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  • Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

    - by Thanos Terentes Printzios
    In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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  • A jQuery Plug-in to monitor Html Element CSS Changes

    - by Rick Strahl
    Here's a scenario I've run into on a few occasions: I need to be able to monitor certain CSS properties on an HTML element and know when that CSS element changes. The need for this arose out of wanting to build generic components that could 'attach' themselves to other objects and monitor changes on the ‘parent’ object so the dependent object can adjust itself accordingly. What I wanted to create is a jQuery plug-in that allows me to specify a list of CSS properties to monitor and have a function fire in response to any change to any of those CSS properties. The result are the .watch() and .unwatch() jQuery plug-ins. Here’s a simple example page of this plug-in that demonstrates tracking changes to an element being moved with draggable and closable behavior: http://www.west-wind.com/WestWindWebToolkit/samples/Ajax/jQueryPluginSamples/WatcherPlugin.htm Try it with different browsers – IE and FireFox use the DOM event handlers and Chrome, Safari and Opera use setInterval handlers to manage this behavior. It should work in all of them but all but IE and FireFox will show a bit of lag between the changes in the main element and the shadow. The relevant HTML for this example is this fragment of a main <div> (#notebox) and an element that is to mimic a shadow (#shadow). <div class="containercontent"> <div id="notebox" style="width: 200px; height: 150px;position: absolute; z-index: 20; padding: 20px; background-color: lightsteelblue;"> Go ahead drag me around and close me! </div> <div id="shadow" style="background-color: Gray; z-index: 19;position:absolute;display: none;"> </div> </div> The watcher plug in is then applied to the main <div> and shadow in sync with the following plug-in code: <script type="text/javascript"> $(document).ready(function () { var counter = 0; $("#notebox").watch("top,left,height,width,display,opacity", function (data, i) { var el = $(this); var sh = $("#shadow"); var propChanged = data.props[i]; var valChanged = data.vals[i]; counter++; showStatus("Prop: " + propChanged + " value: " + valChanged + " " + counter); var pos = el.position(); var w = el.outerWidth(); var h = el.outerHeight(); sh.css({ width: w, height: h, left: pos.left + 5, top: pos.top + 5, display: el.css("display"), opacity: el.css("opacity") }); }) .draggable() .closable() .css("left", 10); }); </script> When you run this page as you drag the #notebox element the #shadow element will maintain and stay pinned underneath the #notebox element effectively keeping the shadow attached to the main element. Likewise, if you hide or fadeOut() the #notebox element the shadow will also go away – show the #notebox element and the shadow also re-appears because we are assigning the display property from the parent on the shadow. Note we’re attaching the .watch() plug-in to the #notebox element and have it fire whenever top,left,height,width,opacity or display CSS properties are changed. The passed data element contains a props[] and vals[] array that holds the properties monitored and their current values. An index passed as the second parm tells you which property has changed and what its current value is (propChanged/valChanged in the code above). The rest of the watcher handler code then deals with figuring out the main element’s position and recalculating and setting the shadow’s position using the jQuery .css() function. Note that this is just an example to demonstrate the watch() behavior here – this is not the best way to create a shadow. If you’re interested in a more efficient and cleaner way to handle shadows with a plug-in check out the .shadow() plug-in in ww.jquery.js (code search for fn.shadow) which uses native CSS features when available but falls back to a tracked shadow element on browsers that don’t support it, which is how this watch() plug-in came about in the first place :-) How does it work? The plug-in works by letting the user specify a list of properties to monitor as a comma delimited string and a handler function: el.watch("top,left,height,width,display,opacity", function (data, i) {}, 100, id) You can also specify an interval (if no DOM event monitoring isn’t available in the browser) and an ID that identifies the event handler uniquely. The watch plug-in works by hooking up to DOMAttrModified in FireFox, to onPropertyChanged in Internet Explorer, or by using a timer with setInterval to handle the detection of changes for other browsers. Unfortunately WebKit doesn’t support DOMAttrModified consistently at the moment so Safari and Chrome currently have to use the slower setInterval mechanism. In response to a changed property (or a setInterval timer hit) a JavaScript handler is fired which then runs through all the properties monitored and determines if and which one has changed. The DOM events fire on all property/style changes so the intermediate plug-in handler filters only those hits we’re interested in. If one of our monitored properties has changed the specified event handler function is called along with a data object and an index that identifies the property that’s changed in the data.props/data.vals arrays. The jQuery plugin to implement this functionality looks like this: (function($){ $.fn.watch = function (props, func, interval, id) { /// <summary> /// Allows you to monitor changes in a specific /// CSS property of an element by polling the value. /// when the value changes a function is called. /// The function called is called in the context /// of the selected element (ie. this) /// </summary> /// <param name="prop" type="String">CSS Properties to watch sep. by commas</param> /// <param name="func" type="Function"> /// Function called when the value has changed. /// </param> /// <param name="interval" type="Number"> /// Optional interval for browsers that don't support DOMAttrModified or propertychange events. /// Determines the interval used for setInterval calls. /// </param> /// <param name="id" type="String">A unique ID that identifies this watch instance on this element</param> /// <returns type="jQuery" /> if (!interval) interval = 100; if (!id) id = "_watcher"; return this.each(function () { var _t = this; var el$ = $(this); var fnc = function () { __watcher.call(_t, id) }; var data = { id: id, props: props.split(","), vals: [props.split(",").length], func: func, fnc: fnc, origProps: props, interval: interval, intervalId: null }; // store initial props and values $.each(data.props, function (i) { data.vals[i] = el$.css(data.props[i]); }); el$.data(id, data); hookChange(el$, id, data); }); function hookChange(el$, id, data) { el$.each(function () { var el = $(this); if (typeof (el.get(0).onpropertychange) == "object") el.bind("propertychange." + id, data.fnc); else if ($.browser.mozilla) el.bind("DOMAttrModified." + id, data.fnc); else data.intervalId = setInterval(data.fnc, interval); }); } function __watcher(id) { var el$ = $(this); var w = el$.data(id); if (!w) return; var _t = this; if (!w.func) return; // must unbind or else unwanted recursion may occur el$.unwatch(id); var changed = false; var i = 0; for (i; i < w.props.length; i++) { var newVal = el$.css(w.props[i]); if (w.vals[i] != newVal) { w.vals[i] = newVal; changed = true; break; } } if (changed) w.func.call(_t, w, i); // rebind event hookChange(el$, id, w); } } $.fn.unwatch = function (id) { this.each(function () { var el = $(this); var data = el.data(id); try { if (typeof (this.onpropertychange) == "object") el.unbind("propertychange." + id, data.fnc); else if ($.browser.mozilla) el.unbind("DOMAttrModified." + id, data.fnc); else clearInterval(data.intervalId); } // ignore if element was already unbound catch (e) { } }); return this; } })(jQuery); Note that there’s a corresponding .unwatch() plug-in that can be used to stop monitoring properties. The ID parameter is optional both on watch() and unwatch() – a standard name is used if you don’t specify one, but it’s a good idea to use unique names for each element watched to avoid overlap in event ids especially if you’re monitoring many elements. The syntax is: $.fn.watch = function(props, func, interval, id) props A comma delimited list of CSS style properties that are to be watched for changes. If any of the specified properties changes the function specified in the second parameter is fired. func The function fired in response to a changed styles. Receives this as the element changed and an object parameter that represents the watched properties and their respective values. The first parameter is passed in this structure: { id: watcherId, props: [], vals: [], func: thisFunc, fnc: internalHandler, origProps: strPropertyListOnWatcher }; A second parameter is the index of the changed property so data.props[i] or data.vals[i] gets the property and changed value. interval The interval for setInterval() for those browsers that don't support property watching in the DOM. In milliseconds. id An optional id that identifies this watcher. Required only if multiple watchers might be hooked up to the same element. The default is _watcher if not specified. It’s been a Journey I started building this plug-in about two years ago and had to make many modifications to it in response to changes in jQuery and also in browser behaviors. I think the latest round of changes made should make this plug-in fairly future proof going forward (although I hope there will be better cross-browser change event notifications in the future). One of the big problems I ran into had to do with recursive change notifications – it looks like starting with jQuery 1.44 and later, jQuery internally modifies element properties on some calls to some .css()  property retrievals and things like outerHeight/Width(). In IE this would cause nasty lock up issues at times. In response to this I changed the code to unbind the events when the handler function is called and then rebind when it exits. This also makes user code less prone to stack overflow recursion as you can actually change properties on the base element. It also means though that if you change one of the monitors properties in the handler the watch() handler won’t fire in response – you need to resort to a setTimeout() call instead to force the code to run outside of the handler: $("#notebox") el.watch("top,left,height,width,display,opacity", function (data, i) { var el = $(this); … // this makes el changes work setTimeout(function () { el.css("top", 10) },10); }) Since I’ve built this component I’ve had a lot of good uses for it. The .shadow() fallback functionality is one of them. Resources The watch() plug-in is part of ww.jquery.js and the West Wind West Wind Web Toolkit. You’re free to use this code here or the code from the toolkit. West Wind Web Toolkit Latest version of ww.jquery.js (search for fn.watch) watch plug-in documentation © Rick Strahl, West Wind Technologies, 2005-2011Posted in ASP.NET  JavaScript  jQuery  

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  • How can I set up a touchscreen as the non-primary monitor in a dual monitor situation?

    - by bazzjedi
    I have been looking for information about using a second monitor, and thought of using a touchscreen. Will a touchscreen monitor work in a dual setup if it is not the main monitor? I haven't found any information on this; I've only found information about the touchscreen being the main monitor. That is, except at this SU question (snippet below): If you mean do the touch screen features still work on the other machine, the answer is yes. Past that, you can even see some of the touch screen features on a non touch screen monitor (just not the multi touch features!) For example, on the taskbar, click (without releasing) on any icon and then drag the mouse up, and you will see that it does the same as using your finger and dragging up. I have a HP 2510 for the main monitor. I'm thinking of adding a HP 2310ti (the touchscreen) as the secondary. My graphics card is a geforce gtx 295. I'm running Windows 7 Professional.

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  • Windows 7: Dual Monitor Issue

    - by sdoca
    I have a Dell laptop with a docking station and two external monitors hooked up. I'm running Windows 7 64 bit. Originally, the two monitors were the same - Dell 1908FP. I have replaced one of them with an HP LA2405. I have set the HP 24" (1920 x 1200 connected via DVI port) as montior 1 and extended to use the Dell 19" (12080 x 1024 connected via VGA port) as monitor 2. I have set my power plan so that when the laptop is plugged in, it will turn the monitors off after 10 minutes, but it will not put my laptop to sleep. However, now that I have the HP monitor, when I unlock my laptop and the monitors come back on, all my windows are resized and shifted to the top left corner of the HP monitor as if they had been resized for display on the smaller Dell monitor. A co-worker has the exact same laptop and monitor configuration but doesn't experience this issue, so I figure there's some configuration that's different but we can't find it. I haven't been able to find any mention of a similar problem doing an internet search, but I'm not really sure what terms to use in my search. Anybody have any suggestions as to what may be causing the issue? OS setting? Monitor setting? EDIT: My laptop is using the Intel Graphics and Media Control Panel/drivers.

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  • Secondary monitor bug: a problem in WPF or in the graphics driver?

    - by emddudley
    I have discovered a strange bug with my WPF application and I am trying to determine whether it is a problem with WPF or my graphics driver so that I can report it to the appropriate company. I have a Quadro FX 1700 with the latest drivers (197.54) on a Windows XP system, running a .NET 3.5 SP1 application. I have dual monitors, and when I maximize then minimize a child window of the main window on my primary monitor, the child window gets drawn on the secondary monitor as well. It appears in both places. I made a sample application (code is below) which induces this behavior. Start the application and ensure the main window is on your primary monitor. Double-click the main window. A green child window should appear. Click the green child window to maximize. Click the green child window to minimize. Can anyone else reproduce this problem? On my system the green child restores, but then it's drawn on both my primary and secondary monitors, rather than just the primary monitor. App.xaml <Application xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" x:Class="DualMonitorBug.App" StartupUri="Shell.xaml" /> App.xaml.cs using System.Windows; namespace DualMonitorBug { public partial class App : Application { } } Shell.xaml <Window xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" x:Class="DualMonitorBug.Shell" Title="Shell" Height="480" Width="640" MouseDoubleClick="ShowDialog" /> Shell.xaml.cs using System.Windows; using System.Windows.Input; namespace DualMonitorBug { public partial class Shell : Window { public Shell() { InitializeComponent(); } private void ShowDialog(object sender, MouseButtonEventArgs e) { DialogWindow dialog = new DialogWindow(); dialog.Owner = this; dialog.Show(); } } } DialogWindow.xaml <Window xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" x:Class="DualMonitorBug.DialogWindow" Title="Dialog Window" Height="240" Width="320" AllowsTransparency="True" Background="Green" MouseLeftButtonDown="ShowHideDialog" WindowStyle="None" /> DialogWindow.xaml.cs using System.Windows; using System.Windows.Input; namespace DualMonitorBug { public partial class DialogWindow : Window { public DialogWindow() { InitializeComponent(); } private void ShowHideDialog(object sender, MouseButtonEventArgs e) { this.WindowState = (this.WindowState == WindowState.Normal) ? WindowState.Maximized : WindowState.Normal; } } }

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  • How to use JavaScript to measure how bright a users monitor is ?

    - by HankV
    I've noticed that the brightness of computer monitors drastically varies between computers. As such, this changes the look of web pages greatly. Is there a way to use JavaScript to automatically detect how bright (or dark) a users monitor is so that I can adjust my web page colors accordingly? UPDATE Please note that I do not want manual user involvement. I want this detection to be automatic so that users don't realize I dynamically change the color palette automatically based on the brightness/darkness of their monitor.

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  • 11gR2 ???:Oracle Cluster Health Monitor(CHM)??

    - by JaneZhang(???)
       Cluster Health Monitor(????CHM)???Oracle?????,?????????????(CPU????SWAP????I/O?????)??????CHM??????????   ??????????????????????Hang?????(Eviction)????????????????,??????CHM????????????????????,????????????? CHM???????????:    11.2.0.2 ?????? Oracle Grid Infrastructure for Linux (???Linux Itanium) ?Solaris (Sparc 64 ? x86-64)    11.2.0.3 ????? Oracle Grid Infrastructure for AIX ? Windows (???Windows Itanium)?    ????,???????????CHM?????(ora.crf)???:    $ crsctl stat res -t -init    --------------------------------------------------------------------------------    NAME           TARGET  STATE        SERVER                   STATE_DETAILS       Cluster Resources ora.crf        ONLINE  ONLINE       rac1 CHM????????:    1). System Monitor Service(osysmond):?????????????,osysmond????????????????cluster logger service,???????????????????CHM?????      $ ps -ef|grep osysmond       root      7984     1  0 Jun05 ?        01:16:14 /u01/app/11.2.0/grid/bin/osysmond.bin    2). Cluster Logger Service(ologgerd):???????,ologgerd ???????(master),???????(standby)??ologgerd???????????????,??????????     ???:     $ ps -ef|grep ologgerd       root      8257     1  0 Jun05 ?        00:38:26 /u01/app/11.2.0/grid/bin/ologgerd -M -d       /u01/app/11.2.0/grid/crf/db/rac2     ???:      $ ps -ef|grep ologgerd       root      8353     1  0 Jun05 ?        00:18:47 /u01/app/11.2.0/grid/bin/ologgerd -m rac2 -r -d /u01/app/11.2.0/grid/crf/db/rac1 CHM Repository:?????????,?????,????Grid Infrastructure home ? ,??1 GB ?????,???????????0.5GB???? ?????OCLUMON??????????????????(??????3????)? ??????????????:     $ oclumon manage -get reppath       CHM Repository Path = /u01/app/11.2.0/grid/crf/db/rac2       Done     $ oclumon manage -get repsize       CHM Repository Size = 68082 <====????       Done     ????:     $ oclumon manage -repos reploc /shared/oracle/chm      ????:     $ oclumon manage -repos resize 68083 <==?3600(??) ? 259200(3?)??      rac1 --> retention check successful      New retention is 68083 and will use 1073750609 bytes of disk space      CRS-9115-Cluster Health Monitor repository size change completed on all nodes.      Done ??CHM???????????:     1. ?????Grid_home/bin/diagcollection.pl:         1). ??,??cluster logger service????:         $ oclumon manage -get master         Master = rac2         2).?root??????rac2???????:         # <Grid_home>/bin/diagcollection.pl -collect -chmos -incidenttime inc_time -incidentduration duration         inc_time?????????????,???MM/DD/YYYY24HH:MM:SS, duration??????????????????         ??:# diagcollection.pl -collect -crshome /u01/app/11.2.0/grid -chmoshome  /u01/app/11.2.0/grid -chmos -incidenttime 06/15/201215:30:00 -incidentduration 00:05       3).????????,CHM?????????chmosData_rac2_20120615_1537.tar.gz?    2. ??????CHM?????????oclumon:        $oclumon dumpnodeview [[-allnodes] | [-n node1 node2] [-last "duration"] | [-s "time_stamp" -e "time_stamp"] [-v] [-warning]] [-h]        -s??????,-e??????        $ oclumon dumpnodeview -allnodes -v -s "2012-06-15 07:40:00" -e "2012-06-15 07:57:00" > /tmp/chm1.txt       $ oclumon dumpnodeview -n node1 node2 node3 -last "12:00:00" >/tmp/chm1.txt       $ oclumon dumpnodeview -allnodes -last "00:15:00" >/tmp/chm1.txt ???/tmp/chm1.txt??????:----------------------------------------Node: rac1 Clock: '06-15-12 07.40.01' SerialNo:168880----------------------------------------SYSTEM:#cpus: 1 cpu: 17.96 cpuq: 5 physmemfree: 32240 physmemtotal: 2065856 mcache: 1064024 swapfree: 3988376 swaptotal: 4192956 ior: 57 iow: 59 ios: 10 swpin: 0 swpout: 0 pgin: 57 pgout: 59 netr: 65.767 netw: 34.871 procs: 183 rtprocs: 10 #fds: 4902 #sysfdlimit: 6815744 #disks: 4 #nics: 3  nicErrors: 0TOP CONSUMERS:topcpu: 'mrtg(32385) 64.70' topprivmem: 'ologgerd(8353) 84068' topshm: 'oracle(8760) 329452' topfd: 'ohasd.bin(6627) 720' topthread: 'crsd.bin(8235) 44'PROCESSES:name: 'mrtg' pid: 32385 #procfdlimit: 65536 cpuusage: 64.70 privmem: 1160 shm: 1584 #fd: 5 #threads: 1 priority: 20 nice: 0name: 'oracle' pid: 32381 #procfdlimit: 65536 cpuusage: 0.29 privmem: 1456 shm: 12444 #fd: 32 #threads: 1 priority: 15 nice: 0...name: 'oracle' pid: 8756 #procfdlimit: 65536 cpuusage: 0.0 privmem: 2892 shm: 24356 #fd: 47 #threads: 1 priority: 16 nice: 0----------------------------------------Node: rac2 Clock: '06-15-12 07.40.02' SerialNo:168878----------------------------------------SYSTEM:#cpus: 1 cpu: 40.72 cpuq: 8 physmemfree: 34072 physmemtotal: 2065856 mcache: 1005636 swapfree: 3991808 swaptotal: 4192956 ior: 54 iow: 104 ios: 11 swpin: 0 swpout: 0 pgin: 54 pgout: 104 netr: 77.817 netw: 33.008 procs: 178 rtprocs: 10 #fds: 4948 #sysfdlimit: 6815744 #disks: 4 #nics: 4  nicErrors: 0TOP CONSUMERS:topcpu: 'orarootagent.bi(8490) 1.59' topprivmem: 'ologgerd(8257) 83108' topshm: 'oracle(8873) 324868' topfd: 'ohasd.bin(6744) 720' topthread: 'crsd.bin(8362) 47'PROCESSES:name: 'oracle' pid: 9040 #procfdlimit: 65536 cpuusage: 0.19 privmem: 6040 shm: 121712 #fd: 33 #threads: 1 priority: 16 nice: 0...  ??CHM?????,???Oracle????:  http://docs.oracle.com/cd/E11882_01/rac.112/e16794/troubleshoot.htm#CWADD92242  Oracle® Clusterware Administration and Deployment Guide  11g Release 2 (11.2)  Part Number E16794-17  ?? My Oracle Support??:  Cluster Health Monitor (CHM) FAQ (Doc ID 1328466.1)

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  • SQL SERVER – What is Page Life Expectancy (PLE) Counter

    - by pinaldave
    During performance tuning consultation there are plenty of counters and values, I often come across. Today we will quickly talk about Page Life Expectancy counter, which is commonly known as PLE as well. You can find the value of the PLE by running following query. SELECT [object_name], [counter_name], [cntr_value] FROM sys.dm_os_performance_counters WHERE [object_name] LIKE '%Manager%' AND [counter_name] = 'Page life expectancy' The recommended value of the PLE counter is 300 seconds. I have seen on busy system this value to be as low as even 45 seconds and on unused system as high as 1250 seconds. Page Life Expectancy is number of seconds a page will stay in the buffer pool without references. In simple words, if your page stays longer in the buffer pool (area of the memory cache) your PLE is higher, leading to higher performance as every time request comes there are chances it may find its data in the cache itself instead of going to hard drive to read the data. Now check your system and post back what is this counter value for you during various time of the day. Is this counter any way relates to performance issues for your system? Note: There are various other counters which are important to discuss during the performance tuning and this counter is not everything. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • EPM 11.1.1 - EPM Infrastructure Tuning Guide v11.1.1.3

    - by Ahmed Awan
    This edition applies to EPM 9.3.1, 11.1.1.1, 11.1.1.2 & 11.1.1.3 only. INTRODUCTION:One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle EPM System performance, all components need to be monitored, analyzed, and tuned. This guide describe the techniques used to monitor performance and the techniques for optimizing the performance of EPM components. Click to Download the EPM 11.1.1.3 Infrastructure Tuning Whitepaper (Right click or option-click the link and choose "Save As..." to download this file)

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  • SQL Profiler: Read/Write units

    - by Ian Boyd
    i've picked a query out of SQL Server Profiler that says it took 1,497 reads: EventClass: SQL:BatchCompleted TextData: SELECT Transactions.... CPU: 406 Reads: 1497 Writes: 0 Duration: 406 So i've taken this query into Query Analyzer, so i may try to reduce the number of reads. But when i turn on SET STATISTICS IO ON to see the IO activity for the query, i get nowhere close to one thousand reads: Table Scan Count Logical Reads =================== ========== ============= FintracTransactions 4 20 LCDs 2 4 LCTs 2 4 FintracTransacti... 0 0 Users 1 2 MALs 0 0 Patrons 0 0 Shifts 1 2 Cages 1 1 Windows 1 3 Logins 1 3 Sessions 1 6 Transactions 1 7 Which if i do my math right, there is a total of 51 reads; not 1,497. So i assume Reads in SQL Profiler is an arbitrary metric. Does anyone know the conversion of SQL Server Profiler Reads to IO Reads? See also SQL Profiler CPU / duration unit Query Analyzer VS. Query Profiler Reads, Writes, and Duration Discrepencies

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  • LINQ To objects: Quicker ideas?

    - by SDReyes
    Do you see a better approach to obtain and concatenate item.Number in a single string? Current: var numbers = new StringBuilder( ); // group is the result of a previous group by var basenumbers = group.Select( item => item.Number ); basenumbers.Aggregate ( numbers, ( res, element ) => res.AppendFormat( "{0:00}", element ) );

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  • Logging library for (c++) games

    - by Klaim
    I know a lot of logging libraries but didn't test a lot of them. (GoogleLog, Pantheios, the coming boost::log library...) In games, especially in remote multiplayer and multithreaded games, logging is vital to debugging, even if you remove all logs in the end. Let's say I'm making a PC game (not console) that needs logs (multiplayer and multithreaded and/or multiprocess) and I have good reasons for looking for a library for logging (like, I don't have time or I'm not confident in my ability to write one correctly for my case). Assuming that I need : performance ease of use (allow streaming or formating or something like that) reliable (don't leak or crash!) cross-platform (at least Windows, MacOSX, Linux/Ubuntu) Wich logging library would you recommand? Currently, I think that boost::log is the most flexible one (you can even log to remotely!), but have not good performance update: is for high performance, but isn't released yet. Pantheios is often cited but I don't have comparison points on performance and usage. I've used my own lib for a long time but I know it don't manage multithreading so it's a big problem, even if it's fast enough. Google Log seems interesting, I just need to test it but if you already have compared those libs and more, your advice might be of good use. Games are often performance demanding while complex to debug so it would be good to know logging libraries that, in our specific case, have clear advantages.

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  • Data in two databases, eager spool resulting in query

    - by Valkyrie
    I have two databases in SQL2k5: one that holds a large amount of static data (SQL Database 1) (never updated but frequently inserted into) and one that holds relational data (SQL Database 2) related to the static data. They're separated mainly because of corporate guidelines and business requirements: assume for the following problem that combining them is not practical. There are places in SQLDB2 that PKs in SQLDB1 are referenced; triggers control the referential integrity, since cross-database relationships are troublesome in SQL Server. BUT, because of the large amount of data in SQLDB1, I'm getting eager spools on queries that join from the Id in SQLDB2 that references the data in SQLDB1. (With me so far? Maybe an example will help:) SELECT t.Id, t.Name, t2.Company FROM SQLDB1.table t INNER JOIN SQLDB2.table t2 ON t.Id = t2.FKId This query results in a eager spool that's 84% of the load of the query; the table in SQLDB1 has 35M rows, so it's completely choking this query. I can't create a view on the table in SQLDB1 and use that as my FK/index; it doesn't want me to create a constraint based on a view. Anyone have any idea how I can fix this huge bottleneck? (Short of putting the static data in the first db: believe me, I've argued that one until I'm blue in the face to no avail.) Thanks! valkyrie Edit: also can't create an indexed view because you can't put schemabinding on a view that references a table outside the database where the view resides. Dang it.

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  • Oracle T4CPreparedStatement memory leaks?

    - by Jay
    A little background on the application that I am gonna talk about in the next few lines: XYZ is a data masking workbench eclipse RCP application: You give it a source table column, and a target table column, it would apply a trasformation (encryption/shuffling/etc) and copy the row data from source table to target table. Now, when I mask n tables at a time, n threads are launched by this app. Here is the issue: I have run into a production issue on first roll out of the above said app. Unfortunately, I don't have any logs to get to the root. However, I tried to run this app in test region and do a stress test. When I collected .hprof files and ran 'em through an analyzer (yourKit), I noticed that objects of oracle.jdbc.driver.T4CPreparedStatement was retaining heap. The analysis also tells me that one of my classes is holding a reference to this preparedstatement object and thereby, n threads have n such objects. T4CPreparedStatement seemed to have character arrays: lastBoundChars and bindChars each of size char[300000]. So, I researched a bit (google!), obtained ojdbc6.jar and tried decompiling T4CPreparedStatement. I see that T4CPreparedStatement extends OraclePreparedStatement, which dynamically manages array size of lastBoundChars and bindChars. So, my questions here are: Have you ever run into an issue like this? Do you know the significance of lastBoundChars / bindChars? I am new to profiling, so do you think I am not doing it correct? (I also ran the hprofs through MAT - and this was the main identified issue - so, I don't really think I could be wrong?) I have found something similar on the web here: http://forums.oracle.com/forums/thread.jspa?messageID=2860681 Appreciate your suggestions / advice.

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  • Free eBook with SQL Server performance tips and nuggets

    - by Claire Brooking
    I’ve often found that the kind of tips that turn out to be helpful are the ones that encourage me to make a small step outside of a routine. No dramatic changes – just a quick suggestion that changes an approach. As a languages student at university, one of the best I spotted came from outside the lecture halls and ended up saving me time (and lots of huffing and puffing) – the use of a rainbow of sticky notes for well-used pages and letter categories in my dictionary. Simple, but armed with a heavy dictionary that could double up as a step stool, those markers were surprisingly handy. When the Simple-Talk editors told me about a book they were planning that would give a series of tips for developers on how to improve database performance, we all agreed it needed to contain a good range of pointers for big-hitter performance topics. But we wanted to include some of the smaller, time-saving nuggets too. We hope we’ve struck a good balance. The 45 Database Performance Tips eBook covers different tips to help you avoid code that saps performance, whether that’s the ‘gotchas’ to be aware of when using Object to Relational Mapping (ORM) tools, or what to be aware of for indexes, database design, and T-SQL. The eBook is also available to download with SQL Prompt from Red Gate. We often hear that it’s the productivity-boosting side of SQL Prompt that makes it useful for everyday coding. So when a member of the SQL Prompt team mentioned an idea to make the most of tab history, a new feature in SQL Prompt 6 for SQL Server Management Studio, we were intrigued. Now SQL Prompt can save tabs we have been working on in SSMS as a way to maintain an active template for queries we often recycle. When we need to reuse the same code again, we search for our saved tab (and we can also customize its name to speed up the search) to get started. We hope you find the eBook helpful, and as always on Simple-Talk, we’d love to hear from you too. If you have a performance tip for SQL Server you’d like to share, email Melanie on the Simple-Talk team ([email protected]) and we’ll publish a collection in a follow-up post.

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  • When is assembler faster than C?

    - by Adam Bellaire
    One of the stated reasons for knowing assembler is that, on occasion, it can be employed to write code that will be more performant than writing that code in a higher-level language, C in particular. However, I've also heard it stated many times that although that's not entirely false, the cases where assembler can actually be used to generate more performant code are both extremely rare and require expert knowledge of and experience with assembler. This question doesn't even get into the fact that assembler instructions will be machine-specific and non-portable, or any of the other aspects of assembler. There are plenty of good reasons for knowing assembler besides this one, of course, but this is meant to be a specific question soliciting examples and data, not an extended discourse on assembler versus higher-level languages. Can anyone provide some specific examples of cases where assembler will be faster than well-written C code using a modern compiler, and can you support that claim with profiling evidence? I am pretty confident these cases exist, but I really want to know exactly how esoteric these cases are, since it seems to be a point of some contention.

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  • How to scale MySQL with multiple machines?

    - by erotsppa
    I have a web app running LAMP. We recently have an increase in load and is now looking at solutions to scale. Scaling apache is pretty easy we are just going to have multiple multiple machines hosting it and round robin the incoming traffic. However, each instance of apache will talk with MySQL and eventually MySQL will be overloaded. How to scale MySQL across multiple machines in this setup? I have already looked at this but specifically we need the updates from the DB available immediately so I don't think replication is a good strategy here? Also hopefully this can be done with minimal code change. PS. We have around a 1:1 read-write ratio.

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  • SQL SERVER – BI Quiz Hint – Performance Tuning Cubes – Hints

    - by pinaldave
    I earlier wrote about SQL BI Quiz over here and here. The details of the quiz is here: Working with huge data is very common when it is about Data Warehousing. It is necessary to create Cubes on the data to make it meaningful and consumable. There are cases when retrieving the data from cube takes lots of the time. Let us assume that your cube is returning you data very quickly. Suddenly on one day it is returning the data very slowly. What are the three things will you to diagnose this. After diagnose what you will do to resolve performance issue. Participate in my question over here I required BI Expert Jason Thomas to help with few hints to blog readers. He is one of the leading SSAS expert and writes a complicated subject in simple words. If queries were executing properly before but now take a long time to return the data, it means that there has been a change in the environment in which it is running. Some possible changes are listed below:-  1) Data factors:- Compare the data size then and now. Increase in data can result in different execution times. Poorly written queries as well as poor design will not start showing issues till the data grows. How to find it out? (Ans : SQL Server profiler and Perfmon Counters can be used for identifying the issues and performance  tuning the MDX queries)  2) Internal Factors:- Is some slow MDX query / multiple mdx queries running at the same time, which was not running when you had tested it before? Is there any locking happening due to proactive caching or processing operations? Are the measure group caches being cleared by processing operations? (Ans : Again, profiler and perfmon counters will help in finding it out. Load testing can be done using AS Performance Workbench (http://asperfwb.codeplex.com/) by running multiple queries at once)  3) External factors:- Is some other application competing for the same resources?  HINT : Read “Identifying and Resolving MDX Query Performance Bottlenecks in SQL Server 2005 Analysis Services” (http://sqlcat.com/whitepapers/archive/2007/12/16/identifying-and-resolving-mdx-query-performance-bottlenecks-in-sql-server-2005-analysis-services.aspx) Well, these are great tips. Now win big prizes by participate in my question over here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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

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

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  • NSMutableArray Vs Stack

    - by Chandan Shetty SP
    I am developing 2D game for iphone in Objectice-C.In this project I need to use stack, I can do it using STL(Standard template library) stacks or NSMutableArray, since this stack is widely used in the game which one is more efficient? @interface CarElement : NSObject { std::stack<myElement*> *mBats; } or @interface CarElement : NSObject { NSMutableArray *mBats; } Thanks,

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  • Mysql 100% CPU + Slow query

    - by felipeclopes
    I'm using the RDS database from amazon with a some very big tables, and yesterday I started to face 100% CPU utilisation on the server and a bunch of slow query logs that were not happening before. I tried to check the queries that were running and faced this result from the explain command +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ | 1 | SIMPLE | businesses | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index; Using temporary; Using filesort | | 1 | SIMPLE | activities_businesses | ref | PRIMARY,index_activities_users_on_business_id,index_tweets_users_on_tweet_id_and_business_id | index_activities_users_on_business_id | 9 | const | 2252 | Using index condition; Using where | | 1 | SIMPLE | activities_b_taggings_975e9c4 | ref | taggings_idx | taggings_idx | 782 | const,myapp_production.activities_businesses.id,const | 1 | Using index condition; Using where | | 1 | SIMPLE | activities | eq_ref | PRIMARY,index_activities_on_created_at | PRIMARY | 8 | myapp_production.activities_businesses.activity_id | 1 | Using where | +----+-------------+-------------------------------+--------+----------------------------------------------------------------------------------------------+---------------------------------------+---------+-----------------------------------------------------------------+------+----------------------------------------------+ Also checkin in the process list, I got something like this: +----+-----------------+-------------------------------------+----------------------------+---------+------+--------------+------------------------------------------------------------------------------------------------------+ | Id | User | Host | db | Command | Time | State | Info | +----+-----------------+-------------------------------------+----------------------------+---------+------+--------------+------------------------------------------------------------------------------------------------------+ | 1 | my_app | my_ip:57152 | my_app_production | Sleep | 0 | | NULL | | 2 | my_app | my_ip:57153 | my_app_production | Sleep | 2 | | NULL | | 3 | rdsadmin | localhost:49441 | NULL | Sleep | 9 | | NULL | | 6 | my_app | my_other_ip:47802 | my_app_production | Sleep | 242 | | NULL | | 7 | my_app | my_other_ip:47807 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 8 | my_app | my_other_ip:47809 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 9 | my_app | my_other_ip:47810 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 10 | my_app | my_other_ip:47811 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | | 11 | my_app | my_other_ip:47813 | my_app_production | Query | 231 | Sending data | SELECT my_fields... | ... So based on the numbers, it looks like there is no reason to have a slow query, since the worst execution plan is the one that goes through 2k rows which is not much. Edit 1 Another information that might be useful is the slow query_log SET timestamp=1401457485; SELECT my_query... # User@Host: myapp[myapp] @ ip-10-195-55-233.ec2.internal [IP] Id: 435 # Query_time: 95.830497 Lock_time: 0.000178 Rows_sent: 0 Rows_examined: 1129387 Edit 2 After profiling, I got this result. The result have approximately 250 rows with two columns each. +----------------------+----------+ | state | duration | +----------------------+----------+ | Sending data | 272 | | removing tmp table | 0 | | optimizing | 0 | | Creating sort index | 0 | | init | 0 | | cleaning up | 0 | | executing | 0 | | checking permissions | 0 | | freeing items | 0 | | Creating tmp table | 0 | | query end | 0 | | statistics | 0 | | end | 0 | | System lock | 0 | | Opening tables | 0 | | logging slow query | 0 | | Sorting result | 0 | | starting | 0 | | closing tables | 0 | | preparing | 0 | +----------------------+----------+ Edit 3 Adding query as requested SELECT activities.share_count, activities.created_at FROM `activities_businesses` INNER JOIN `businesses` ON `businesses`.`id` = `activities_businesses`.`business_id` INNER JOIN `activities` ON `activities`.`id` = `activities_businesses`.`activity_id` JOIN taggings activities_b_taggings_975e9c4 ON activities_b_taggings_975e9c4.taggable_id = activities_businesses.id AND activities_b_taggings_975e9c4.taggable_type = 'ActivitiesBusiness' AND activities_b_taggings_975e9c4.tag_id = 104 AND activities_b_taggings_975e9c4.created_at >= '2014-04-30 13:36:44' WHERE ( businesses.id = 1 ) AND ( activities.created_at > '2014-04-30 13:36:44' ) AND ( activities.created_at < '2014-05-30 12:27:03' ) ORDER BY activities.created_at; Edit 4 There may be a chance that the indexes are not being applied due to difference in column type between the taggings and the activities_businesses, on the taggable_id column. mysql> SHOW COLUMNS FROM activities_businesses; +-------------+------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | activity_id | bigint(20) | YES | MUL | NULL | | | business_id | bigint(20) | YES | MUL | NULL | | +-------------+------------+------+-----+---------+----------------+ 3 rows in set (0.01 sec) mysql> SHOW COLUMNS FROM taggings; +---------------+--------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +---------------+--------------+------+-----+---------+----------------+ | id | int(11) | NO | PRI | NULL | auto_increment | | tag_id | int(11) | YES | MUL | NULL | | | taggable_id | bigint(20) | YES | | NULL | | | taggable_type | varchar(255) | YES | | NULL | | | tagger_id | int(11) | YES | | NULL | | | tagger_type | varchar(255) | YES | | NULL | | | context | varchar(128) | YES | | NULL | | | created_at | datetime | YES | | NULL | | +---------------+--------------+------+-----+---------+----------------+ So it is examining way more rows than it shows in the explain query, probably because some indexes are not being applied. Do you guys can help m with that?

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  • Divide and conquer method to compute roots [SOLVED]

    - by hellsoul153
    Hello, Knowing that we can use Divide-and-Conquer algorithm to compute large exponents, for exemple 2 exp 100 = 2 exp(50) * 2 exp(50), which is quite more efficient, is this method efficient using roots ? For exemple 2 exp (1/100) = (2 exp(1/50)) exp(1/50) ? In other words, I'm wondering if (n exp(1/x)) is more efficient to (n exp(1/y)) for x < y and where x and y are integers.

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