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  • The All New Hotmail Looks Very Impressive [Video Tour]

    - by Gopinath
    With loads of new new features being introduced into GMail every now and then, Microsoft can’t sit and relax any more. Microsoft realized this and worked hard to introduce really impressive features in upcoming version of Windows Live Hotmail that was previewed couple of days ago. Most of the new features announced in the upcoming version are focusing on the important need of email users – de-clutter the mail box and effectively manage email over load easily. Here is the list highlight of new features New Features Sweep away clutter – This is the most impressive in the set of new features. It allows you to manage email overload. If you’ve subscribed to a newsletter but decided to not to allow it into your inbox, you can activate the sweep feature to move all the messages of the newsletter in to a folder other than your inbox. This may sound similar to filters option in GMail but the workflow is very easy in Hotmail. Quickly find message – Easy to use options are provided to see mails in separate views likes mails from contacts, social networking mail, mails from e-mail subscription services, etc. Now it’s easy to prioritize email checking like how you wish to. I prefer to check mails from my contacts first, then social networking messages and then the newsletter subscriptions. Improved spam detection – The span detection rules are tightened for better spam protection and also hotmail learns from user actions to effectively catch spam No more mail box storage restrictions – With a smart decision of Microsoft, users  no longer need to worry about the storage restrictions of their mail box – large attachments of hotmail can be stored in Windows Live SkyDrive. With Hotmail, we’ve combined the simplicity of sending photos through email with the power of Windows Live SkyDrive so that you can send up to 200 photos, each up to 50 MB in size, all in a single email. You can send all your vacation photos at once without worrying about attachment limits, Excellent Integration With Office Web Apps -  View and editing of office documents attached to the emails are made very easy by integrating Office Web Apps with Hotmail. When you receive a document/presentation/spreadsheet in hotmail, you can view it, edit it, save it or even you can send the modified document to original sender – all these without leaving hotmail. Inline viewing options for Photos, Videos, Social Network Messages – You can view photos embedded in the mail as slideshows(with the help of SilverLight), YouTube  & Hulu videos can be played inline  and track shipping notifications. Threaded conversations – emails in Hotmail are grouped just like it happens in GMail Others - enhanced account protection, full-session SSL, multiple email accounts, subfolders, contact management Video Tour Of New Features Here is an impressive video tour of new Hotmail features. When are these new features coming to Hotmail? Majority of the new features announced today are rolled out in coming weeks gradually to all the users. But advanced features like Office Integration with Hotmail is expected to take couple of months for general availability. Will You Switch back to Hotmail? Will these features lure GMail/Yahoo users to switch back to Hotmail? May be not immediately but these features may hold the existing users from leaving Hotmail. I used Hotmail, in the pre GMail era and now I use  Hotmail id only to sign-in to Microsoft websites that requites Hotmail authentication. It’s been years since I composed a new email in Hotmail. Even though the new features announced by Hotmail are very impressive, I like the way how GMail rapidly brings new features at regular intervals. If Hotmail also keeps innovating with new features at regular intervals, then there are good chances for it’s old users to return home. Join us on Facebook to read all our stories right inside your Facebook news feed.

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  • Rewriting Apache URLs to use only paths and set response headers

    - by jabley
    I have apache httpd in front of an application running in Tomcat. The application exposes URLs of the form: /path/to/images?id={an-image-id} The entities returned by such URLs are images (even though URIs are opaque, I find human-friendly ones are easier to work with!). The application does not set caching directives on the image response, so I've added that via Apache. # LocationMatch to set caching directives on image responses <LocationMatch "^/path/to/images$"> # Can't have Set-Cookie on response, otherwise the downstream caching proxy # won't cache! Header unset Set-Cookie # Mark the response as cacheable. Header append Cache-Control "max-age=8640000" </LocationMatch> Note that I can't use ExpiresByType since not all images served by the app have versioned URIs. I know that ones served by the /path/to/images resource handler are versioned URIs though, which don't perform any sort of content negotiation, and thus are ripe for Far Future Expires management. This is working well for us. Now a requirement has come up to put something else in front of the app (in this case, Amazon CloudFront) to further distribute and cache some of the content. Amazon CloudFront will not pass query string parameters through to my origin server. I thought I would be able to work around this, by changing my apache config appropriately: # Rewrite to map new Amazon CloudFront friendly URIs to the application resources RewriteRule ^/new/path/to/images/([0-9]+) /path/to/images?id=$1 [PT] # LocationMatch to set caching directives on image responses <LocationMatch "^/path/to/images$"> # Can't have Set-Cookie on response, otherwise the downstream caching proxy # won't cache! Header unset Set-Cookie # Mark the response as cacheable. Header append Cache-Control "max-age=8640000" </LocationMatch> This works fine in terms of serving the content, but there are no longer caching directives with the response. I've tried playing around with [PT], [P] for the RewriteRule, and adding a new LocationMatch directive: # Rewrite to map new Amazon CloudFront friendly URIs to the application resources # /new/path/to/images/12345 -> /path/to/images?id=12345 RewriteRule ^/new/path/to/images/([0-9]+) /path/to/images?id=$1 [PT] # LocationMatch to set caching directives on image responses <LocationMatch "^/path/to/images$"> # Can't have Set-Cookie on response, otherwise the downstream caching proxy # won't cache! Header unset Set-Cookie # Mark the response as cacheable. Header append Cache-Control "max-age=8640000" </LocationMatch> <LocationMatch "^/new/path/to/images/"> # Can't have Set-Cookie on response, otherwise the downstream caching proxy # won't cache! Header unset Set-Cookie # Mark the response as cacheable. Header append Cache-Control "max-age=8640000" </LocationMatch> Unfortunately, I'm still unable to get the Cache-Control header added to the response with the new URL format. Please point out what I'm missing to get /new/path/to/images/12345 returning a 200 response with a Cache-Control: max-age=8640000 header. Pointers as to how to debug apache like this would be appreciated as well!

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  • SVG rotation animation having problems on chrome for jelly bean, is there a workaround?

    - by Metalskin
    I've got a strange problem with chrome on jellybean running svg animations triggered from javascript. This JSFiddle example works fine on chrome and firefox on linux, but when I run it on android with chrome I get the final step of the animation painted at the beginning of the animation. I've tried this on both an Nexus 7 and Transformer Prime, they both have the problem. I've tested using firefox on the android devices and the problem doesn't exist. So I'm presuming that it's a defect with chrome. However I've seen other animations using svg that do not have this problem in chrome on jellybean. Is anyone aware of a way to get around this problem, or is there something that I'm doing in my animation/js that is a possible cause of the problem? I've now created a bug report at code.google.com, however I still need a workaround, if anyone can help me (or in case I'm doing something stupid). I've now discovered that this is reproducible on chrome for linux (and I suspect windows). If you click on the button to start the animation before the previous animation has completed then the problem occurs. In this case the hand is drawn at the end of the 45 degree sweep before it starts the sweep. I now suspect that I should be calling something to stop the animation before I change the animation. Anyway, hopefully someone can resolve this problem.

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  • JMeter Stress testing

    - by mcondiff
    MAMP server hosting a Joomla instance. I'd like to hear the community's thoughts on the best way to stress test the server and find it's breaking point on concurrent users etc. Currently I have setup a test plan which I have going to the home page, grabbing the index.php, css, js and all images and have run tests on 1 to 100 users and a varying number of loops. What I'd like to know is how do I determine at what number of concurrent requests or looping requests is a good way to gauge if my server can handle the proposed increase in traffic? What is a good KB/sec, Throughput, Average, Max, Min via the Aggregate Report and at what number of threads/loops etc? I have googled and have not found immediate answers to these questions and thought to come here. More or less I have just used this http://jakarta.apache.org/jmeter/usermanual/jmeter_proxy_step_by_step.pdf to guide me and then I have been winging it in terms of Thread and Loop numbers. Any light shed on these subject would be much appreciated.

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  • JBoss Seam project can not be run/deployed

    - by user1494328
    I created sample application in Seam framework (Seam Web Project) and JBoss Server 7.1. When I try run application, console dislays: 23:29:35,419 ERROR [org.jboss.msc.service.fail] (MSC service thread 1-3) MSC00001: Failed to start service jboss.deployment.unit."secoundProject-ds.xml".PARSE: org.jboss.msc.service.StartException in service jboss.deployment.unit."secoundProject-ds.xml".PARSE: Failed to process phase PARSE of deployment "secoundProject-ds.xml" at org.jboss.as.server.deployment.DeploymentUnitPhaseService.start(DeploymentUnitPhaseService.java:119) [jboss-as-server-7.1.1.Final.jar:7.1.1.Final] at org.jboss.msc.service.ServiceControllerImpl$StartTask.startService(ServiceControllerImpl.java:1811) [jboss-msc-1.0.2.GA.jar:1.0.2.GA] at org.jboss.msc.service.ServiceControllerImpl$StartTask.run(ServiceControllerImpl.java:1746) [jboss-msc-1.0.2.GA.jar:1.0.2.GA] at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886) [rt.jar:1.6.0_24] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908) [rt.jar:1.6.0_24] at java.lang.Thread.run(Thread.java:662) [rt.jar:1.6.0_24] Caused by: org.jboss.as.server.deployment.DeploymentUnitProcessingException: IJ010061: Unexpected element: local-tx-datasource at org.jboss.as.connector.deployers.processors.DsXmlDeploymentParsingProcessor.deploy(DsXmlDeploymentParsingProcessor.java:85) at org.jboss.as.server.deployment.DeploymentUnitPhaseService.start(DeploymentUnitPhaseService.java:113) [jboss-as-server-7.1.1.Final.jar:7.1.1.Final] ... 5 more Caused by: org.jboss.jca.common.metadata.ParserException: IJ010061: Unexpected element: local-tx-datasource at org.jboss.jca.common.metadata.ds.DsParser.parseDataSources(DsParser.java:183) at org.jboss.jca.common.metadata.ds.DsParser.parse(DsParser.java:119) at org.jboss.jca.common.metadata.ds.DsParser.parse(DsParser.java:82) at org.jboss.as.connector.deployers.processors.DsXmlDeploymentParsingProcessor.deploy(DsXmlDeploymentParsingProcessor.java:80) ... 6 more 23:29:35,452 INFO [org.jboss.as.server.deployment] (MSC service thread 1-4) JBAS015877: Stopped deployment secoundProject-ds.xml in 1ms 23:29:35,455 INFO [org.jboss.as.server] (DeploymentScanner-threads - 2) JBAS015863: Replacement of deployment "secoundProject-ds.xml" by deployment "secoundProject-ds.xml" was rolled back with failure message {"JBAS014671: Failed services" => {"jboss.deployment.unit.\"secoundProject-ds.xml\".PARSE" => "org.jboss.msc.service.StartException in service jboss.deployment.unit.\"secoundProject-ds.xml\".PARSE: Failed to process phase PARSE of deployment \"secoundProject-ds.xml\""}} 23:29:35,457 INFO [org.jboss.as.server.deployment] (MSC service thread 1-1) JBAS015876: Starting deployment of "secoundProject-ds.xml" 23:29:35,920 ERROR [org.jboss.msc.service.fail] (MSC service thread 1-1) MSC00001: Failed to start service jboss.deployment.unit."secoundProject-ds.xml".PARSE: org.jboss.msc.service.StartException in service jboss.deployment.unit."secoundProject-ds.xml".PARSE: Failed to process phase PARSE of deployment "secoundProject-ds.xml" at org.jboss.as.server.deployment.DeploymentUnitPhaseService.start(DeploymentUnitPhaseService.java:119) [jboss-as-server-7.1.1.Final.jar:7.1.1.Final] at org.jboss.msc.service.ServiceControllerImpl$StartTask.startService(ServiceControllerImpl.java:1811) [jboss-msc-1.0.2.GA.jar:1.0.2.GA] at org.jboss.msc.service.ServiceControllerImpl$StartTask.run(ServiceControllerImpl.java:1746) [jboss-msc-1.0.2.GA.jar:1.0.2.GA] at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886) [rt.jar:1.6.0_24] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908) [rt.jar:1.6.0_24] at java.lang.Thread.run(Thread.java:662) [rt.jar:1.6.0_24] Caused by: org.jboss.as.server.deployment.DeploymentUnitProcessingException: IJ010061: Unexpected element: local-tx-datasource at org.jboss.as.connector.deployers.processors.DsXmlDeploymentParsingProcessor.deploy(DsXmlDeploymentParsingProcessor.java:85) at org.jboss.as.server.deployment.DeploymentUnitPhaseService.start(DeploymentUnitPhaseService.java:113) [jboss-as-server-7.1.1.Final.jar:7.1.1.Final] ... 5 more Caused by: org.jboss.jca.common.metadata.ParserException: IJ010061: Unexpected element: local-tx-datasource at org.jboss.jca.common.metadata.ds.DsParser.parseDataSources(DsParser.java:183) at org.jboss.jca.common.metadata.ds.DsParser.parse(DsParser.java:119) at org.jboss.jca.common.metadata.ds.DsParser.parse(DsParser.java:82) at org.jboss.as.connector.deployers.processors.DsXmlDeploymentParsingProcessor.deploy(DsXmlDeploymentParsingProcessor.java:80) ... 6 more 23:29:35,952 INFO [org.jboss.as.controller] (DeploymentScanner-threads - 2) JBAS014774: Service status report JBAS014777: Services which failed to start: service jboss.deployment.unit."secoundProject-ds.xml".PARSE: org.jboss.msc.service.StartException in service jboss.deployment.unit."secoundProject-ds.xml".PARSE: Failed to process phase PARSE of deployment "secoundProject-ds.xml" My secoundProject-ds.xml: <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE datasources PUBLIC "-//JBoss//DTD JBOSS JCA Config 1.5//EN" "http://www.jboss.org/j2ee/dtd/jboss-ds_1_5.dtd"> <datasources> <local-tx-datasource> <jndi-name>secoundProjectDatasource</jndi-name> <use-java-context>true</use-java-context> <connection-url>jdbc:mysql://localhost:3306/database</connection-url> <driver-class>com.mysql.jdbc.Driver</driver-class> <user-name>root</user-name> <password></password> </local-tx-datasource> </datasources> When I comment tags errors disappear, but application is disabled in browser (The requested resource (/secoundProject/) is not available.). What should I do to fix this problem?

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  • java.lang.OutOfMemoryError on ec2 machine

    - by vinchan
    I have a java app on a large instance that will spawn up to 800 threads. I can run the application fine as user "root" but not as another user which I created. I get the deadly. java.lang.OutOfMemoryError: unable to create new native thread at java.lang.Thread.start0(Native Method) at java.lang.Thread.start(Thread.java:657) at java.util.concurrent.ThreadPoolExecutor.addWorker(ThreadPoolExecutor.java:943) at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1325) nightmare. I have tried increasing the stack size already in limits.conf to no avail. Please, help me out. What is different here for the root and other user?

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  • What would be better in my case - apache, nginx or lighttpd ?

    - by The Devil
    Hey everybody, I'm writing a php site that's expected to get about 200-300 concurrent users browsing it. When initializing the application will load about 30 php classes, some 10 maybe 15 images and a couple of css files. So my question is what else can I do (except optimizing my code and using apc/eaccelerator for php) to get as close as possible to those numbers of concurrent users ? Currently we haven't chosen a server for the site to be hosted on but most probably it'll be a VPS Dual core + 2 or maybe 4gb ram. Is it possible for such a server to handle that load ? Also how could I test it myself and be sure that it'll be able to handle it ? Thanks in advance, Me

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  • how limit the number of open TCP streams from same IP to a local port?

    - by JMW
    Hi, i would like to limit the number of concurrent open TCP streams from the the same IP to the server's (local) port. Let's say 4 concurrent conncetions. How can this be done with ip tables? the closest thing, that i've found was: In Apache, is there a way to limit the number of new connections per second/hour/day? iptables -A INPUT -p tcp --dport 80 -i eth0 -m state --state NEW -m recent --set iptables -A INPUT -p tcp --dport 80 -i eth0 -m state --state NEW -m recent --update --seconds 86400 --hitcount 100 -j REJECT But this limitation just messures the number of new connections over the time. This might be good for controlling HTTP traffic. But this is not a good solution for me, since my TCP streams usually have a lifetime between 5 minutes and 2 hours. thanks a lot in advance for any reply :)

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  • AB failed requests - What can I do about them?

    - by matthewsteiner
    So, in the past I've never had any problems with this app. All benchmarks had 100% success rate. Yesterday I set up nginx to server static content and pass on other requests to apache. Now, if I have 1 concurrent user (-c 1) then everything is fine. But it seems the more concurrent users I have, the more failed requests I get. Not a lot, but maybe about 10 or 15 out of 350. They're "length", whatever that means. Visiting the website with a browser, I don't have any problems at all. How can I find out the cause of these failed requests?

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  • TCP and fair bandwidth sharing

    - by lxgr
    The congestion control algorithm(s) of TCP seem to distribute the available bandwidth fairly between individual TCP flows. Is there some way to enable (or more precisely, enforce) fair bandwidth sharing on a per-host instead of a per-flow basis on a router? There should not be an (easy) way for a user to gain a disproportional bandwidth share by using multiple concurrent TCP flows (the way some download managers and most P2P clients do). I'm currently running a DD-WRT router to share a residential DSL line, and currently it's possible to (inadvertently or maliciously) hog most of the bandwidth by using multiple concurrent connections, which affecty VoIP conversations badly. I've played with the QoS settings a bit, but I'm not sure how to enable fair bandwidth sharing on a per-IP basis (per-service is not an option, as most of the flows are HTTP).

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  • Refresh QTextEdit in PyQt

    - by Mark Underwood
    Hi all, Im writing a PyQt app that takes some input in one widget, and then processes some text files. What ive got at the moment is when the user clicks the "process" button a seperate window with a QTextEdit in it pops up, and ouputs some logging messages. On Mac OS X this window is refreshed automatically and you cna see the process. On Windows, the window reports (Not Responding) and then once all the proccessing is done, the log output is shown. Im assuming I need to refresh the window after each write into the log, and ive had a look around at using a timer. etc, but havnt had much luck in getting it working. Below is the source code. It has two files, GUI.py which does all the GUI stuff and MOVtoMXF that does all the processing. GUI.py import os import sys import MOVtoMXF from PyQt4.QtCore import * from PyQt4.QtGui import * class Form(QDialog): def process(self): path = str(self.pathBox.displayText()) if(path == ''): QMessageBox.warning(self, "Empty Path", "You didnt fill something out.") return xmlFile = str(self.xmlFileBox.displayText()) if(xmlFile == ''): QMessageBox.warning(self, "No XML file", "You didnt fill something.") return outFileName = str(self.outfileNameBox.displayText()) if(outFileName == ''): QMessageBox.warning(self, "No Output File", "You didnt do something") return print path + " " + xmlFile + " " + outFileName mov1 = MOVtoMXF.MOVtoMXF(path, xmlFile, outFileName, self.log) self.log.show() rc = mov1.ScanFile() if( rc < 0): print "something happened" #self.done(0) def __init__(self, parent=None): super(Form, self).__init__(parent) self.log = Log() self.pathLabel = QLabel("P2 Path:") self.pathBox = QLineEdit("") self.pathBrowseB = QPushButton("Browse") self.pathLayout = QHBoxLayout() self.pathLayout.addStretch() self.pathLayout.addWidget(self.pathLabel) self.pathLayout.addWidget(self.pathBox) self.pathLayout.addWidget(self.pathBrowseB) self.xmlLabel = QLabel("FCP XML File:") self.xmlFileBox = QLineEdit("") self.xmlFileBrowseB = QPushButton("Browse") self.xmlLayout = QHBoxLayout() self.xmlLayout.addStretch() self.xmlLayout.addWidget(self.xmlLabel) self.xmlLayout.addWidget(self.xmlFileBox) self.xmlLayout.addWidget(self.xmlFileBrowseB) self.outFileLabel = QLabel("Save to:") self.outfileNameBox = QLineEdit("") self.outputFileBrowseB = QPushButton("Browse") self.outputLayout = QHBoxLayout() self.outputLayout.addStretch() self.outputLayout.addWidget(self.outFileLabel) self.outputLayout.addWidget(self.outfileNameBox) self.outputLayout.addWidget(self.outputFileBrowseB) self.exitButton = QPushButton("Exit") self.processButton = QPushButton("Process") self.buttonLayout = QHBoxLayout() #self.buttonLayout.addStretch() self.buttonLayout.addWidget(self.exitButton) self.buttonLayout.addWidget(self.processButton) self.layout = QVBoxLayout() self.layout.addLayout(self.pathLayout) self.layout.addLayout(self.xmlLayout) self.layout.addLayout(self.outputLayout) self.layout.addLayout(self.buttonLayout) self.setLayout(self.layout) self.pathBox.setFocus() self.setWindowTitle("MOVtoMXF") self.connect(self.processButton, SIGNAL("clicked()"), self.process) self.connect(self.exitButton, SIGNAL("clicked()"), self, SLOT("reject()")) self.ConnectButtons() class Log(QTextEdit): def __init__(self, parent=None): super(Log, self).__init__(parent) self.timer = QTimer() self.connect(self.timer, SIGNAL("timeout()"), self.updateText()) self.timer.start(2000) def updateText(self): print "update Called" AND MOVtoMXF.py import os import sys import time import string import FileUtils import shutil import re class MOVtoMXF: #Class to do the MOVtoMXF stuff. def __init__(self, path, xmlFile, outputFile, edit): self.MXFdict = {} self.MOVDict = {} self.path = path self.xmlFile = xmlFile self.outputFile = outputFile self.outputDirectory = outputFile.rsplit('/',1) self.outputDirectory = self.outputDirectory[0] sys.stdout = OutLog( edit, sys.stdout) class OutLog(): def __init__(self, edit, out=None, color=None): """(edit, out=None, color=None) -> can write stdout, stderr to a QTextEdit. edit = QTextEdit out = alternate stream ( can be the original sys.stdout ) color = alternate color (i.e. color stderr a different color) """ self.edit = edit self.out = None self.color = color def write(self, m): if self.color: tc = self.edit.textColor() self.edit.setTextColor(self.color) #self.edit.moveCursor(QtGui.QTextCursor.End) self.edit.insertPlainText( m ) if self.color: self.edit.setTextColor(tc) if self.out: self.out.write(m) self.edit.show() If any other code is needed (i think this is all that is needed) then just let me know. Any Help would be great. Mark

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  • Can't run my servlet from tomcat server even though the classes are in package

    - by Mido
    Hi there, i am trying to get my servlet to run, i have been searching for 2 days and trying every possible solution and no luck. The servet class is in the appropriate folder (i.e under the package name). I also added the jar files needed in my servlet into lib folder. the web.xml file maps the url and defines the servlet. So i did everything in the documentation and wt people said in here and still getting this error : type Exception report message description The server encountered an internal error () that prevented it from fulfilling this request. exception javax.servlet.ServletException: Error instantiating servlet class assign1a.RPCServlet org.apache.catalina.valves.ErrorReportValve.invoke(ErrorReportValve.java:108) org.apache.catalina.valves.AccessLogValve.invoke(AccessLogValve.java:558) org.apache.catalina.connector.CoyoteAdapter.service(CoyoteAdapter.java:379) org.apache.coyote.http11.Http11AprProcessor.process(Http11AprProcessor.java:282) org.apache.coyote.http11.Http11AprProtocol$Http11ConnectionHandler.process(Http11AprProtocol.java:357) org.apache.tomcat.util.net.AprEndpoint$SocketProcessor.run(AprEndpoint.java:1687) java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886) java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908) java.lang.Thread.run(Thread.java:619) root cause java.lang.NoClassDefFoundError: assign1a/RPCServlet (wrong name: server/RPCServlet) java.lang.ClassLoader.defineClass1(Native Method) java.lang.ClassLoader.defineClassCond(ClassLoader.java:632) java.lang.ClassLoader.defineClass(ClassLoader.java:616) java.security.SecureClassLoader.defineClass(SecureClassLoader.java:141) org.apache.catalina.loader.WebappClassLoader.findClassInternal(WebappClassLoader.java:2820) org.apache.catalina.loader.WebappClassLoader.findClass(WebappClassLoader.java:1143) org.apache.catalina.loader.WebappClassLoader.loadClass(WebappClassLoader.java:1638) org.apache.catalina.loader.WebappClassLoader.loadClass(WebappClassLoader.java:1516) org.apache.catalina.valves.ErrorReportValve.invoke(ErrorReportValve.java:108) org.apache.catalina.valves.AccessLogValve.invoke(AccessLogValve.java:558) org.apache.catalina.connector.CoyoteAdapter.service(CoyoteAdapter.java:379) org.apache.coyote.http11.Http11AprProcessor.process(Http11AprProcessor.java:282) org.apache.coyote.http11.Http11AprProtocol$Http11ConnectionHandler.process(Http11AprProtocol.java:357) org.apache.tomcat.util.net.AprEndpoint$SocketProcessor.run(AprEndpoint.java:1687) java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886) java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908) java.lang.Thread.run(Thread.java:619) note The full stack trace of the root cause is available in the Apache Tomcat/7.0.5 logs. Also here is my servlet code : package assign1a; import java.io.IOException; import java.util.logging.Level; import java.util.logging.Logger; import javax.servlet.ServletException; import javax.servlet.http.HttpServlet; import javax.servlet.http.HttpServletRequest; import javax.servlet.http.HttpServletResponse; import lib.jsonrpc.RPCService; public class RPCServlet extends HttpServlet { /** * */ private static final long serialVersionUID = -5274024331393844879L; private static final Logger log = Logger.getLogger(RPCServlet.class.getName()); protected RPCService service = new ServiceImpl(); public void doGet(HttpServletRequest request, HttpServletResponse response) throws IOException, ServletException { response.setContentType("text/html"); response.getWriter().write("rpc service " + service.getServiceName() + " is running..."); } public void doPost(HttpServletRequest request, HttpServletResponse response) throws IOException, ServletException { try { service.dispatch(request, response); } catch (Throwable t) { log.log(Level.WARNING, t.getMessage(), t); } } } Please help me :) Thanks. EDIT: here are the contents of my web.xml file <web-app xmlns="http://java.sun.com/xml/ns/javaee" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://java.sun.com/xml/ns/javaee http://java.sun.com/xml/ns/javaee/web-app_3_0.xsd" version="3.0" metadata-complete="true"> <servlet> <servlet-name>jsonrpc</servlet-name> <servlet-class>assign1a.RPCServlet</servlet-class> </servlet> <servlet-mapping> <servlet-name>jsonrpc</servlet-name> <url-pattern>/rpc</url-pattern> </servlet-mapping> </web-app>

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  • clojure.algo.monad strange m-plus behaviour with parser-m - why is second m-plus evaluated?

    - by Mark Fisher
    I'm getting unexpected behaviour in some monads I'm writing. I've created a parser-m monad with (def parser-m (state-t maybe-m)) which is pretty much the example given everywhere (here, here and here) I'm using m-plus to act a kind of fall-through query mechanism, in my case, it first reads values from a cache (database), if that returns nil, the next method is to read from "live" (a REST call). However, the second value in the m-plus list is always called, even though its value is disgarded (if the cache hit was good) and the final return is that of the first monadic function. Here's a cutdown version of the issue i'm seeing, and some solutions I found, but I don't know why. My questions are: Is this expected behaviour or a bug in m-plus? i.e. will the 2nd method in a m-plus list always be evaluated if the first item returns a value? Minor in comparison to the above, but if i remove the call _ (fetch-state) from checker, when i evaluate that method, it prints out the messages for the functions the m-plus is calling (when i don't think it should). Is this also a bug? Here's a cut-down version of the code in question highlighting the problem. It simply checks key/value pairs passed in are same as the initial state values, and updates the state to mark what it actually ran. (ns monods.monad-test (:require [clojure.algo.monads :refer :all])) (def parser-m (state-t maybe-m)) (defn check-k-v [k v] (println "calling with k,v:" k v) (domonad parser-m [kv (fetch-val k) _ (do (println "k v kv (= kv v)" k v kv (= kv v)) (m-result 0)) :when (= kv v) _ (do (println "passed") (m-result 0)) _ (update-val :ran #(conj % (str "[" k " = " v "]"))) ] [k v])) (defn filler [] (println "filler called") (domonad parser-m [_ (fetch-state) _ (do (println "filling") (m-result 0)) :when nil] nil)) (def checker (domonad parser-m [_ (fetch-state) result (m-plus ;; (filler) ;; intitially commented out deliberately (check-k-v :a 1) (check-k-v :b 2) (check-k-v :c 3))] result)) (checker {:a 1 :b 2 :c 3 :ran []}) When I run this as is, the output is: > (checker {:a 1 :b 2 :c 3 :ran []}) calling with k,v: :a 1 calling with k,v: :b 2 calling with k,v: :c 3 k v kv (= kv v) :a 1 1 true passed k v kv (= kv v) :b 2 2 true passed [[:a 1] {:a 1, :b 2, :c 3, :ran ["[:a = 1]"]}] I don't expect the line k v kv (= kv v) :b 2 2 true to show at all. The first function to m-plus (as seen in the final output) is what is returned from it. Now, I've found if I pass a filler into m-plus that does nothing (i.e. uncomment the (filler) line) then the output is correct, the :b value isn't evaluated. If I don't have the filler method, and make the first method test fail (i.e. change it to (check-k-v :a 2) then again everything is good, I don't get a call to check :c, only a and b are tested. From my understanding of what the state-t maybe-m transformation is giving me, then the m-plus function should look like: (defn m-plus [left right] (fn [state] (if-let [result (left state)] result (right state)))) which would mean that right isn't called unless left returns nil/false. I'd be interested to know if my understanding is correct or not, and why I have to put the filler method in to stop the extra evaluation (whose effects I don't want to happen). Apologies for the long winded post!

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  • Why does this Java code not utilize all CPU cores?

    - by ReneS
    The attached simple Java code should load all available cpu core when starting it with the right parameters. So for instance, you start it with java VMTest 8 int 0 and it will start 8 threads that do nothing else than looping and adding 2 to an integer. Something that runs in registers and not even allocates new memory. The problem we are facing now is, that we do not get a 24 core machine loaded (AMD 2 sockets with 12 cores each), when running this simple program (with 24 threads of course). Similar things happen with 2 programs each 12 threads or smaller machines. So our suspicion is that the JVM (Sun JDK 6u20 on Linux x64) does not scale well. Did anyone see similar things or has the ability to run it and report whether or not it runs well on his/her machine (= 8 cores only please)? Ideas? I tried that on Amazon EC2 with 8 cores too, but the virtual machine seems to run different from a real box, so the loading behaves totally strange. package com.test; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.util.concurrent.Future; import java.util.concurrent.TimeUnit; public class VMTest { public class IntTask implements Runnable { @Override public void run() { int i = 0; while (true) { i = i + 2; } } } public class StringTask implements Runnable { @Override public void run() { int i = 0; String s; while (true) { i++; s = "s" + Integer.valueOf(i); } } } public class ArrayTask implements Runnable { private final int size; public ArrayTask(int size) { this.size = size; } @Override public void run() { int i = 0; String[] s; while (true) { i++; s = new String[size]; } } } public void doIt(String[] args) throws InterruptedException { final String command = args[1].trim(); ExecutorService executor = Executors.newFixedThreadPool(Integer.valueOf(args[0])); for (int i = 0; i < Integer.valueOf(args[0]); i++) { Runnable runnable = null; if (command.equalsIgnoreCase("int")) { runnable = new IntTask(); } else if (command.equalsIgnoreCase("string")) { runnable = new StringTask(); } Future<?> submit = executor.submit(runnable); } executor.awaitTermination(1, TimeUnit.HOURS); } public static void main(String[] args) throws InterruptedException { if (args.length < 3) { System.err.println("Usage: VMTest threadCount taskDef size"); System.err.println("threadCount: Number 1..n"); System.err.println("taskDef: int string array"); System.err.println("size: size of memory allocation for array, "); System.exit(-1); } new VMTest().doIt(args); } }

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  • SQL SERVER – Concurrency Basics – Guest Post by Vinod Kumar

    - by pinaldave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions from SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. Learning is always fun when it comes to SQL Server and learning the basics again can be more fun. I did write about Transaction Logs and recovery over my blogs and the concept of simplifying the basics is a challenge. In the real world we always see checks and queues for a process – say railway reservation, banks, customer supports etc there is a process of line and queue to facilitate everyone. Shorter the queue higher is the efficiency of system (a.k.a higher is the concurrency). Every database does implement this using checks like locking, blocking mechanisms and they implement the standards in a way to facilitate higher concurrency. In this post, let us talk about the topic of Concurrency and what are the various aspects that one needs to know about concurrency inside SQL Server. Let us learn the concepts as one-liners: Concurrency can be defined as the ability of multiple processes to access or change shared data at the same time. The greater the number of concurrent user processes that can be active without interfering with each other, the greater the concurrency of the database system. Concurrency is reduced when a process that is changing data prevents other processes from reading that data or when a process that is reading data prevents other processes from changing that data. Concurrency is also affected when multiple processes are attempting to change the same data simultaneously. Two approaches to managing concurrent data access: Optimistic Concurrency Model Pessimistic Concurrency Model Concurrency Models Pessimistic Concurrency Default behavior: acquire locks to block access to data that another process is using. Assumes that enough data modification operations are in the system that any given read operation is likely affected by a data modification made by another user (assumes conflicts will occur). Avoids conflicts by acquiring a lock on data being read so no other processes can modify that data. Also acquires locks on data being modified so no other processes can access the data for either reading or modifying. Readers block writer, writers block readers and writers. Optimistic Concurrency Assumes that there are sufficiently few conflicting data modification operations in the system that any single transaction is unlikely to modify data that another transaction is modifying. Default behavior of optimistic concurrency is to use row versioning to allow data readers to see the state of the data before the modification occurs. Older versions of the data are saved so a process reading data can see the data as it was when the process started reading and not affected by any changes being made to that data. Processes modifying the data is unaffected by processes reading the data because the reader is accessing a saved version of the data rows. Readers do not block writers and writers do not block readers, but, writers can and will block writers. Transaction Processing A transaction is the basic unit of work in SQL Server. Transaction consists of SQL commands that read and update the database but the update is not considered final until a COMMIT command is issued (at least for an explicit transaction: marked with a BEGIN TRAN and the end is marked by a COMMIT TRAN or ROLLBACK TRAN). Transactions must exhibit all the ACID properties of a transaction. ACID Properties Transaction processing must guarantee the consistency and recoverability of SQL Server databases. Ensures all transactions are performed as a single unit of work regardless of hardware or system failure. A – Atomicity C – Consistency I – Isolation D- Durability Atomicity: Each transaction is treated as all or nothing – it either commits or aborts. Consistency: ensures that a transaction won’t allow the system to arrive at an incorrect logical state – the data must always be logically correct.  Consistency is honored even in the event of a system failure. Isolation: separates concurrent transactions from the updates of other incomplete transactions. SQL Server accomplishes isolation among transactions by locking data or creating row versions. Durability: After a transaction commits, the durability property ensures that the effects of the transaction persist even if a system failure occurs. If a system failure occurs while a transaction is in progress, the transaction is completely undone, leaving no partial effects on data. Transaction Dependencies In addition to supporting all four ACID properties, a transaction might exhibit few other behaviors (known as dependency problems or consistency problems). Lost Updates: Occur when two processes read the same data and both manipulate the data, changing its value and then both try to update the original data to the new value. The second process might overwrite the first update completely. Dirty Reads: Occurs when a process reads uncommitted data. If one process has changed data but not yet committed the change, another process reading the data will read it in an inconsistent state. Non-repeatable Reads: A read is non-repeatable if a process might get different values when reading the same data in two reads within the same transaction. This can happen when another process changes the data in between the reads that the first process is doing. Phantoms: Occurs when membership in a set changes. It occurs if two SELECT operations using the same predicate in the same transaction return a different number of rows. Isolation Levels SQL Server supports 5 isolation levels that control the behavior of read operations. Read Uncommitted All behaviors except for lost updates are possible. Implemented by allowing the read operations to not take any locks, and because of this, it won’t be blocked by conflicting locks acquired by other processes. The process can read data that another process has modified but not yet committed. When using the read uncommitted isolation level and scanning an entire table, SQL Server can decide to do an allocation order scan (in page-number order) instead of a logical order scan (following page pointers). If another process doing concurrent operations changes data and move rows to a new location in the table, the allocation order scan can end up reading the same row twice. Also can happen if you have read a row before it is updated and then an update moves the row to a higher page number than your scan encounters later. Performing an allocation order scan under Read Uncommitted can cause you to miss a row completely – can happen when a row on a high page number that hasn’t been read yet is updated and moved to a lower page number that has already been read. Read Committed Two varieties of read committed isolation: optimistic and pessimistic (default). Ensures that a read never reads data that another application hasn’t committed. If another transaction is updating data and has exclusive locks on data, your transaction will have to wait for the locks to be released. Your transaction must put share locks on data that are visited, which means that data might be unavailable for others to use. A share lock doesn’t prevent others from reading but prevents them from updating. Read committed (snapshot) ensures that an operation never reads uncommitted data, but not by forcing other processes to wait. SQL Server generates a version of the changed row with its previous committed values. Data being changed is still locked but other processes can see the previous versions of the data as it was before the update operation began. Repeatable Read This is a Pessimistic isolation level. Ensures that if a transaction revisits data or a query is reissued the data doesn’t change. That is, issuing the same query twice within a transaction cannot pickup any changes to data values made by another user’s transaction because no changes can be made by other transactions. However, this does allow phantom rows to appear. Preventing non-repeatable read is a desirable safeguard but cost is that all shared locks in a transaction must be held until the completion of the transaction. Snapshot Snapshot Isolation (SI) is an optimistic isolation level. Allows for processes to read older versions of committed data if the current version is locked. Difference between snapshot and read committed has to do with how old the older versions have to be. It’s possible to have two transactions executing simultaneously that give us a result that is not possible in any serial execution. Serializable This is the strongest of the pessimistic isolation level. Adds to repeatable read isolation level by ensuring that if a query is reissued rows were not added in the interim, i.e, phantoms do not appear. Preventing phantoms is another desirable safeguard, but cost of this extra safeguard is similar to that of repeatable read – all shared locks in a transaction must be held until the transaction completes. In addition serializable isolation level requires that you lock data that has been read but also data that doesn’t exist. Ex: if a SELECT returned no rows, you want it to return no. rows when the query is reissued. This is implemented in SQL Server by a special kind of lock called the key-range lock. Key-range locks require that there be an index on the column that defines the range of values. If there is no index on the column, serializable isolation requires a table lock. Gets its name from the fact that running multiple serializable transactions at the same time is equivalent of running them one at a time. Now that we understand the basics of what concurrency is, the subsequent blog posts will try to bring out the basics around locking, blocking, deadlocks because they are the fundamental blocks that make concurrency possible. Now if you are with me – let us continue learning for SQL Server Locking Basics. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Concurrency

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  • The C++ Standard Template Library as a BDB Database (part 1)

    - by Gregory Burd
    If you've used C++ you undoubtedly have used the Standard Template Libraries. Designed for in-memory management of data and collections of data this is a core aspect of all C++ programs. Berkeley DB is a database library with a variety of APIs designed to ease development, one of those APIs extends and makes use of the STL for persistent, transactional data storage. dbstl is an STL standard compatible API for Berkeley DB. You can make use of Berkeley DB via this API as if you are using C++ STL classes, and still make full use of Berkeley DB features. Being an STL library backed by a database, there are some important and useful features that dbstl can provide, while the C++ STL library can't. The following are a few typical use cases to use the dbstl extensions to the C++ STL for data storage. When data exceeds available physical memory.Berkeley DB dbstl can vastly improve performance when managing a dataset which is larger than available memory. Performance suffers when the data can't reside in memory because the OS is forced to use virtual memory and swap pages of memory to disk. Switching to BDB's dbstl improves performance while allowing you to keep using STL containers. When you need concurrent access to C++ STL containers.Few existing C++ STL implementations support concurrent access (create/read/update/delete) within a container, at best you'll find support for accessing different containers of the same type concurrently. With the Berkeley DB dbstl implementation you can concurrently access your data from multiple threads or processes with confidence in the outcome. When your objects are your database.You want to have object persistence in your application, and store objects in a database, and use the objects across different runs of your application without having to translate them to/from SQL. The dbstl is capable of storing complicated objects, even those not located on a continous chunk of memory space, directly to disk without any unnecessary overhead. These are a few reasons why you should consider using Berkeley DB's C++ STL support for your embedded database application. In the next few blog posts I'll show you a few examples of this approach, it's easy to use and easy to learn.

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  • Application Lifecycle Management Tools

    - by John K. Hines
    Leading a team comprised of three former teams means that we have three of everything.  Three places to gather requirements, three (actually eight or nine) places for customers to submit support requests, three places to plan and track work. We’ve been looking into tools that combine these features into a single product.  Not just Agile planning tools, but those that allow us to look in a single place for requirements, work items, and reports. One of the interesting choices is Software Planner by Automated QA (the makers of Test Complete).  It's a lovely tool with real end-to-end process support.  We’re probably not going to use it for one reason – cost.  I’m sure our company could get a discount, but it’s on a concurrent user license that isn’t cheap for a large number of users.  Some initial guesswork had us paying over $6,000 for 3 concurrent users just to get started with the Enterprise version.  Still, it’s intuitive, has great Agile capabilities, and has a reputation for excellent customer support. At the moment we’re digging deeper into Rational Team Concert by IBM.  Reading the docs on this product makes me want to submit my resume to Big Blue.  Not only does RTC integrate everything we need, but it’s free for up to 10 developers.  It has beautiful support for all phases of Scrum.  We’re going to bring the sales representative in for a demo. This marks one of the few times that we’re trying to resist the temptation to write our own tool.  And I think this is the first time that something so complex may actually be capably provided by an external source.   Hooray for less work! Technorati tags: Scrum Scrum Tools

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  • UML Diagrams of Multi-Threaded Applications

    - by PersonalNexus
    For single-threaded applications I like to use class diagrams to get an overview of the architecture of that application. This type of diagram, however, hasn’t been very helpful when trying to understand heavily multi-threaded/concurrent applications, for instance because different instances of a class "live" on different threads (meaning accessing an instance is save only from the one thread it lives on). Consequently, associations between classes don’t necessarily mean that I can call methods on those objects, but instead I have to make that call on the target object's thread. Most literature I have dug up on the topic such as Designing Concurrent, Distributed, and Real-Time Applications with UML by Hassan Gomaa had some nice ideas, such as drawing thread boundaries into object diagrams, but overall seemed a bit too academic and wordy to be really useful. I don’t want to use these diagrams as a high-level view of the problem domain, but rather as a detailed description of my classes/objects, their interactions and the limitations due to thread-boundaries I mentioned above. I would therefore like to know: What types of diagrams have you found to be most helpful in understanding multi-threaded applications? Are there any extensions to classic UML that take into account the peculiarities of multi-threaded applications, e.g. through annotations illustrating that some objects might live in a certain thread while others have no thread-affinity; some fields of an object may be read from any thread, but written to only from one; some methods are synchronous and return a result while others are asynchronous that get requests queued up and return results for instance via a callback on a different thread.

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  • Exalogic Elastic Cloud Software (EECS) version 2.0.1 available

    - by JuergenKress
    We are pleased to announce that as of today (May 14, 2012) the Exalogic Elastic Cloud Software (EECS) version 2.0.1 has been made Generally Available. This release is the culmination of over two and a half years of engineering effort from an extended team spanning 18 product development organizations on three continents, and is the most powerful, sophisticated and comprehensive Exalogic Elastic Cloud Software release to date. With this new EECS release, Exalogic customers now have an ideal platform for not only high-performance and mission critical applications, but for standardization and consolidation of virtually all Oracle Fusion Middleware, Fusion Applications, Application Unlimited and Oracle GBU Applications. With the release of EECS 2.0.1, Exalogic is now capable of hosting multiple concurrent tenants, business applications and middleware deployments with fine-grained resource management, enterprise-grade security, unmatched manageability and extreme performance in a fully virtualized environment. The Exalogic Elastic Cloud Software 2.0.1 release brings important new technologies to the Exalogic platform: Exalogic is now capable of hosting multiple concurrent tenants, business applications and middleware deployments with fine-grained resource management, enterprise-grade security, unmatched manageabi! lity and extreme performance in a fully virtualized environment. Support for extremely high-performance x86 server virtualization via a highly optimized version of Oracle VM 3.x. A rich, fully integrated Infrastructure-as-a-Service management system called Exalogic Control which provides graphical, command line and Java interfaces that allows Cloud Users, or external systems, to create and manage users, virtual servers, virtual storage and virtual network resources. Webcast Series: Rethink Your Business Application Deployment Strategy Redefining the CRM and E-Commerce Experience with Oracle Exalogic, 7-Jun@10am PT & On-Demand: ‘The Road to a Cloud-Enabled, Infinitely Elastic Application Infrastructure’ (featuring Gartner Analysts). WebLogic Partner Community For regular information become a member in the WebLogic Partner Community please visit: http://www.oracle.com/partners/goto/wls-emea ( OPN account required). If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Wiki Technorati Tags: ExaLogic Elastic Cloud,ExaLogic,WebLogic,WebLogic Community,Oracle,OPN,Jürgen Kress,ExaLogic 2.0.1

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  • Install Base Transaction Error Troubleshooting

    - by LuciaC
    Oracle Installed Base is an item instance life cycle tracking application that facilitates enterprise-wide life cycle item management and tracking capability.In a typical process flow a sales order is created and shipped, this updates Inventory and creates a new item instance in Install Base (IB).  The Inventory update results in a record being placed in the SFM Event Queue.  If the record is successfully processed the IB tables are updated, if there is an error the record is placed in the csi_txn_errors table and the error needs to be resolved so that the IB instance can be created.It's extremely important to be proactive and monitor IB Transaction Errors regularly.  Errors cascade and can build up exponentially if not resolved. Due to this cascade effect, error records need to be considered as a whole and not individually; the root cause of any error needs to be resolved first and this may result in the subsequent errors resolving themselves. Install Base Transaction Error Diagnostic Program In the past the IBtxnerr.sql script was used to diagnose transaction errors, this is now replaced by an enhanced concurrent program version of the script. See the following note for details of how to download, install and run the concurrent program as well as details of how to interpret the results: Doc ID 1501025.1 - Install Base Transaction Error Diagnostic Program  The program provides comprehensive information about the errors found as well as links to known knowledge articles which can help to resolve the specific error. Troubleshooting Watch the replay of the 'EBS CRM: 11i and R12 Transaction Error Troubleshooting - an Overview' webcast or download the presentation PDF (go to Doc ID 1455786.1 and click on 'Archived 2011' tab).  The webcast and PDF include more information, including SQL statements that you can use to identify errors and their sources as well as recommended setup and troubleshooting tips. Refer to these notes for comprehensive information: Doc ID 1275326.1: E-Business Oracle Install Base Product Information Center Doc ID 1289858.1: Install Base Transaction Errors Master Repository Doc ID: 577978.1: Troubleshooting Install Base Errors in the Transaction Errors Processing Form  Don't forget your Install Base Community where you can ask questions to help you resolve your IB transaction errors.

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  • Using ConcurrentQueue for thread-safe Performance Bookkeeping.

    - by Strenium
    Just a small tidbit that's sprung up today. I had to book-keep and emit diagnostics for the average thread performance in a highly-threaded code over a period of last X number of calls and no more. Need of the day: a thread-safe, self-managing stats container. Since .NET 4.0 introduced new thread-safe 'Collections.Concurrent' objects and I've been using them frequently - the one in particular seemed like a good fit for storing each threads' performance data - ConcurrentQueue. But I wanted to store only the most recent X# of calls and since the ConcurrentQueue currently does not support size constraint I had to come up with my own generic version which attempts to restrict usage to numeric types only: unfortunately there is no IArithmetic-like interface which constrains to only numeric types – so the constraints here here aren't as elegant as they could be. (Note the use of the Average() method, of course you can use others as well as make your own).   FIFO FixedSizedConcurrentQueue using System;using System.Collections.Concurrent;using System.Linq; namespace xxxxx.Data.Infrastructure{    [Serializable]    public class FixedSizedConcurrentQueue<T> where T : struct, IConvertible, IComparable<T>    {        private FixedSizedConcurrentQueue() { }         public FixedSizedConcurrentQueue(ConcurrentQueue<T> queue)        {            _queue = queue;        }         ConcurrentQueue<T> _queue = new ConcurrentQueue<T>();         public int Size { get { return _queue.Count; } }        public double Average { get { return _queue.Average(arg => Convert.ToInt32(arg)); } }         public int Limit { get; set; }        public void Enqueue(T obj)        {            _queue.Enqueue(obj);            lock (this)            {                T @out;                while (_queue.Count > Limit) _queue.TryDequeue(out @out);            }        }    } }   The usage case is straight-forward, in this case I’m using a FIFO queue of maximum size of 200 to store doubles to which I simply Enqueue() the calculated rates: Usage var RateQueue = new FixedSizedConcurrentQueue<double>(new ConcurrentQueue<double>()) { Limit = 200 }; /* greater size == longer history */   That’s about it. Happy coding!

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  • terminate called after throwing an instance of 'std::length_error'

    - by mark
    hello all, this is my first post here. As i am newbie, the problem might be stupid. I was writing a piece of code while the following error message shown, terminate called after throwing an instance of 'std::length_error' what(): basic_string::_S_create /home/gcj/finals /home/gcj/quals where Aborted the following is the offending code especially Line 39 to Line 52. It is weired for me as this block of code is almost same as the Line64 to Line79. int main(){ std::vector<std::string> dirs, need; std::string tmp_str; std::ifstream fp_in("small.in"); std::ofstream fp_out("output"); std::string::iterator iter_substr_begin, iter_substr_end; std::string slash("/"); int T, N, M; fp_in>>T; for (int t = 0; t < T; t++){ std::cout<<" time "<< t << std::endl; fp_in >> N >> M; for (int n =0; n<N; n++){ fp_in>>tmp_str; dirs.push_back(tmp_str); tmp_str.clear(); } for (int m=0; m<M; m++){ fp_in>>tmp_str; need.push_back(tmp_str); tmp_str.clear(); } for (std::vector<std::string>::iterator iter = dirs.begin(); iter!=dirs.end(); iter++){ for (std::string::iterator iter_str = (*iter).begin()+1; iter_str<(*iter).end(); ++iter_str){ if ((*iter_str)=='/') { std::string tmp_str2((*iter).begin(), iter_str); if (find(dirs.begin(), dirs.end(), tmp_str2)==dirs.end()) { dirs.push_back(tmp_str2); } } } } for (std::vector<std::string>::iterator iter_tmp = dirs.begin(); iter_tmp!= dirs.end(); ++iter_tmp) std::cout<<*iter_tmp<<" "; dirs.clear(); std::cout<<std::endl; std::cout<<" need "<<std::endl; //processing the next for (std::vector<std::string>::iterator iter_tmp = need.begin(); iter_tmp!=need.end(); ++iter_tmp) std::cout<<*iter_tmp<<" "; std::cout<<" where "; for (std::vector<std::string>::iterator iter = need.begin(); iter!=need.end(); iter++){ for (std::string::iterator iter_str = (*iter).begin()+1; iter_str<(*iter).end(); ++iter_str){ if ((*iter_str)=='/') { std::string tmp_str2((*iter).begin(), iter_str); if (find(need.begin(), need.end(), tmp_str2)==need.end()) { need.push_back(tmp_str2); } } } } for (std::vector<std::string>::iterator iter_tmp = need.begin(); iter_tmp!= need.end(); ++iter_tmp) std::cout<<*iter_tmp<<" "; need.clear(); std::cout<<std::endl; //finish processing the next } for (std::vector<std::string>::iterator iter= dirs.begin(); iter!=dirs.end(); iter++) std::cout<<*iter<<" "; std::cout<<std::endl; for (std::vector<std::string>::iterator iter= need.begin(); iter!=need.end(); iter++) std::cout<<*iter<<" "; std::cout<<std::endl; fp_out.close(); } best regards, Mark

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  • Committed JDO writes do not apply on local GAE HRD, or possibly reused transaction

    - by eeeeaaii
    I'm using JDO 2.3 on app engine. I was using the Master/Slave datastore for local testing and recently switched over to using the HRD datastore for local testing, and parts of my app are breaking (which is to be expected). One part of the app that's breaking is where it sends a lot of writes quickly - that is because of the 1-second limit thing, it's failing with a concurrent modification exception. Okay, so that's also to be expected, so I have the browser retry the writes again later when they fail (maybe not the best hack but I'm just trying to get it working quickly). But a weird thing is happening. Some of the writes which should be succeeding (the ones that DON'T get the concurrent modification exception) are also failing, even though the commit phase completes and the request returns my success code. I can see from the log that the retried requests are working okay, but these other requests that seem to have committed on the first try are, I guess, never "applied." But from what I read about the Apply phase, writing again to that same entity should force the apply... but it doesn't. Code follows. Some things to note: I am attempting to use automatic JDO caching. So this is where JDO uses memcache under the covers. This doesn't actually work unless you wrap everything in a transaction. all the requests are doing is reading a string out of an entity, modifying part of the string, and saving that string back to the entity. If these requests weren't in transactions, you'd of course have the "dirty read" problem. But with transactions, isolation is supposed to be at the level of "serializable" so I don't see what's happening here. the entity being modified is a root entity (not in a group) I have cross-group transactions enabled Another weird thing is happening. If the concurrent modification thing happens, and I subsequently edit more than 5 more entities (this is the max for cross-group transactions), then nothing happens right away, but when I stop and restart the server I get "IllegalArgumentException: operating on too many entity groups in a single transaction". Could it be possible that the PMF is returning the same PersistenceManager every time, or the PM is reusing the same transaction every time? I don't see how I could possibly get the above error otherwise. The code inside the transaction just edits one root entity. I can't think of any other way that GAE would give me the "too many entity groups" error. The relevant code (this is a simplified version) PersistenceManager pm = PMF.getManager(); Transaction tx = pm.currentTransaction(); String responsetext = ""; try { tx.begin(); // I have extra calls to "makePersistent" because I found that relying // on pm.close didn't always write the objects to cache, maybe that // was only a DataNucleus 1.x issue though Key userkey = obtainUserKeyFromCookie(); User u = pm.getObjectById(User.class, userkey); pm.makePersistent(u); // to make sure it gets cached for next time Key mapkey = obtainMapKeyFromQueryString(); // this is NOT a java.util.Map, just FYI Map currentmap = pm.getObjectById(Map.class, mapkey); Text mapData = currentmap.getMapData(); // mapData is JSON stored in the entity Text newMapData = parseModifyAndReturn(mapData); // transform the map currentmap.setMapData(newMapData); // mutate the Map object pm.makePersistent(currentmap); // make sure to persist so there is a cache hit tx.commit(); responsetext = "OK"; } catch (JDOCanRetryException jdoe) { // log jdoe responsetext = "RETRY"; } catch (Exception e) { // log e responsetext = "ERROR"; } finally { if (tx.isActive()) { tx.rollback(); } pm.close(); } resp.getWriter().println(responsetext); EDIT: so I have verified that it fails after exactly 5 transactions. Here's what I do: I create a Foo (root entity), do a bunch of concurrent operations on that Foo, and some fail and get retried, and some commit but don't apply (as described above). Then, I start creating more Foos, and do a few operations on those new Foos. If I only create four Foos, stopping and restarting app engine does NOT give me the IllegalArgumentException. However if I create five Foos (which is the limit for cross-group transactions), then when I stop and restart app engine, I do get the exception. So it seems that somehow these new Foos I am creating are counting toward the limit of 5 max entities per transaction, even though they are supposed to be handled by separate transactions. It's as if a transaction is still open and is being reused by the servlet when it handles the new requests for the 2nd through 5th Foos. EDIT2: it looks like the IllegalArgument thing is independent of the other bug. In other words, it always happens when I create five Foos, even if I don't get the concurrent modification exception. I don't know if it's a symptom of the same problem or if it's unrelated. EDIT3: I found out what was causing the (unrelated) IllegalArgumentException, it was a dumb mistake on my part. But the other issue is still happening. EDIT4: added pseudocode for the datastore access EDIT5: I am pretty sure I know why this is happening, but I will still award the bounty to anyone who can confirm it. Basically, I think the problem is that transactions are not really implemented in the local version of the datastore. References: https://groups.google.com/forum/?fromgroups=#!topic/google-appengine-java/gVMS1dFSpcU https://groups.google.com/forum/?fromgroups=#!topic/google-appengine-java/deGasFdIO-M https://groups.google.com/forum/?hl=en&fromgroups=#!msg/google-appengine-java/4YuNb6TVD6I/gSttMmHYwo0J Because transactions are not implemented, rollback is essentially a no-op. Therefore, I get a dirty read when two transactions try to modify the record at the same time. In other words, A reads the data and B reads the data at the same time. A attempts to modify the data, and B attempts to modify a different part of the data. A writes to the datastore, then B writes, obliterating A's changes. Then B is "rolled back" by app engine, but since rollbacks are a no-op when running on the local datastore, B's changes stay, and A's do not. Meanwhile, since B is the thread that threw the exception, the client retries B, but does not retry A (since A was supposedly the transaction that succeeded).

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  • WebLogic Server Performance and Tuning: Part I - Tuning JVM

    - by Gokhan Gungor
    Each WebLogic Server instance runs in its own dedicated Java Virtual Machine (JVM) which is their runtime environment. Every Admin Server in any domain executes within a JVM. The same also applies for Managed Servers. WebLogic Server can be used for a wide variety of applications and services which uses the same runtime environment and resources. Oracle WebLogic ships with 2 different JVM, HotSpot and JRocket but you can choose which JVM you want to use. JVM is designed to optimize itself however it also provides some startup options to make small changes. There are default values for its memory and garbage collection. In real world, you will not want to stick with the default values provided by the JVM rather want to customize these values based on your applications which can produce large gains in performance by making small changes with the JVM parameters. We can tell the garbage collector how to delete garbage and we can also tell JVM how much space to allocate for each generation (of java Objects) or for heap. Remember during the garbage collection no other process is executed within the JVM or runtime, which is called STOP THE WORLD which can affect the overall throughput. Each JVM has its own memory segment called Heap Memory which is the storage for java Objects. These objects can be grouped based on their age like young generation (recently created objects) or old generation (surviving objects that have lived to some extent), etc. A java object is considered garbage when it can no longer be reached from anywhere in the running program. Each generation has its own memory segment within the heap. When this segment gets full, garbage collector deletes all the objects that are marked as garbage to create space. When the old generation space gets full, the JVM performs a major collection to remove the unused objects and reclaim their space. A major garbage collect takes a significant amount of time and can affect system performance. When we create a managed server either on the same machine or on remote machine it gets its initial startup parameters from $DOMAIN_HOME/bin/setDomainEnv.sh/cmd file. By default two parameters are set:     Xms: The initial heapsize     Xmx: The max heapsize Try to set equal initial and max heapsize. The startup time can be a little longer but for long running applications it will provide a better performance. When we set -Xms512m -Xmx1024m, the physical heap size will be 512m. This means that there are pages of memory (in the state of the 512m) that the JVM does not explicitly control. It will be controlled by OS which could be reserve for the other tasks. In this case, it is an advantage if the JVM claims the entire memory at once and try not to spend time to extend when more memory is needed. Also you can use -XX:MaxPermSize (Maximum size of the permanent generation) option for Sun JVM. You should adjust the size accordingly if your application dynamically load and unload a lot of classes in order to optimize the performance. You can set the JVM options/heap size from the following places:     Through the Admin console, in the Server start tab     In the startManagedWeblogic script for the managed servers     $DOMAIN_HOME/bin/startManagedWebLogic.sh/cmd     JAVA_OPTIONS="-Xms1024m -Xmx1024m" ${JAVA_OPTIONS}     In the setDomainEnv script for the managed servers and admin server (domain wide)     USER_MEM_ARGS="-Xms1024m -Xmx1024m" When there is free memory available in the heap but it is too fragmented and not contiguously located to store the object or when there is actually insufficient memory we can get java.lang.OutOfMemoryError. We should create Thread Dump and analyze if that is possible in case of such error. The second option we can use to produce higher throughput is to garbage collection. We can roughly divide GC algorithms into 2 categories: parallel and concurrent. Parallel GC stops the execution of all the application and performs the full GC, this generally provides better throughput but also high latency using all the CPU resources during GC. Concurrent GC on the other hand, produces low latency but also low throughput since it performs GC while application executes. The JRockit JVM provides some useful command-line parameters that to control of its GC scheme like -XgcPrio command-line parameter which takes the following options; XgcPrio:pausetime (To minimize latency, parallel GC) XgcPrio:throughput (To minimize throughput, concurrent GC ) XgcPrio:deterministic (To guarantee maximum pause time, for real time systems) Sun JVM has similar parameters (like  -XX:UseParallelGC or -XX:+UseConcMarkSweepGC) to control its GC scheme. We can add -verbosegc -XX:+PrintGCDetails to monitor indications of a problem with garbage collection. Try configuring JVM’s of all managed servers to execute in -server mode to ensure that it is optimized for a server-side production environment.

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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

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