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  • Sabre Manages Fast Data Growth with Oracle Data Integration Products

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Last year at OpenWorld we announced Sabre Holding as a winner of the Fusion Middleware Innovation Awards. The Sabre team did an excellent job at leveraging cutting edge technologies for managing rapid data growth and exponential scalability demands they have experienced in the travel industry. Today we announced the details and specific benefits of Sabre’s new real-time data integration solution in a press release. Please take a look if you haven’t seen it yet. Sabre Holdings Deploys Oracle Data Integrator and Oracle GoldenGate to Support Rapid Customer Growth There are 3 different areas of benefits Sabre achieved by using Oracle Data Integration products: Manages 7X increase in data sources for the enterprise data warehouse Reduced infrastructure complexity Decreased time to market for new products and services by 30 percent. This simply shows that using latest technologies helps the companies to innovate robust solutions against today’s key data management challenges. And the benefit of using a next generation data integration technology is not only seen in the IT operations, but also in the business side. A better data integration solution for the enterprise data warehouse delivered the platform they need to accelerate how they service their customers, improving their competitive advantage. Tomorrow I will give another great example of innovation with next generation data integration from Oracle. We will be discussing the Fusion Middleware Innovation Awards 2012 winners and their results with using Oracle’s data integration products.

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  • implementing dynamic query handler on historical data

    - by user2390183
    EDIT : Refined question to focus on the core issue Context: I have historical data about property (house) sales collected from various sources in a centralized/cloud data source (assume info collection is handled by a third party) Planning to develop an application to query and retrieve data from this centralized data source Example Queries: Simple : for given XYZ post code, what is average house price for 3 bed room house? Complex: What is estimated price for an house at "DD,Some Street,XYZ Post Code" (worked out from average values of historic data filtered by various characteristics of the house: house post code, no of bed rooms, total area, and other deeper insights like house building type, year of built, features)? In addition to average price, the application should support other property info ** maximum, or minimum price..etc and trend (graph) on a selected property attribute over a period of time**. Hence, the queries should not enforce the search based on a primary key or few fixed fields In other words, queries can be What is the change in 3 Bed Room house price (irrespective of location) over last 30 days? What kind of properties we can get for X price (irrespective of location or house type) The challenge I have is identifying the domain (BI/ Data Analytical or DB Design or DB Query Interface or DW related or something else) this problem (dynamic query on historic data) belong to, so that I can do further exploration My findings so far I could be wrong on the following, so please correct me if you think so I briefly read about BI/Data Analytics - I think it is heavy weight solution for my problem and has scalability issues. DB Design - As I understand RDBMS works well if you know Data model at design time. I am expecting attributes about property or other entity (user) that am going to bring in, would evolve quickly. hence maintenance would be an issue. As I am going to have multiple users executing query at same time, performance would be a bottleneck Other options like Graph DB (http://www.tinkerpop.com/) seems to be bit complex (they are good. but using those tools meant for generic purpose, make me think like assembly programming to solve my problem ) BigData related solution are to analyse data from multiple unrelated domains So, Any suggestion on the space this problem fit in ? (Especially if you have design/implementation experience of back-end for property listing or similar portals)

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  • I need some help creating a non-binary tree (or some other data structure that will better solve my problem)

    - by EDO
    I have about ten lists of numbers and some strings. Each list has about <= 30K lines. Each line on a list has a distinct number. I need to build an efficient way of finding all the lines in each list that has the same 'control' number (or key for dB guys) and comparing what is in their string parts. I am writing this in Java. I have thought about using trees but my brain cells are about burnt now. I need some help.

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  • AngularJS dealing with large data sets (Strategy)

    - by Brian
    I am working on developing a personal temperature logging viewer based on my rasppi curl'ing data into my web server's api. Temperatures are taken every 2 seconds and I can have several temperature sensors posting data. Needless to say I will have a lot of data to handle even within the scope of an hour. I have implemented a very simple paging api from the server so the server doesn't timeout and is currently only returning data in 1000 units per call, then paging through the data. I had the idea to intially show say the last 20 minutes of data from a sensor (or all sensors depending on user choices), then allowing the user to select other timeframes from which to show data. The issue comes in when you want to view all sensors or an extended time period (say 24 hours). Is there a best practice of handling this large amount of data? Would it be useful to load those first 20 minutes into the live view and then cache into local storage something like the last 24 hours? I haven't been able to find a decent idea of this in use yet even though there are a lot of ways to take this problem. I am just looking for some suggestions as to what might provide a good balance between good performance and not caching the entire data set on the client side (as beyond a week of data this might not be feasible).

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  • replacing data.frame element-wise operations with data.table (that used rowname)

    - by Harold
    So lets say I have the following data.frames: df1 <- data.frame(y = 1:10, z = rnorm(10), row.names = letters[1:10]) df2 <- data.frame(y = c(rep(2, 5), rep(5, 5)), z = rnorm(10), row.names = letters[1:10]) And perhaps the "equivalent" data.tables: dt1 <- data.table(x = rownames(df1), df1, key = 'x') dt2 <- data.table(x = rownames(df2), df2, key = 'x') If I want to do element-wise operations between df1 and df2, they look something like dfRes <- df1 / df2 And rownames() is preserved: R> head(dfRes) y z a 0.5 3.1405463 b 1.0 1.2925200 c 1.5 1.4137930 d 2.0 -0.5532855 e 2.5 -0.0998303 f 1.2 -1.6236294 My poor understanding of data.table says the same operation should look like this: dtRes <- dt1[, !'x', with = F] / dt2[, !'x', with = F] dtRes[, x := dt1[,x,]] setkey(dtRes, x) (setkey optional) Is there a more data.table-esque way of doing this? As a slightly related aside, more generally, I would have other columns such as factors in each data.table and I would like to omit those columns while doing the element-wise operations, but still have them in the result. Does this make sense? Thanks!

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  • PHP - post data ends when '&' is in data.

    - by Phil Jackson
    Hi all, im posting data using jquery/ajax and PHP at the backend. Problem being, when I input something like 'Jack & Jill went up the hill' im only recieving 'Jack' when it gets to the backend. I have thrown an error at the frontend before that data is sent which alerts 'Jack & Jill went up the hill'. When I put die(print_r($_POST)); at the very top of my index page im only getting [key] => Jack how can I be loosing the data? I thought It may have been my filter; <?php function filter( $data ) { $data = trim( htmlentities( strip_tags( mb_convert_encoding( $data, 'HTML-ENTITIES', "UTF-8") ) ) ); if ( get_magic_quotes_gpc() ) { $data = stripslashes( $data ); } //$data = mysql_real_escape_string( $data ); return $data; } echo "<xmp>" . filter("you & me") . "</xmp>"; ?> but that returns fine in the test above you &amp; me which is in place after I added die(print_r($_POST));. Can anyone think of how and why this is happening? Any help much appreciated. Regards, Phil.

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  • WPF unwanted grid splitter behaviour

    - by SaphuA
    Hello, I have a simple grid with 3 columns (one of which contains a grid splitter). When resizing the grid and the left column reaches its minimum width, instead of doing nothing it increases the width of the right column. Could anyone help me stop this? I can't set the max width of the right column, because the grid itself also resizes. Here's some sample code that shows the problem. While resizing, move the mouse over the red area: XAML: <Grid DockPanel.Dock="Top" Height="200"> <Grid.ColumnDefinitions> <ColumnDefinition MinWidth="200" Width="*" /> <ColumnDefinition Width="3" /> <ColumnDefinition MinWidth="120" Width="240" /> </Grid.ColumnDefinitions> <Grid.RowDefinitions> <RowDefinition Height="*" /> </Grid.RowDefinitions> <Rectangle Fill="Red" Grid.Row="0" Grid.Column="0" /> <DockPanel LastChildFill="True" Grid.Row="0" Grid.Column="2" > <Rectangle DockPanel.Dock="Right" Width="20" Fill="Blue" /> <Rectangle Fill="Green" /> </DockPanel> <GridSplitter Background="LightGray" Grid.Row="0" Grid.Column="1" Height="Auto" Width="Auto" HorizontalAlignment="Stretch" VerticalAlignment="Stretch" /> </Grid>

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  • Grid does not get auto size wpf

    - by Jasim Khan Afridi
    I have a Grid inside a grid. I want it to to avail maximum size irrespective of window size. Main_Grid should be max width Grid_tool_bar should be max width but infact it is not. I am unable to find the reason. Plz help me out. <Window x:Class="SocialNetworkingApp.MainWindow" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" Title="MainWindow" Background="White" WindowStyle="None" HorizontalAlignment="Stretch" WindowState="Normal" AllowsTransparency="True" WindowStartupLocation="CenterScreen"> <Border Margin="0,0,0,0" BorderBrush="Black" BorderThickness="1,1,1,1" > <Grid x:Name="Main_Grid" Background="White" Width="Auto" Height="Auto" Margin="0,0,0,0" HorizontalAlignment="Left" VerticalAlignment="Top"> <Grid.RowDefinitions> <RowDefinition Height="30" /> <RowDefinition Height="25"/> <RowDefinition Height="50"/> <RowDefinition Height="Auto"/> <RowDefinition Height="20"/> </Grid.RowDefinitions> <Grid.ColumnDefinitions> <ColumnDefinition Width="1*"/> </Grid.ColumnDefinitions> <Grid Name="Title_Bar" Grid.Row="0" VerticalAlignment="Top" ShowGridLines="True" Grid.IsSharedSizeScope="True" MouseDown="Drag_Window" Background="#FF4FA2DA" HorizontalAlignment="Left" Width="766" Height="31"> <Grid.RowDefinitions> <RowDefinition Height="Auto" /> </Grid.RowDefinitions> <Grid.ColumnDefinitions> <ColumnDefinition Width="30"/> <ColumnDefinition Width="Auto"/> <ColumnDefinition Width="120" /> </Grid.ColumnDefinitions> </Grid> </Grid> </Border> </Window>

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  • applying paddingRight to flex grid column not to grid header

    - by Ben
    Whenever I add paddingRight to a column in the flex grid, it adds the padding to the header as well. Is anyone familiar with how I can add paddingRight just to the column and not to the header? Below is the column code where I was specifying the padding. <mx:DataGridColumn width="60" headerText="Type" dataField="Grade" headerStyleName="headerLeft" textAlign="left" draggable="false" resizable="false" headerRenderer="GridHeaderRenderer" paddingRight="5"/>

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  • SQL Developer Debugging, Watches, Smart Data, & Data

    - by thatjeffsmith
    After presenting the SQL Developer PL/SQL debugger for about an hour yesterday at KScope12 in San Antonio, my boss came up and asked, “Now, would you really want to know what the Smart Data panel does?” Apparently I had ‘made up’ my own story about what that panel’s intent is based on my experience with it. Not good Jeff, not good. It was a very small point of my presentation, but I probably should have read the docs. The Smart Data tab displays information about variables, using your Debugger: Smart Data preferences. You can also specify these preferences by right-clicking in the Smart Data window and selecting Preferences. Debugger Smart Data Preferences, control number of variables to display The Smart Data panel auto-inspects the last X accessed variables. So if you have a program with 26 variables, instead of showing you all 26, it will just show you the last two variables that were referenced in your program. If you were to click on the ‘Data’ debug panel, you’ll see EVERYTHING. And if you only want to see a very specific set of values, then you should use Watches. The Smart Data Panel As I step through the code, the variables being tracked change as they are referenced. Only the most recent ones display. This is controlled by the ‘Maximum Locations to Remember’ preference. Step through the code, see the latest variables accessed The Data Panel All variables are displayed. Might be information overload on large PL/SQL programs where you have many dozens or even hundreds of variables to track. Shows everything all the time Watches Watches are added manually and only show what you ask for. Data on Demand – add a watch to track a specific variable Remember, you can interact with your data If you want to do more than just watch, you can mouse-right on a data element, and change the value of the variable as the program is running. This is one of the primary benefits to debugging over using DBMS_OUTPUT to track what’s happening in your program. Change the values while the program is running to test your ‘What if?’ scenarios

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  • SQL – Biggest Concerns in a Data-Driven World

    - by Pinal Dave
    The ongoing chaos over Government Agency’s snooping has ignited a heated debate on privacy of personal data and its use by government and/or other institutions. It has created a feeling of disapproval and distrust among users. This incident proves to be a lesson for companies that are looking to leverage their business using a data driven approach. According to analysts, the goal of gathering personal information should be to deliver benefits to both the parties – the user as well as the data collector(government or business). Using data the right way is crucial, and companies need to deploy the right software applications and systems to ensure that their efforts are well-directed. However, there are various issues plaguing analysts regarding available software, which are highlighted below. According to a InformationWeek 2013 Survey of Analytics, Business Intelligence and Information Management where 541 business technology professionals contributed as respondents, it was discovered that the biggest concern was deemed to be the scarcity of expertise and high costs associated with the same. This concern was voiced by as many as 38% of the participants. A close second came out to be the issue of data warehouse appliance platforms being expensive, with 33% of those present believing it to be a huge roadblock. Another revelation made in this respect was that 31% professionals weren’t even sure how Data Analytics can create business opportunities for them. Another 17% shared that they found data platform technologies such as Hadoop and NoSQL technologies hard to learn. These results clearly pointed out that there are awareness and expertise issues that also need much attention. Unless the demand-supply gap of Business Intelligence professionals well versed in data analysis technologies is met, this divide is going to affect how companies make the most of their BI campaigns. One of the key action points that can be taken to salvage the situation, is to provide training on Data Analytics concepts. Koenig Solutions offer courses on many such technologies including a course on MCSE SQL Server 2012: BI Platform. So it’s time to brush up your skills and get down to work in a data driven world that awaits you ahead. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • display image in a grid using extjs

    - by Abisha
    I am new to extjs. I want to display icon images for each grid elements. can you please healp me anybody? i am getting the image path from an xml file. my code is below. here i am displaying image path. i have to replace it by displaying image. Ext.onReady(function(){ var store = new Ext.data.Store({ url: 'new_frm.xml', reader: new Ext.data.XmlReader({ record: 'message', fields: [{name: 'first'},{name: 'last'},{name: 'company'},{name: 'email'},{name: 'gender'},{name: 'form-file'},{name: 'state'},{name: 'Live'},{name: 'content'}] }) }); var grid = new Ext.grid.GridPanel({ store: store, columns: [ {header: "First Name", width: 120, dataIndex: 'first', sortable: true}, {header: "Last Name", width: 180, dataIndex: 'last', sortable: true}, {header: "Company", width: 115, dataIndex: 'company', sortable: true}, {header: "Email", width: 100, dataIndex: 'email', sortable: true}, {header: "Gender", width: 100, dataIndex: 'gender', sortable: true}, {header: "Photo", width: 100, dataIndex: 'form-file', sortable: true}, {header: "State", width: 100, dataIndex: 'state', sortable: true}, {header: "Living with", width: 100, dataIndex: 'Live', sortable: true}, {header: "Commands", width: 100, dataIndex: 'content', sortable: true} ], renderTo:'example-grid', height:200 }); store.load(); });

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  • trying to make a simple grid-class, non-lvalue in assignment

    - by Tyrfing
    I'm implementing a simple C++ grid class. One Function it should support is accessed through round brackets, so that I can access the elements by writing mygrid(0,0). I overloaded the () operator and i am getting the error message: "non-lvalue in assignment". what I want to be able to do: //main cGrid<cA*> grid(5, 5); grid(0,0) = new cA(); excerpt of my implementation of the grid class: template class cGrid { private: T* data; int mWidth; int mHeight; public: cGrid(int width, int height) : mWidth(width), mHeight(height) { data = new T[width*height]; } ~cGrid() { delete data; } T operator ()(int x, int y) { if (x >= 0 && x <= mWidth) { if (y >= 0 && y <= mHeight) { return data[x + y * mWidth]; } } } const T &operator ()(int x, int y) const { if (x >= 0 && x <= mWidth) { if (y >= 0 && y <= mHeight) { return data[x + y * mWidth]; } } } The rest of the code deals with the implementation of an iterator and should not be releveant.

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  • Find Control inside Grid Row

    - by arpan911
    i m using parent child grid and on child grid i m doing Show / hide threw java script. and child grid i bind run time with Templatecolumns like GridView NewDg = new GridView(); NewDg.ID = "dgdStoreWiseMenuStock"; TemplateField TOTAL = new TemplateField(); TOTAL.HeaderTemplate = new BusinessLogic.GridViewTemplateTextBox(ListItemType.Header, "TOTAL",e.Row.RowIndex ); TOTAL.HeaderStyle.Width = Unit.Percentage(5.00); TOTAL.ItemTemplate = new BusinessLogic.GridViewTemplateTextBox(ListItemType.Item, "TOTAL", e.Row.RowIndex); NewDg.Columns.Add(TOTAL); NewDg.DataSource = ds; NewDg.DataBind(); NewDg.Columns[1].Visible = false; NewDg.Columns[2].Visible = false; System.IO.StringWriter sw = new System.IO.StringWriter(); System.Web.UI.HtmlTextWriter htw = new System.Web.UI.HtmlTextWriter(sw); NewDg.RenderControl(htw); Now I have one TextBox inside Grid named "TOTAL" I want to Find This TextBox and wanna get its value. How can Get it ?

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  • how to write right click event for selected row in ng-grid using angularjs

    - by user3819122
    i am using angularjs to write click event for selected row from ng-grid.but i want to write right click event for selected row from ng-grid in angularjs.below is my sample code for click event for selected row in ng-grid. Sample.html: <html> <body> <div ng-controller="tableController"> <div class="gridStyle" ng-grid="gridOptions"></div> </div> </body> </html> Sample.js: app.controller('tableController', function($scope) { $scope.myData = [{ name: "Moroni", age: 50 }, { name: "Tiancum", age: 43 }, { name: "Jacob", age: 27 }, { name: "Nephi", age: 29 }, { name: "Enos", age: 34 }]; $scope.gridOptions = { data: 'myData', enableRowSelection: true, columnDefs: [{ field: 'name', displayName: 'Name', cellTemplate: '<div ng-click="foo()" ng-bind="row.getProperty(col.field)"></div>' }, { field: 'age', displayName: 'Age', cellTemplate: '<div ng-click="foo()" ng-bind="row.getProperty(col.field)"></div>' } ] }; $scope.foo = function() { alert('select'); } }); please suggest me how to do this.

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  • Jquery grid overlay in wordpress

    - by Anders Kitson
    I am adding this simple plugin that I have working in a static html site, and am trying to add it to a wordpress development site based off of 960 gs. The jquery code links are correct but the console gives me this error "Uncaught TypeError: Cannot call method 'addGrid' of null" I got the code from this turtorial http://www.badlydrawntoy.com/2009/04/21/960gs-grid-overlay-a-jquery-plugin/ Here is the code I am using /*<![CDATA[*/ // onload $(function() { $("body").addGrid(12, {img_path: 'img/'}); }); /*]]>*/ Here is the code for the plugin /* * @ description: Plugin to display 960.gs gridlines See http://960.gs/ * @author: badlyDrawnToy sharp / http://www.badlydrawntoy.com * @license: Creative Commons License - ShareAlike http://creativecommons.org/licenses/by-sa/3.0/ * @version: 1.0 20th April 2009 */ (function($){$.fn.addGrid=function(cols,options){var defaults={default_cols:12,z_index:999,img_path:'/images/',opacity:.6};var opts=$.extend(defaults,options);var cols=cols!=null&&(cols===12||cols===16)?cols:12;var cols=cols===opts.default_cols?'12_col':'16_col';return this.each(function(){var $el=$(this);var height=$el.height();var wrapper=$('<div id="'+opts.grid_id+'"/>').appendTo($el).css({'display':'none','position':'absolute','top':0,'z-index':(opts.z_index-1),'height':height,'opacity':opts.opacity,'width':'100%'});$('<div/>').addClass('container_12').css({'margin':'0 auto','width':'960px','height':height,'background-image':'url('+opts.img_path+cols+'.png)','background-repeat':'repeat-y'}).appendTo(wrapper);$('<div>grid on</div>').appendTo($el).css({'position':'absolute','top':0,'left':0,'z-index':opts.z_index,'background':'#222','color':'#fff','padding':'3px 6px','width':'40px','text-align':'center'}).hover(function(){$(this).css("cursor","pointer");},function(){$(this).css("cursor","default");}).toggle(function(){$(this).text("grid off");$('#'+opts.grid_id).slideDown();},function(){$(this).text("grid on");$('#'+opts.grid_id).slideUp();});});};})(jQuery);

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  • Store XML data in Core Data

    - by ct2k7
    Hi, is there any easy way of store XML data into core data? Currently, my app just pulls the values from the XML file directly, however, this isn't efficient for XML files which holds over 100 entries, thus storing the data in Core Data would be the best option. XML file is called/downloaded/parsed ever time the app opens. With the Core Data, the XML data would be downloaded ever 3600 seconds or so, and refresh the current data in the core data, to reduce the loading time when opening the app. Any ideas on how I can do this? Having reviewed the developer documentation, it doesn't look very tasty.

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  • Where can I find free and open data?

    - by kitsune
    Sooner or later, coders will feel the need to have access to "open data" in one of their projects, from knowing a city's zip to a more obscure information such as the axial tilt of Pluto. I know data.un.org which offers access to the UN's extensive array of databases that deal with human development and other socio-economic issues. The other usual suspects are NASA and the USGS for planetary data. There's an article at readwriteweb with more links. infochimps.org seems to stand out. Personally, I need to find historic commodity prices, stock values and other financial data. All these data sets seem to cost money however. Clarification To clarify, I'm interested in all kinds of open data, because sooner or later, I know I will be in a situation where I could need it. I will try to edit this answer and include the suggestions in a structured manners. A link for financial data was hidden in that readwriteweb article, doh! It's called opentick.com. Looks good so far! Update I stumbled over semantic data in another question of mine on here. There is opencyc ('the world's largest and most complete general knowledge base and commonsense reasoning engine'). A project called UMBEL provides a light-weight, distilled version of opencyc. Umbel has semantic data in rdf/owl/skos n3 syntax. The Worldbank also released a very nice API. It offers data from the last 50 years for about 200 countries

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  • Temporary storage for keeping data between program iterations?

    - by mr.b
    I am working on an application that works like this: It fetches data from many sources, resulting in pool of about 500,000-1,500,000 records (depends on time/day) Data is parsed Part of data is processed in a way to compare it to pre-existing data (read from database), calculations are made, and stored in database. Resulting dataset that has to be stored in database is, however, much smaller in size (compared to original data set), and ranges from 5,000-50,000 records. This process almost always updates existing data, perhaps adds few more records. Then, data from step 2 should be kept somehow, somewhere, so that next time data is fetched, there is a data set which can be used to perform calculations, without touching pre-existing data in database. I should point out that this data can be lost, it's not irreplaceable (key information can be read from database if needed), but it would speed up the process next time. Application components can (and will be) run off different computers (in the same network), so storage has to be reachable from multiple hosts. I have considered using memcached, but I'm not quite sure should I do so, because one record is usually no smaller than 200 bytes, and if I have 1,500,000 records, I guess that it would amount to over 300 MB of memcached cache... But that doesn't seem scalable to me - what if data was 5x that amount? If it were to consume 1-2 GB of cache only to keep data in between iterations (which could easily happen)? So, the question is: which temporary storage mechanism would be most suitable for this kind of processing? I haven't considered using mysql temporary tables, as I'm not sure if they can persist between sessions, and be used by other hosts in network... Any other suggestion? Something I should consider?

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  • Why are data structures so important in interviews?

    - by Vamsi Emani
    I am a newbie into the corporate world recently graduated in computers. I am a java/groovy developer. I am a quick learner and I can learn new frameworks, APIs or even programming languages within considerably short amount of time. Albeit that, I must confess that I was not so strong in data structures when I graduated out of college. Through out the campus placements during my graduation, I've witnessed that most of the biggie tech companies like Amazon, Microsoft etc focused mainly on data structures. It appears as if data structures is the only thing that they expect from a graduate. Adding to this, I see that there is this general perspective that a good programmer is necessarily a one with good knowledge about data structures. To be honest, I felt bad about that. I write good code. I follow standard design patterns of coding, I do use data structures but at the superficial level as in java exposed APIs like ArrayLists, LinkedLists etc. But the companies usually focused on the intricate aspects of Data Structures like pointer based memory manipulation and time complexities. Probably because of my java-ish background, Back then, I understood code efficiency and logic only when talked in terms of Object Oriented Programming like Objects, instances, etc but I never drilled down into the level of bits and bytes. I did not want people to look down upon me for this knowledge deficit of mine in Data Structures. So really why all this emphasis on Data Structures? Does, Not having knowledge in Data Structures really effect one's career in programming? Or is the knowledge in this subject really a sufficient basis to differentiate a good and a bad programmer?

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  • Data structure for pattern matching.

    - by alvonellos
    Let's say you have an input file with many entries like these: date, ticker, open, high, low, close, <and some other values> And you want to execute a pattern matching routine on the entries(rows) in that file, using a candlestick pattern, for example. (See, Doji) And that pattern can appear on any uniform time interval (let t = 1s, 5s, 10s, 1d, 7d, 2w, 2y, and so on...). Say a pattern matching routine can take an arbitrary number of rows to perform an analysis and contain an arbitrary number of subpatterns. In other words, some patterns may require 4 entries to operate on. Say also that the routine (may) later have to find and classify extrema (local and global maxima and minima as well as inflection points) for the ticker over a closed interval, for example, you could say that a cubic function (x^3) has the extrema on the interval [-1, 1]. (See link) What would be the most natural choice in terms of a data structure? What about an interface that conforms a Ticker object containing one row of data to a collection of Ticker so that an arbitrary pattern can be applied to the data. What's the first thing that comes to mind? I chose a doubly-linked circular linked list that has the following methods: push_front() push_back() pop_front() pop_back() [] //overloaded, can be used with negative parameters But that data structure seems very clumsy, since so much pushing and popping is going on, I have to make a deep copy of the data structure before running an analysis on it. So, I don't know if I made my question very clear -- but the main points are: What kind of data structures should be considered when analyzing sequential data points to conform to a pattern that does NOT require random access? What kind of data structures should be considered when classifying extrema of a set of data points?

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  • Grid overlayed on image using javascript, need help getting grid coordinates.

    - by Alos
    Hi I am fairly new to javascript and could use some help, I am trying to overlay a grid on top of an image and then be able to have the user click on the grid and get the grid coordinate from the box that the user clicked. I have been working with the code from the following stackoverflow question: Creating a grid overlay over image. link text Here is the code that I have so far: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> </script> <script type="text/javascript"> var SetGrid = function(el, sz, nr, nc){ //get number of rows/columns according to the 'grid' size //numcols = el.getSize().x/sz; //numrows = el.getSize().y/sz; numcols = 48; numrows = 32; //create table element for injecting cols/rows var gridTable = new Element('table', { 'id' : 'gridTable', 'styles' : { 'width' : el.getSize().x, 'height' : el.getSize().y, 'top' : el.getCoordinates().top, 'left' : el.getCoordinates().left } }); //inject rows/cols into gridTable for (row = 1; row<=numrows; row++){ thisRow = new Element('tr', { 'id' : row, 'class' : 'gridRow' }); for(col = 1; col<=numcols; col++){ thisCol = new Element('td', { 'id' : col, 'class' : 'gridCol0' }); //each cell gets down/up over event... down starts dragging|up stops|over draws area if down was fired thisCol.addEvents({ 'mousedown' : function(){ dragFlag = true; startRow = this.getParent().get('id'); startCol = this.get('id'); }, 'mouseup' : function(){ dragFlag = false; }, 'mouseover' : function(){ if (dragFlag==true){ this.set('class', 'gridCol'+$$('#lvlSelect .on').get('value')); } }, 'click' : function(){ //this.set('class', 'gridCol'+$$('#lvlSelect .on').get('id').substr(3, 1) ); str = $$('#lvlSelect .on').get('id'); alert(str.substr(2, 3)); } }); thisCol.inject(thisRow, 'bottom'); }; thisRow.inject(gridTable, 'bottom'); }; gridTable.inject(el.getParent()); } //sens level selector func var SetSensitivitySelector = function(el, sz, nr, nc){ $$('#lvlSelect ul li').each(function(el){ el.addEvents({ 'click' : function(){ $$('#lvlSelect ul li').set('class', ''); this.set('class', 'on'); }, 'mouseover' : function(){ el.setStyle('cursor','pointer'); }, 'mouseout' : function(){ el.setStyle('cursor',''); } }); }); } //execute window.addEvent('load', function(){ SetGrid($('imagetomap'), 32); SetSensitivitySelector(); }); var gridSize = { x: 48, y: 32 }; var img = document.getElementById('imagetomap'); img.onclick = function(e) { if (!e) e = window.event; alert(Math.floor(e.offsetX/ gridSize.x) + ', ' + Math.floor(e.offsetY / gridSize.y)); } </script> <style> #imagetomapdiv { float:left; display: block; } #gridTable { border:1px solid red; border-collapse:collapse; position:absolute; z-index:5; } #gridTable td { opacity:0.2; filter:alpha(opacity=20); } #gridTable .gridCol0 { border:1px solid gray; background-color: none; } #gridTable .gridCol1 { border:1px solid gray; background-color: green; } #gridTable .gridCol2 { border:1px solid gray; background-color: blue; } #gridTable .gridCol3 { border:1px solid gray; background-color: yellow; } #gridTable .gridCol4 { border:1px solid gray; background-color: orange; } #gridTable .gridCol5 { border:1px solid gray; background-color: red; } #lvlSelect ul {float: left; display:block; position:relative; margin-left: 20px; padding: 10px; } #lvlSelect ul li { width:40px; text-align:center; display:block; border:1px solid black; position:relative; padding: 10px; list-style:none; opacity:0.2; filter:alpha(opacity=20); } #lvlSelect ul li.on { opacity:1; filter:alpha(opacity=100); } #lvlSelect ul #li0 { background-color: none; } #lvlSelect ul #li1 { background-color: green; } #lvlSelect ul #li2 { background-color: blue; } #lvlSelect ul #li3 { background-color: yellow; } #lvlSelect ul #li4 { background-color: orange; } #lvlSelect ul #li5 { background-color: red; } </style> </div> <div id="lvlSelect"> <ul> <li value="0" id="li0">0</li> <li value="1" id="li1">1</li> <li value="2" id="li2">2</li> <li value="3" id="li3">3</li> <li value="4" id="li4">4</li> <li value="5" id="li5" class="on">5</li> </ul> </div> In this example the grid box changes color when the image is grid box is clicked, but I would like to be able to have the coordinates of the box. Any help would be great. Thank you

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  • Five Key Strategies in Master Data Management

    - by david.butler(at)oracle.com
    Here is a very interesting Profit Magazine article on MDM: A recent customer survey reveals the deleterious effects of data fragmentation. by Trevor Naidoo, December 2010   Across industries and geographies, IT organizations have grown in complexity, whether due to mergers and acquisitions, or decentralized systems supporting functional or departmental requirements. With systems architected over time to support unique, one-off process needs, they are becoming costly to maintain, and the Internet has only further added to the complexity. Data fragmentation has become a key inhibitor in delivering flexible, user-friendly systems. The Oracle Insight team conducted a survey assessing customers' master data management (MDM) capabilities over the past two years to get a sense of where they are in terms of their capabilities. The responses, by 27 respondents from six different industries, reveal five key areas in which customers need to improve their data management in order to get better financial results. 1. Less than 15 percent of organizations surveyed understand the sources and quality of their master data, and have a roadmap to address missing data domains. Examples of the types of master data domains referred to are customer, supplier, product, financial and site. Many organizations have multiple sources of master data with varying degrees of data quality in each source -- customer data stored in the customer relationship management system is inconsistent with customer data stored in the order management system. Imagine not knowing how many places you stored your customer information, and whether a customer's address was the most up to date in each source. In fact, more than 55 percent of the respondents in the survey manage their data quality on an ad-hoc basis. It is important for organizations to document their inventory of data sources and then profile these data sources to ensure that there is a consistent definition of key data entities throughout the organization. Some questions to ask are: How do we define a customer? What is a product? How do we define a site? The goal is to strive for one common repository for master data that acts as a cross reference for all other sources and ensures consistent, high-quality master data throughout the organization. 2. Only 18 percent of respondents have an enterprise data management strategy to ensure that data is treated as an asset to the organization. Most respondents handle data at the department or functional level and do not have an enterprise view of their master data. The sales department may track all their interactions with customers as they move through the sales cycle, the service department is tracking their interactions with the same customers independently, and the finance department also has a different perspective on the same customer. The salesperson may not be aware that the customer she is trying to sell to is experiencing issues with existing products purchased, or that the customer is behind on previous invoices. The lack of a data strategy makes it difficult for business users to turn data into information via reports. Without the key building blocks in place, it is difficult to create key linkages between customer, product, site, supplier and financial data. These linkages make it possible to understand patterns. A well-defined data management strategy is aligned to the business strategy and helps create the governance needed to ensure that data stewardship is in place and data integrity is intact. 3. Almost 60 percent of respondents have no strategy to integrate data across operational applications. Many respondents have several disparate sources of data with no strategy to keep them in sync with each other. Even though there is no clear strategy to integrate the data (see #2 above), the data needs to be synced and cross-referenced to keep the business processes running. About 55 percent of respondents said they perform this integration on an ad hoc basis, and in many cases, it is done manually with the help of Microsoft Excel spreadsheets. For example, a salesperson needs a report on global sales for a specific product, but the product has different product numbers in different countries. Typically, an analyst will pull all the data into Excel, manually create a cross reference for that product, and then aggregate the sales. The exact same procedure has to be followed if the same report is needed the following month. A well-defined consolidation strategy will ensure that a central cross-reference is maintained with updates in any one application being propagated to all the other systems, so that data is synchronized and up to date. This can be done in real time or in batch mode using integration technology. 4. Approximately 50 percent of respondents spend manual efforts cleansing and normalizing data. Information stored in various systems usually follows different standards and formats, making it difficult to match the data. A customer's address can be stored in different ways using a variety of abbreviations -- for example, "av" or "ave" for avenue. Similarly, a product's attributes can be stored in a number of different ways; for example, a size attribute can be stored in inches and can also be entered as "'' ". These types of variations make it difficult to match up data from different sources. Today, most customers rely on manual, heroic efforts to match, cleanse, and de-duplicate data -- clearly not a scalable, sustainable model. To solve this challenge, organizations need the ability to standardize data for customers, products, sites, suppliers and financial accounts; however, less than 10 percent of respondents have technology in place to automatically resolve duplicates. It is no wonder, therefore, that we get communications about products we don't own, at addresses we don't reside, and using channels (like direct mail) we don't like. An all-too-common example of a potential challenge follows: Customers end up receiving duplicate communications, which not only impacts customer satisfaction, but also incurs additional mailing costs. Cleansing, normalizing, and standardizing data will help address most of these issues. 5. Only 10 percent of respondents have the ability to share data that was mastered in a master data hub. Close to 60 percent of respondents have efforts in place that profile, standardize and cleanse data manually, and the output of these efforts are stored in spreadsheets in various parts of the organization. This valuable information is not easily shared with the rest of the organization and, more importantly, this enriched information cannot be sent back to the source systems so that the data is fixed at the source. A key benefit of a master data management strategy is not only to clean the data, but to also share the data back to the source systems as well as other systems that need the information. Aside from the source systems, another key beneficiary of this data is the business intelligence system. Having clean master data as input to business intelligence systems provides more accurate and enhanced reporting.  Characteristics of Stellar MDM When deciding on the right master data management technology, organizations should look for solutions that have four main characteristics: enterprise-grade MDM performance complete technology that can be rapidly deployed and addresses multiple business issues end-to-end MDM process management with data quality monitoring and assurance pre-built MDM business relevant applications with data stores and workflows These master data management capabilities will aid in moving closer to a best-practice maturity level, delivering tremendous efficiencies and savings as well as revenue growth opportunities as a result of better understanding your customers.  Trevor Naidoo is a senior director in Industry Strategy and Insight at Oracle. 

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  • ????????WebLogic Server - Enterprise Grid Messaging |WebLogic Channel|??????

    - by ???02
    WebLogic Server????????????????????????????Enterprise Grid Messaging?????????? ?? ????????????????????????????????????????????????WebLogic Server?Java EE?JMS???JMS????????????JMS???????????????????????????????????????????????????????????????????????????????11gR1???Enterprise Grid Messaging????Oracle Advanced Queuing?Oracle RAC???????????????? ?????Enterprise Grid Messaging????????????????????????? ????¦WebLogic JMS????¦JMS??¦?????????¦?????????¦?????????????????¦Advanced Queue???? ???????????????????????????http://www.oracle.com/technetwork/jp/ondemand/application-grid/wls11g-egm-201107-otn-sc-439529-ja.pdf

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  • Address Regulatory Mandates for Data Encryption Without Changing Your Applications

    - by Troy Kitch
    The Payment Card Industry Data Security Standard, US state-level data breach laws, and numerous data privacy regulations worldwide all call for data encryption to protect personally identifiable information (PII). However encrypting PII data in applications requires costly and complex application changes. Fortunately, since this data typically resides in the application database, using Oracle Advanced Security, PII can be encrypted transparently by the Oracle database without any application changes. In this ISACA webinar, learn how Oracle Advanced Security offers complete encryption for data at rest, in transit, and on backups, along with built-in key management to help organizations meet regulatory requirements and save money. You will also hear from TransUnion Interactive, the consumer subsidiary of TransUnion, a global leader in credit and information management, which maintains credit histories on an estimated 500 million consumers across the globe, about how they addressed PCI DSS encryption requirements using Oracle Database 11g with Oracle Advanced Security. Register to watch the webinar now.

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