53 0.26 0.41 0.86 ] C[ 0.99 0.04 0.00 0.13 0.94 0.92 0.07 0.14 0.35 0.23 0.04 ] T[ 0.00 0.07 0.03 0.01 0.00 0.01 0.06 0.25 0.14 0.12 0.04 ] G[ 0.00 0.23 0.00 0.20 0.04 0.02 0.54 0.08 0.25 0.24 0.06 ] A[ 0.01 0.66 0.97 0.67 0.03 0.05 0.33 0.53 0.26 0.41 0.86 ] C[ 0.99 0.04 0.00 0.13 0.94 0.92 0.07 0.14 0.35 0.23 0.04 ] T[ 0.00 0.07 0.03 0.01 0.00 0.01 0.06 0.25 0.14 0.12 0.04 ] G[ 0.00 0.23 0.00 0.20 0.04 0.02 0.54 0.08 0.25 0.24 0.06 ] A[ 0.01 0.66 0.97 0.67 0.03 0.05 0.33 0.53 0.26 0.41 0.86 ] C[ 0.99 0.04 0.00 0.13 0.94 0.92 0.07 0.14 0.35 0.23 0.04 ] T[ 0.00 0.07 0.03 0.01 0.00 0.01 0.06 0.25 0.14 0.12 0.04 ] G[ 0.00 0.23 0.00 0.20 0.04 0.02 0.54 0.08 0.25 0.24 0.06 ] What is the problem??? Why the scrambling do not work after the first time, and all the list filled with the same matrix?!

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• Go - Using a container/heap to implement a priority queue

  - by Seth Hoenig

  In the big picture, I'm trying to implement Dijkstra's algorithm using a priority queue. According to members of golang-nuts, the idiomatic way to do this in Go is to use the heap interface with a custom underlying data structure. So I have created Node.go and PQueue.go like so: //Node.go package pqueue type Node struct { row int col int myVal int sumVal int } func (n *Node) Init(r, c, mv, sv int) { n.row = r n.col = c n.myVal = mv n.sumVal = sv } func (n *Node) Equals(o *Node) bool { return n.row == o.row && n.col == o.col } And PQueue.go: // PQueue.go package pqueue import "container/vector" import "container/heap" type PQueue struct { data vector.Vector size int } func (pq *PQueue) Init() { heap.Init(pq) } func (pq *PQueue) IsEmpty() bool { return pq.size == 0 } func (pq *PQueue) Push(i interface{}) { heap.Push(pq, i) pq.size++ } func (pq *PQueue) Pop() interface{} { pq.size-- return heap.Pop(pq) } func (pq *PQueue) Len() int { return pq.size } func (pq *PQueue) Less(i, j int) bool { I := pq.data.At(i).(Node) J := pq.data.At(j).(Node) return (I.sumVal + I.myVal) < (J.sumVal + J.myVal) } func (pq *PQueue) Swap(i, j int) { temp := pq.data.At(i).(Node) pq.data.Set(i, pq.data.At(j).(Node)) pq.data.Set(j, temp) } And main.go: (the action is in SolveMatrix) // Euler 81 package main import "fmt" import "io/ioutil" import "strings" import "strconv" import "./pqueue" const MATSIZE = 5 const MATNAME = "matrix_small.txt" func main() { var matrix [MATSIZE][MATSIZE]int contents, err := ioutil.ReadFile(MATNAME) if err != nil { panic("FILE IO ERROR!") } inFileStr := string(contents) byrows := strings.Split(inFileStr, "\n", -1) for row := 0; row < MATSIZE; row++ { byrows[row] = (byrows[row])[0 : len(byrows[row])-1] bycols := strings.Split(byrows[row], ",", -1) for col := 0; col < MATSIZE; col++ { matrix[row][col], _ = strconv.Atoi(bycols[col]) } } PrintMatrix(matrix) sum, len := SolveMatrix(matrix) fmt.Printf("len: %d, sum: %d\n", len, sum) } func PrintMatrix(mat [MATSIZE][MATSIZE]int) { for r := 0; r < MATSIZE; r++ { for c := 0; c < MATSIZE; c++ { fmt.Printf("%d ", mat[r][c]) } fmt.Print("\n") } } func SolveMatrix(mat [MATSIZE][MATSIZE]int) (int, int) { var PQ pqueue.PQueue var firstNode pqueue.Node var endNode pqueue.Node msm1 := MATSIZE - 1 firstNode.Init(0, 0, mat[0][0], 0) endNode.Init(msm1, msm1, mat[msm1][msm1], 0) if PQ.IsEmpty() { // make compiler stfu about unused variable fmt.Print("empty") } PQ.Push(firstNode) // problem return 0, 0 } The problem is, upon compiling i get the error message: [~/Code/Euler/81] $ make 6g -o pqueue.6 Node.go PQueue.go 6g main.go main.go:58: implicit assignment of unexported field 'row' of pqueue.Node in function argument make: *** [all] Error 1 And commenting out the line PQ.Push(firstNode) does satisfy the compiler. But I don't understand why I'm getting the error message in the first place. Push doesn't modify the argument in any way.

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• I can't compile android projetc wiht JNI code

  - by lobi

  I'm trying to build simple android app with some JNI code. When I press build project in eclipse I get this error: Description Resource Path Location Type fatal error: algorithm: No such file or directory Tracker line 56, external location: /home/slani/code/OpenCV-2.4.6-android-sdk/sdk/native/jni/include/opencv2/core/core.hpp C/C++ Problem make: *** [obj/local/armeabi/objs/detect_jni/detect_jni.o] Error 1 Tracker C/C++ Problem Line 56 in core.hpp contains the relevant include. This is my Android.mk file jni folder: LOCAL_PATH := $(call my-dir) include $(CLEAR_VARS) include /home/slani/code/OpenCV-2.4.6-android-sdk/sdk/native/jni/OpenCV.mk LOCAL_MODULE := detect_jni LOCAL_SRC_FILES := detect_jni.cpp include $(BUILD_SHARED_LIBRARY) This is my Aplication.mk file in jni folder: APP_STL := gnustl_static APP_CPPFLAGS := -frtti -fexceptions APP_ABI := armeabi-v7a APP_PLATFORM := all This is my .cpp file: #include <jni.h> #include <opencv/cv.h> #include <opencv2/imgproc/imgproc.hpp> #include <opencv2/features2d/features2d.hpp> using namespace cv; extern "C"{ JNIEXPORT void JNICALL Java_com_slani_tracker_OpenCamera_findObject((JNIEnv *env, jlong addRgba, jlong addHsv); JNIEXPORT void JNICALL Java_com_slani_tracker_OpenCamera_findObject((JNIEnv *env, jlong addRgba, jlong addHsv) { Mat& rgba = *(Mat*)addRgba; Mat& hsv = *(Mat*)addHsv; cvtColor(rgba, hsv,CV_RGBA2HSV); } } Can someone please help me? What could be causing this problem? Thanks

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• Problem with Silverlight/wpf in scrolling html div.

  - by Mat

  Hi all, I have a Silverlight object sitting at the bottom of a scrollable div. This object is submitted to a wcf backend via a javascript button. The problem is, as the silverlight is at the bottom of the scrollable div it is not viewable until you have scrolled down. This is generating an error when the javascript button is clicked ( if i havent scrolled down ) awfully strange, or am i just an idiot :/ if i scroll down so the silverlight object, so it is in view it submits just fine. The error i got is an alert type error which says : The parameter value must be greater than zero. Parameter name: pixelWidth This seems to be returned from the wcf service. What could cause this? Can anyone help me rectify. Kind regards Mat.

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• Tomcat 6 Realm Config with Windows AD

  - by mat

  We have Tomcat 6 connecting to a Win2k3 Server running AD. The realm is configured as such <Realm className="org.apache.catalina.realm.JNDIRealm" debug="99" referrals="follow" connectionURL="<url>" connectionName="CN=Query Account,OU=Service Accounts,DC=company,DC=com" connectionPassword="<pwd>" userBase="OU=Users,DC=company,DC=com" userSubtree="true" userSearch="(sAMAccountName={0})" userRoleName="member" roleBase="OU=Security Groups,DC=company,DC=com" roleName="cn" roleSearch="(member={0})" roleSubtree="true"/> Our groups in AD are such Security Groups (OU) IT (OU) IT Support (OU) Support Staff (CN) The LDAP security works if in the web.xml, I speficy Support Staff. i.e works for Common names. We want ANY user under Security Groups OU to have access to the application and not just the CN. Tomcat does not search OU's and it just searches CN's in our case. How do we configure our settings so we can do OU level authorization and not just CN level ? thanks Mat

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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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• 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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• NoSQL Memcached API for MySQL: Latest Updates

  - by Mat Keep

  With data volumes exploding, it is vital to be able to ingest and query data at high speed. For this reason, MySQL has implemented NoSQL interfaces directly to the InnoDB and MySQL Cluster (NDB) storage engines, which bypass the SQL layer completely. Without SQL parsing and optimization, Key-Value data can be written directly to MySQL tables up to 9x faster, while maintaining ACID guarantees. In addition, users can continue to run complex queries with SQL across the same data set, providing real-time analytics to the business or anonymizing sensitive data before loading to big data platforms such as Hadoop, while still maintaining all of the advantages of their existing relational database infrastructure. This and more is discussed in the latest Guide to MySQL and NoSQL where you can learn more about using the APIs to scale new generations of web, cloud, mobile and social applications on the world's most widely deployed open source database The native Memcached API is part of the MySQL 5.6 Release Candidate, and is already available in the GA release of MySQL Cluster. By using the ubiquitous Memcached API for writing and reading data, developers can preserve their investments in Memcached infrastructure by re-using existing Memcached clients, while also eliminating the need for application changes. Speed, when combined with flexibility, is essential in the world of growing data volumes and variability. Complementing NoSQL access, support for on-line DDL (Data Definition Language) operations in MySQL 5.6 and MySQL Cluster enables DevOps teams to dynamically update their database schema to accommodate rapidly changing requirements, such as the need to capture additional data generated by their applications. These changes can be made without database downtime. Using the Memcached interface, developers do not need to define a schema at all when using MySQL Cluster. Lets look a little more closely at the Memcached implementations for both InnoDB and MySQL Cluster. Memcached Implementation for InnoDB The Memcached API for InnoDB is previewed as part of the MySQL 5.6 Release Candidate. As illustrated in the following figure, Memcached for InnoDB is implemented via a Memcached daemon plug-in to the mysqld process, with the Memcached protocol mapped to the native InnoDB API. Figure 1: Memcached API Implementation for InnoDB With the Memcached daemon running in the same process space, users get very low latency access to their data while also leveraging the scalability enhancements delivered with InnoDB and a simple deployment and management model. Multiple web / application servers can remotely access the Memcached / InnoDB server to get direct access to a shared data set. With simultaneous SQL access, users can maintain all the advanced functionality offered by InnoDB including support for Foreign Keys, XA transactions and complex JOIN operations. Benchmarks demonstrate that the NoSQL Memcached API for InnoDB delivers up to 9x higher performance than the SQL interface when inserting new key/value pairs, with a single low-end commodity server supporting nearly 70,000 Transactions per Second. Figure 2: Over 9x Faster INSERT Operations The delivered performance demonstrates MySQL with the native Memcached NoSQL interface is well suited for high-speed inserts with the added assurance of transactional guarantees. You can check out the latest Memcached / InnoDB developments and benchmarks here You can learn how to configure the Memcached API for InnoDB here Memcached Implementation for MySQL Cluster Memcached API support for MySQL Cluster was introduced with General Availability (GA) of the 7.2 release, and joins an extensive range of NoSQL interfaces that are already available for MySQL Cluster Like Memcached, MySQL Cluster provides a distributed hash table with in-memory performance. MySQL Cluster extends Memcached functionality by adding support for write-intensive workloads, a full relational model with ACID compliance (including persistence), rich query support, auto-sharding and 99.999% availability, with extensive management and monitoring capabilities. All writes are committed directly to MySQL Cluster, eliminating cache invalidation and the overhead of data consistency checking to ensure complete synchronization between the database and cache. Figure 3: Memcached API Implementation with MySQL Cluster Implementation is simple: 1. The application sends reads and writes to the Memcached process (using the standard Memcached API). 2. This invokes the Memcached Driver for NDB (which is part of the same process) 3. The NDB API is called, providing for very quick access to the data held in MySQL Cluster’s data nodes. The solution has been designed to be very flexible, allowing the application architect to find a configuration that best fits their needs. It is possible to co-locate the Memcached API in either the data nodes or application nodes, or alternatively within a dedicated Memcached layer. The benefit of this flexible approach to deployment is that users can configure behavior on a per-key-prefix basis (through tables in MySQL Cluster) and the application doesn’t have to care – it just uses the Memcached API and relies on the software to store data in the right place(s) and to keep everything synchronized. Using Memcached for Schema-less Data By default, every Key / Value is written to the same table with each Key / Value pair stored in a single row – thus allowing schema-less data storage. Alternatively, the developer can define a key-prefix so that each value is linked to a pre-defined column in a specific table. Of course if the application needs to access the same data through SQL then developers can map key prefixes to existing table columns, enabling Memcached access to schema-structured data already stored in MySQL Cluster. Conclusion Download the Guide to MySQL and NoSQL to learn more about NoSQL APIs and how you can use them to scale new generations of web, cloud, mobile and social applications on the world's most widely deployed open source database See how to build a social app with MySQL Cluster and the Memcached API from our on-demand webinar or take a look at the docs Don't hesitate to use the comments section below for any questions you may have 

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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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• Compound assignment operators in Python's Numpy library

  - by Leonard

  The "vectorizing" of fancy indexing by Python's numpy library sometimes gives unexpected results. For example: import numpy a = numpy.zeros((1000,4), dtype='uint32') b = numpy.zeros((1000,4), dtype='uint32') i = numpy.random.random_integers(0,999,1000) j = numpy.random.random_integers(0,3,1000) a[i,j] += 1 for k in xrange(1000): b[i[k],j[k]] += 1 Gives different results in the arrays 'a' and 'b' (i.e. the appearance of tuple (i,j) appears as 1 in 'a' regardless of repeats, whereas repeats are counted in 'b'). This is easily verified as follows: numpy.sum(a) 883 numpy.sum(b) 1000 It is also notable that the fancy indexing version is almost two orders of magnitude faster than the for loop. My question is: "Is there an efficient way for numpy to compute the repeat counts as implemented using the for loop in the provided example?"

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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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• How should I work out VAT (UK tax) in my eCommerce site?

  - by Leonard Challis

  We have an ecommerce system in place. The sales actually go through Sage, so we have an export script from our system that uses a third-party Sage Importer program. With a new version of this importer, values are checked more thoroughly. We are getting 1 pence discrepancies because of the way rounding works - our system has always held prices and worked to 4 decimal places. In the checkout the totals would be worked out first, then the rounding to 2 decimal places. The importer does rounding first, though. So, for instance: Our way: Product 1: £13.4561 Qty: 2 Total inc VAT = £32.29 (to 2dp) Importer way: Our way: Product 1: £13.4561 Qty: 2 Total inc VAT = £32.30 (to 2dp) Management are reluctant to lose the 4dp but the developers of the Sage importer have said that this is correct and makes sense -- you woudn't sell a product for £13.4561 in a shop, nor would you charge someone tax at 4 decimal places. I contacted the HMRC and the operator didn't really give me much to go on, telling me a technician would phone back, to which they haven't and I'm still waiting after almost a week and numerous follow-up calls. I did find a PDF on the HMRC's web site, but this did about us much to confuse me as it did to answer my questions. I see that they're happy for people to round up or down, as long it is consistent, but I can't tell whether it should be done on a line by line basis or on the end total of the order. We are now in the position where we need to decide whether it's worth us doing one of the following, or something completely different. Please advise with any experience or information I can read. Change all products on the site to use 2dp Keep 4dp but round each line in the order to 2dp before working out tax Keep it as it is and "fudge" the values at the export script (i.e. make that values correct by adding or subtracting 1p and changing the shipping cost to make the totals still work out) Any thoughts?

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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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• Just graduated from the finest graduates of the NeoSmart Technologies Institute of BCD Learning.

  - by Leonard Mwangi

  My laptop housing my life in entirety decided to go south this last weekend, cant blame it because I wanted it to do things that not even normal people :)  but it corrupted and could not get it going no matter what I tried. Imagining what I would loose (my POC's, Couple of VM's and lots and lots of documentation) pushed me to try anything short of reinstall. After toiling for about an hour looking for solution, I ended up at  http://neosmart.net/wiki/display/EBCD/Recovering+the+Vista+Bootloader+from+the+DVD where the last solution is the one that worked for me. I am glad to be functional again :) Thanks NeoSmart guys

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• SSIS ForEachLoop Container

  - by Leonard Mwangi

  I recently had a client request to create an SSIS package that would loop through a set of data in SQL tables to allow them to complete their data transformation processes. Knowing that Integration Services does have ForEachLoop Container, I knew the task would be easy but the moment I jumped into it I figured there was no straight forward way to accomplish the task since for each didn’t really have a loop through the table enumerator. With the capabilities of integration Services, I was still confident that it was possible it was just a matter of creativity to get it done. I set out to discover what different ForEach Loop Editor Enumerators did and settled with Variable Enumerator.  Here is how I accomplished the task. 1.       Drop your ForEach Loop Container in your WorkArea. 2.       Create a few SSIS Variable that will contain the data. Notice I have assigned MyID_ID variable a value of “TEST’ which is not evaluated either. This variable will be assigned data from the database hence allowing us to loop. 3.       In the ForEach Loop Editor’s Collection select Variable Enumerator 4.       Once this is all set, we need a mechanism to grab the data from the SQL Table and assigning it to the variable. Fig: Select Top 1 record Fig: Assign Top 1 record to the variable 5.       Now all that’s required is a house cleaning process that will update the table that you are looping so that you can be able to grab the next record   A look of the complete package

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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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• adobe-flash-properties-gtk on Saucy 13.10

  - by leonard vertighel

  How can I install adobe-flash-properties-gtk on the new Ubuntu 13.10 Saucy? It was present since last version Raring 13.04. is there another way to control the sites allowed to use the webcam? The "partner" repositories are enabled. Cheers PS: How can I install adobe-flash-properties-gtk on the new Ubuntu 13.10 Saucy? It was present since last version Raring 13.04. is there another way to control the sites allowed to use the webcam? The "partner" repositories are enabled. Cheers PS: instructions like this one "Can't install adobe-flash-properties-gtk" stop at Raring 13.04.

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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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