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  • how to get large pictures from photo album via facebook graph api

    - by Nav
    I am currently using the following code to retrieve all the photos from a user profile FB.api('/me/albums?fields=id,name', function(response) { //console.log(response.data.length); for (var i = 0; i < response.data.length; i++) { var album = response.data[i]; FB.api('/' + album.id + '/photos', function(photos) { if (photos && photos.data && photos.data.length) { for (var j = 0; j < photos.data.length; j++) { var photo = photos.data[j]; // photo.picture contain the link to picture var image = document.createElement('img'); image.src = photo.picture; document.body.appendChild(image); image.className = "border"; image.onclick = function() { //this.parentNode.removeChild(this); document.getElementById(info.id).src = this.src; document.getElementById(info.id).style.width = "220px"; document.getElementById(info.id).style.height = "126px"; }; } } }); } }); but, the photos that it returns are of poor quality and are basically like thumbnails.How to retrieve larger photos from the albums. Generally for profile picture I use ?type=large which returns a decent profile image but the type=large is not working in the case of photos from photo albums and also is there a way to get the photos in zip format from facebook once I specify the photo url as I want users to be able to download the photos.

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  • Database for managing large volumes of (system) metrics

    - by symcbean
    Hi, I'm looking at building a system for managing and reporting stats on web page performance. I'll be collecting a lot more stats than are available in the standard log formats (approx 20 metrics) but compared to most types of database applications, the base data structure will be very simple. My problem is that I'll be accumulating a lot of data - in the region of 100,000 records (i.e. sets of metrics) per hour. Of course, resources are very limited! So that its possible to sensibly interact with the data, I'd need to consolidate each metric into one minute bins, broken down by URL, then for anything more than 1 day old, consolidated into 10 minute bins, then at 1 week, hourly bins. At the front end, I want to provide a view (prefereably as plots) of the last hour of data, with the facility for users to drill up/down through defined hierarchies of URLs (which do not always map directly to the hierarchy expressed in the path of the URL) and to view different time frames. Rather than coding all this myself and using a relational database, I was wondering if there were tools available which would facilitate both the management of the data and the reporting. I had a look at Mondrian however I can't see from the documentation I've looked at whether it's possible to drop the more granular information while maintaining the consolidated views of the data. RRDTool looks promising in terms of managing the data consolidation, but seems to be rather limited in terms of querying the dataset as a multi-dimensional/relational database. What else whould I be looking at?

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  • Interesting Scala typing solution, doesn't work in 2.7.7?

    - by djc
    I'm trying to build some image algebra code that can work with images (basically a linear pixel buffer + dimensions) that have different types for the pixel. To get this to work, I've defined a parametrized Pixel trait with a few methods that should be able to get used with any Pixel subclass. (For now, I'm only interested in operations that work on the same Pixel type.) Here it is: trait Pixel[T <: Pixel[T]] { def mul(v: Double): T def max(v: T): T def div(v: Double): T def div(v: T): T } Now I define a single Pixel type that has storage based on three doubles (basically RGB 0.0-1.0), I've called it TripleDoublePixel: class TripleDoublePixel(v: Array[Double]) extends Pixel[TripleDoublePixel] { var data: Array[Double] = v def this() = this(Array(0.0, 0.0, 0.0)) def toString(): String = { "(" + data(0) + ", " + data(1) + ", " + data(2) + ")" } def increment(v: TripleDoublePixel) { data(0) += v.data(0) data(1) += v.data(1) data(2) += v.data(2) } def mul(v: Double): TripleDoublePixel = { new TripleDoublePixel(data.map(x => x * v)) } def div(v: Double): TripleDoublePixel = { new TripleDoublePixel(data.map(x => x / v)) } def div(v: TripleDoublePixel): TripleDoublePixel = { var tmp = new Array[Double](3) tmp(0) = data(0) / v.data(0) tmp(1) = data(1) / v.data(1) tmp(2) = data(2) / v.data(2) new TripleDoublePixel(tmp) } def max(v: TripleDoublePixel): TripleDoublePixel = { val lv = data(0) * data(0) + data(1) * data(1) + data(2) * data(2) val vv = v.data(0) * v.data(0) + v.data(1) * v.data(1) + v.data(2) * v.data(2) if (lv > vv) (this) else v } } Now I want to write code to use this, that doesn't have to know what type the pixels are. For example: def idiv[T](a: Image[T], b: Image[T]) { for (i <- 0 until a.data.size) { a.data(i) = a.data(i).div(b.data(i)) } } Unfortunately, this doesn't compile: (fragment of lindet-gen.scala):145: error: value div is not a member of T a.data(i) = a.data(i).div(b.data(i)) I was told in #scala that this worked for someone else, but that was on 2.8. I've tried to get 2.8-rc1 going, but it doesn't compile for me. Is there any way to get this to work in 2.7.7?

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  • PHP : If...Else...Query

    - by Rachel
    I am executing this statement under while (($data=fgetcsv($this->fin,5000,";"))!==FALSE) Now what I want in else loop is to throw exception only for data value which did not satisfy the if condition. Right now am displaying the complete row as I am not sure how to throw exception only for data which does not satisfy the value. Code if ((strtotime($data[11]) &&strtotime($data[12])&&strtotime($data[16]))!==FALSE && ctype_digit($data[0]) && ctype_alnum($data[1]) && ctype_digit($data[2]) && ctype_alnum($data[3]) && ctype_alnum($data[4]) && ctype_alnum($data[5]) && ctype_alnum($data[6]) && ctype_alnum($data[7]) && ctype_alnum($data[8]) && $this->_is_valid($data[9]) && ctype_digit($data[10]) && ctype_digit($data[13]) && $this->_is_valid($data[14])) { //Some Logic } else { throw new Exception ("Data {$data[0], $data[1], $data[2], $data[3], $data[4], $data[5], $data[6], $data[7], $data[8], $data[9], $data[10], $data[11], $data[12], $data[13], $data[14], $data[16]} is not in valid format"); } Guidance would be highly appreciated as to how can I throw exception only for data which did not satisfy the if value.

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  • SQL SERVER – Copy Data from One Table to Another Table – SQL in Sixty Seconds #031 – Video

    - by pinaldave
    Copy data from one table to another table is one of the most requested questions on forums, Facebook and Twitter. The question has come in many formats and there are places I have seen developers are using cursor instead of this direct method. Earlier I have written the similar article a few years ago - SQL SERVER – Insert Data From One Table to Another Table – INSERT INTO SELECT – SELECT INTO TABLE. The article has been very popular and I have received many interesting and constructive comments. However there were two specific comments keep on ending up on my mailbox. 1) SQL Server AdventureWorks Samples Database does not have table I used in the example 2) If there is a video tutorial of the same example. After carefully thinking I decided to build a new set of the scripts for the example which are very similar to the old one as well video tutorial of the same. There was no better place than our SQL in Sixty Second Series to cover this interesting small concept. Let me know what you think of this video. Here is the updated script. -- Method 1 : INSERT INTO SELECT USE AdventureWorks2012 GO ----Create TestTable CREATE TABLE TestTable (FirstName VARCHAR(100), LastName VARCHAR(100)) ----INSERT INTO TestTable using SELECT INSERT INTO TestTable (FirstName, LastName) SELECT FirstName, LastName FROM Person.Person WHERE EmailPromotion = 2 ----Verify that Data in TestTable SELECT FirstName, LastName FROM TestTable ----Clean Up Database DROP TABLE TestTable GO --------------------------------------------------------- --------------------------------------------------------- -- Method 2 : SELECT INTO USE AdventureWorks2012 GO ----Create new table and insert into table using SELECT INSERT SELECT FirstName, LastName INTO TestTable FROM Person.Person WHERE EmailPromotion = 2 ----Verify that Data in TestTable SELECT FirstName, LastName FROM TestTable ----Clean Up Database DROP TABLE TestTable GO Related Tips in SQL in Sixty Seconds: SQL SERVER – Insert Data From One Table to Another Table – INSERT INTO SELECT – SELECT INTO TABLE Powershell – Importing CSV File Into Database – Video SQL SERVER – 2005 – Export Data From SQL Server 2005 to Microsoft Excel Datasheet SQL SERVER – Import CSV File into Database Table Using SSIS SQL SERVER – Import CSV File Into SQL Server Using Bulk Insert – Load Comma Delimited File Into SQL Server SQL SERVER – 2005 – Generate Script with Data from Database – Database Publishing Wizard What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com)   Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Excel

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  • Data Generator Source Adapter

    This component needs little explanation. It generates random integer (DT_I4) and string (DT_WSTR) data and places them in the pipeline. You specify how many columns of each you would like and for any string columns you pass a fixed length value. You then need to specify how many rows in total you require to be generated. This component is used by us to do testing of the pipeline and components downstream. Previously we would have used a script component (as a source) to generate the rows but found ourselves rewriting the code too often so created this component. Screenshots SQL Server 2005 Integration Services SQL Server 2008/2012 Integration Services The component is provided as an MSI file, however to complete the installation, you will have to add the transformation to the Visual Studio toolbox manually. Right-click the toolbox, and select Choose Items.... Select the SSIS Data Flow Items tab, and then check the Data Generator Source from the list. Downloads The Data Generator Source Adapter is available for SQL Server 2005, SQL Server 2008 (includes R2) and SQL Server 2012. Please choose the version to match your SQL Server version, or you can install multiple versions and use them side by side if you have more than one version of SQL Server installed. Data Generator Source Adapter for SQL Server 2005 Data Generator Source Adapter for SQL Server 2008 Data Generator Source Adapter for SQL Server 2012 Version History SQL Server 2012 Version 3.0.0.30 - SQL Server 2012 release. Includes upgrade support for both 2005 and 2008 packages to 2012. (5 Jun 2012) SQL Server 2008 Version 2.0.0.29 - SQL Server 2008 February 2008 CTP. Includes support for upgrade of 2005 packages. Simplified user interface. (4 Mar 2008) Version 2.0.0.27 - SQL Server 2008 November 2007 CTP. String columns will now use the default system code page. Previously string columns always used 1252. (15 Feb 2008) SQL Server 2005 Version 1.1.0.23 - SQL Server 2005 RTM Refresh. SP1 Compatibility Testing. (12 Jun 2006) Version 1.0.0.0 - SQL Server 2005 IDW 16 Sept CTP. Public release. (6 Oct 2005)

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  • Data Governance (Veri Yönetisimi)

    - by Arda Eralp
    Data governance,veri ile ilgili islemler için bir sorumluluklar sistemidir. Bu sistemin temelini ise politikalar, standartlar ve prosedürler olusturur. Sistem politikalar, standartlar ve prosedürler sayesinde verinin ne zaman, hangi sartlar altinda, hangi eylemlerde, hangi yöntemler ile kimler tarafindan kullanilacagina karar verir. Sistemin kurumda basarili bir sekilde islemesi için öncelikle kurumda farkindalik saglanmasi gereklidir. Farkindalik saglandiktan sonra ise kurum governance ve mimari kültürünü benimsemelidir. Ancak bu sartlar altinda sistem basarili bir sekilde isleyebilecektir. Bu sebeplerden dolayidir ki data governance kisa bir süreç degil, aksine kurum varligini sürdürdügü sürece isleyecek olan bir süreçtir. Bu durum bize data governance in bir proje degil bir program oldugunu açiklamaktadir. Programin baslangicinda kurumun ihtiyaçlarinin netlesmesi ve farkindaligin saglanmasi temeldir. Hedef kitle ise, veri ile dogrudan ve ya dolayli olarak iliski içerisinde olan herkesdir. Bu sebeple programin baslangicinda hedef kitleyi içeren ekipler ile toplantilar düzenlenecektir. Bu toplantilar sayesinde hem farkindalik saglanacak hemde ekiplerin ihtiyaçlari birebir ekipler tarafindan aktarilarak netlesecektir. Hedef kitlenin ihtiyaçlari netlestirildikten sonra ise devamli isleyecek olan bu sürecin planlamasi yapilacaktir. Bu sürecin planlanmasinda ihtiyaçlarin önceliklendirilmesi gerekmektedir. Sebebi ise her ekibin ihtiyaçlarinin farkli olabilecegi ve bütün ihtiyaçlara ayni anda karsilik verilemeyebileceginin öngörülmesidir. Bu öngörünün temeli ise ekiplerin ihtiyaçlarinin birbirleriyle olan baglantisidir. Süreç planlamasinda ihtiyaçlarin önceliklendirilmesinin ardindan kurumun büyüklügünün gözönünde bulundurulmasi gerekmedir. Kurumun büyüklügünün önemi ise eger kurum bir bütün olarak ayni anda govern edilemeyecek kadar büyük ise ihtiyaçlari öncelikli olarak bulunan ekipler ile govern edilmesine baslanarak sürecin belirli bir hiz ile bütün kurumda isler hale getirilmesini saglamaktir. Ihtiyaçlar belirlendikten ve ilgili ekipler seçildikten sonra artik programin planlanmasina geçilebilecek. Programin planlama asamasinda öncelikli olarak sürecin asamalarini kontrol edecek ve süreç kurum içerisinde isleyise geçtiginde kontrolü saglayacak olan Data Governance Office in planlanmasidir. Office in planlanmasiyla birlikte süreçteki roller ve bu rollerin sorumluluklari belirlenecektir. Planlama asamasinda Data governance office, roller ve sorumluluklar, güvenlik ve veri saklanan sistemler ele alinacak konulardir. Planlama asamasi tamamlandiginda ise belirlenen ekipler ve ihtiyaçlar dogrultusunda programin isleyis asamasina geçilebilecektir. Isleyis kisminda ekibin ihtiyaçlari dogrultusunda güvenlik konusunda ve veri saklanan sistemler üzerinde çalismalar yapilacaktir. Bu yapilan çalismalar bir süreç olarak dökümante edilecek ve süreç sona erdiginde baska bir ekiple baska bir ihtiyaç dogrultusunda çalisma yapilarak ayni süreç isletilecek ve böylece kurum içesinde ilgili süreçte standartlasma saglanacaktir. Güvenlik konusunda verinin erisim güvenligi ve kullanim güvenligi ele alinacaktir. Veri saklanan sistemler üzerindeki çalismalar ise saklanan sistemlerin program dahilinde belirlenen standartlar ile olusturulmasi ve yönetilmesi saglanacaktir. Isleyis kisminin ardindan ise programin izleme kismina geçilecektir. Bu kisimda artik Data Governance Office olusmus, politikalar, standartlar ve prosedürler belirlenmistir. Ve Data Governance Office çalisanlari rolleri ve sorumluluklari dahilinde programin isleyisini izleyecek ve gerek gördügünde politikalar standartlar ve prosedürler üzerinde degisiklikler yapacaklardir.

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  • SQL 2014 does data the way developers want

    - by Rob Farley
    A post I’ve been meaning to write for a while, good that it fits with this month’s T-SQL Tuesday, hosted by Joey D’Antoni (@jdanton) Ever since I got into databases, I’ve been a fan. I studied Pure Maths at university (as well as Computer Science), and am very comfortable with Set Theory, which undergirds relational database concepts. But I’ve also spent a long time as a developer, and appreciate that that databases don’t exactly fit within the stuff I learned in my first year of uni, particularly the “Algorithms and Data Structures” subject, in which we studied concepts like linked lists. Writing in languages like C, we used pointers to quickly move around data, without a database in sight. Of course, if we had a power failure all this data was lost, as it was only persisted in RAM. Perhaps it’s why I’m a fan of database internals, of indexes, latches, execution plans, and so on – the developer in me wants to be reassured that we’re getting to the data as efficiently as possible. Back when SQL Server 2005 was approaching, one of the big stories was around CLR. Many were saying that T-SQL stored procedures would be a thing of the past because we now had CLR, and that obviously going to be much faster than using the abstracted T-SQL. Around the same time, we were seeing technologies like Linq-to-SQL produce poor T-SQL equivalents, and developers had had a gutful. They wanted to move away from T-SQL, having lost trust in it. I was never one of those developers, because I’d looked under the covers and knew that despite being abstracted, T-SQL was still a good way of getting to data. It worked for me, appealing to both my Set Theory side and my Developer side. CLR hasn’t exactly become the default option for stored procedures, although there are plenty of situations where it can be useful for getting faster performance. SQL Server 2014 is different though, through Hekaton – its In-Memory OLTP environment. When you create a table using Hekaton (that is, a memory-optimized one), the table you create is the kind of thing you’d’ve made as a developer. It creates code in C leveraging structs and pointers and arrays, which it compiles into fast code. When you insert data into it, it creates a new instance of a struct in memory, and adds it to an array. When the insert is committed, a small write is made to the transaction to make sure it’s durable, but none of the locking and latching behaviour that typifies transactional systems is needed. Indexes are done using hashes and using bw-trees (which avoid locking through the use of pointers) and by handling each updates as a delete-and-insert. This is data the way that developers do it when they’re coding for performance – the way I was taught at university before I learned about databases. Being done in C, it compiles to very quick code, and although these tables don’t support every feature that regular SQL tables do, this is still an excellent direction that has been taken. @rob_farley

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  • Strategy for avoiding duplicate object ids for data shared across devices using iCloud

    - by rmaddy
    I have a data intensive iOS app that is not using CoreData nor does it support iCloud synching (yet). All of my objects are created with unique keys. I use a simple long long initialized with the current time. Then as I need a new key I increment the value by 1. This has all worked well for a few years with the app running isolated on a single device. Now I want to add support for automatic data sync across devices using iCloud. As my app is written, there is the possibility that two objects created on two different devices could end up with the same key. I need to avoid this possibility. I'm looking for ideas for solving this issue. I have a few requirements that the solution must meet: 1) The key needs to remain a single integral data type. Converting all existing keys to a compound key or to a string or other type would affect the entire code base and likely result in more bugs than it's worth. 2) The solution can't depend on an Internet connection. A user must be able to run the app and add data even with no Internet connection. The data should still resolve properly later when the data syncs through iCloud once a connection is available. I'll accept one exception to this rule. If no other option is available, I may be open to requiring an Internet connection the first time the app's data is initialized. One idea I have been toying around with in my head is logically splitting the integer key into two parts. The high 4 or 5 bits could be used as some sort of device id while the rest represents the actual key. The fuzzy part is figuring out how to come up with non-conflicting device ids that fit in a few bits. This should be viable since I don't need to deal will millions of devices. I just need to deal with the few devices that would be shared by a given iCloud account. I'm open to suggestions. Thanks.

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  • JGoodies HashMap

    - by JohnMcClane
    Hi, I'm trying to build a chart program using presentation model. Using JGoodies for data binding was relatively easy for simple types like strings or numbers. But I can't figure out how to use it on a hashmap. I'll try to explain how the chart works and what my problem is: A chart consists of DataSeries, a DataSeries consists of DataPoints. I want to have a data model and to be able to use different views on the same model (e.g. bar chart, pie chart,...). Each of them consists of three classes. For example: DataPointModel: holds the data model (value, label, category) DataPointViewModel: extends JGoodies PresentationModel. wraps around DataPointModel and holds view properties like font and color. DataPoint: abstract class, extends JComponent. Different Views must subclass and implement their own ui. Binding and creating the data model was easy, but i don't know how to bind my data series model. package at.onscreen.chart; import java.beans.PropertyChangeListener; import java.beans.PropertyChangeSupport; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.HashMap; import java.util.Iterator; public class DataSeriesModel { public static String PROPERTY_DATAPOINT = "dataPoint"; public static String PROPERTY_DATAPOINTS = "dataPoints"; public static String PROPERTY_LABEL = "label"; public static String PROPERTY_MAXVALUE = "maxValue"; /** * holds the data points */ private HashMap dataPoints; /** * the label for the data series */ private String label; /** * the maximum data point value */ private Double maxValue; /** * the model supports property change notification */ private PropertyChangeSupport propertyChangeSupport; /** * default constructor */ public DataSeriesModel() { this.maxValue = Double.valueOf(0); this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); } /** * constructor * @param label - the series label */ public DataSeriesModel(String label) { this.dataPoints = new HashMap(); this.maxValue = Double.valueOf(0); this.label = label; this.propertyChangeSupport = new PropertyChangeSupport(this); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeriesModel(String label, DataPoint[] dataPoints) { this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); this.maxValue = Double.valueOf(0); this.label = label; for (int i = 0; i < dataPoints.length; i++) { this.addDataPoint(dataPoints[i]); } } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeriesModel(String label, Collection dataPoints) { this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); this.maxValue = Double.valueOf(0); this.label = label; for (Iterator it = dataPoints.iterator(); it.hasNext();) { this.addDataPoint(it.next()); } } /** * adds a new data point to the series. if the series contains a data point with same id, it will be replaced by the new one. * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { String category = dataPoint.getCategory(); DataPoint oldDataPoint = this.getDataPoint(category); this.dataPoints.put(category, dataPoint); this.setMaxValue(Math.max(this.maxValue, dataPoint.getValue())); this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINT, oldDataPoint, dataPoint); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.dataPoints.get(category); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { DataPoint dataPoint = this.getDataPoint(category); this.dataPoints.remove(category); if (dataPoint != null) { if (dataPoint.getValue() == this.getMaxValue()) { Double maxValue = Double.valueOf(0); for (Iterator it = this.iterator(); it.hasNext();) { DataPoint itDataPoint = it.next(); maxValue = Math.max(itDataPoint.getValue(), maxValue); } this.setMaxValue(maxValue); } } this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINT, dataPoint, null); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.setMaxValue(Double.valueOf(0)); this.dataPoints.clear(); this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINTS, this.getDataPoints(), null); } /** * returns the maximum of all data point values * @return the maximum of all data points */ public Double getMaxValue() { return this.maxValue; } /** * sets the max value * @param maxValue - the max value */ protected void setMaxValue(Double maxValue) { Double oldMaxValue = this.getMaxValue(); this.maxValue = maxValue; this.propertyChangeSupport.firePropertyChange(PROPERTY_MAXVALUE, oldMaxValue, maxValue); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.dataPoints.containsKey(category); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.label; } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.dataPoints.values().iterator(); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.dataPoints.values(); } /** * returns the number of data points in the series * @return the number of data points */ public int getSize() { return this.dataPoints.size(); } /** * adds a PropertyChangeListener * @param listener - the listener */ public void addPropertyChangeListener(PropertyChangeListener listener) { this.propertyChangeSupport.addPropertyChangeListener(listener); } /** * removes a PropertyChangeListener * @param listener - the listener */ public void removePropertyChangeListener(PropertyChangeListener listener) { this.propertyChangeSupport.removePropertyChangeListener(listener); } } package at.onscreen.chart; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.Iterator; import com.jgoodies.binding.PresentationModel; public class DataSeriesViewModel extends PresentationModel { /** * default constructor */ public DataSeriesViewModel() { super(new DataSeriesModel()); } /** * constructor * @param label - the series label */ public DataSeriesViewModel(String label) { super(new DataSeriesModel(label)); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeriesViewModel(String label, DataPoint[] dataPoints) { super(new DataSeriesModel(label, dataPoints)); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeriesViewModel(String label, Collection dataPoints) { super(new DataSeriesModel(label, dataPoints)); } /** * full constructor * @param model - the data series model */ public DataSeriesViewModel(DataSeriesModel model) { super(model); } /** * adds a data point to the series * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { this.getBean().addDataPoint(dataPoint); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.getBean().contains(category); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.getBean().getDataPoint(category); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.getBean().getDataPoints(); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.getBean().getLabel(); } /** * sets the max value * @param maxValue - the max value */ public Double getMaxValue() { return this.getBean().getMaxValue(); } /** * returns the number of data points in the series * @return the number of data points */ public int getSize() { return this.getBean().getSize(); } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.getBean().iterator(); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.getBean().removeAll(); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { this.getBean().removeDataPoint(category); } } package at.onscreen.chart; import java.beans.PropertyChangeEvent; import java.beans.PropertyChangeListener; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.Iterator; import javax.swing.JComponent; public abstract class DataSeries extends JComponent implements PropertyChangeListener { /** * the model */ private DataSeriesViewModel model; /** * default constructor */ public DataSeries() { this.model = new DataSeriesViewModel(); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * constructor * @param label - the series label */ public DataSeries(String label) { this.model = new DataSeriesViewModel(label); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeries(String label, DataPoint[] dataPoints) { this.model = new DataSeriesViewModel(label, dataPoints); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeries(String label, Collection dataPoints) { this.model = new DataSeriesViewModel(label, dataPoints); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param model - the model */ public DataSeries(DataSeriesViewModel model) { this.model = model; this.model.addPropertyChangeListener(this); this.createComponents(); } /** * creates, binds and configures UI components. * data point properties can be created here as components or be painted in paintComponent. */ protected abstract void createComponents(); @Override public void propertyChange(PropertyChangeEvent evt) { this.repaint(); } /** * adds a data point to the series * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { this.model.addDataPoint(dataPoint); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.model.contains(category); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.model.getDataPoint(category); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.model.getDataPoints(); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.model.getLabel(); } /** * sets the max value * @param maxValue - the max value */ public Double getMaxValue() { return this.model.getMaxValue(); } /** * returns the number of data points in the series * @return the number of data points */ public int getDataPointCount() { return this.model.getSize(); } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.model.iterator(); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.model.removeAll(); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { this.model.removeDataPoint(category); } /** * returns the data series view model * @return - the data series view model */ public DataSeriesViewModel getViewModel() { return this.model; } /** * returns the data series model * @return - the data series model */ public DataSeriesModel getModel() { return this.model.getBean(); } } package at.onscreen.chart.builder; import java.util.Collection; import net.miginfocom.swing.MigLayout; import at.onscreen.chart.DataPoint; import at.onscreen.chart.DataSeries; import at.onscreen.chart.DataSeriesViewModel; public class BuilderDataSeries extends DataSeries { /** * default constructor */ public BuilderDataSeries() { super(); } /** * constructor * @param label - the series label */ public BuilderDataSeries(String label) { super(label); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public BuilderDataSeries(String label, DataPoint[] dataPoints) { super(label, dataPoints); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public BuilderDataSeries(String label, Collection dataPoints) { super(label, dataPoints); } /** * full constructor * @param model - the model */ public BuilderDataSeries(DataSeriesViewModel model) { super(model); } @Override protected void createComponents() { this.setLayout(new MigLayout()); /* * * I want to add a new BuilderDataPoint for each data point in the model. * I want the BuilderDataPoints to be synchronized with the model. * e.g. when a data point is removed from the model, the BuilderDataPoint shall be removed * from the BuilderDataSeries * */ } } package at.onscreen.chart.builder; import javax.swing.JFormattedTextField; import javax.swing.JTextField; import at.onscreen.chart.DataPoint; import at.onscreen.chart.DataPointModel; import at.onscreen.chart.DataPointViewModel; import at.onscreen.chart.ValueFormat; import com.jgoodies.binding.adapter.BasicComponentFactory; import com.jgoodies.binding.beans.BeanAdapter; public class BuilderDataPoint extends DataPoint { /** * default constructor */ public BuilderDataPoint() { super(); } /** * constructor * @param category - the category */ public BuilderDataPoint(String category) { super(category); } /** * constructor * @param value - the value * @param label - the label * @param category - the category */ public BuilderDataPoint(Double value, String label, String category) { super(value, label, category); } /** * full constructor * @param model - the model */ public BuilderDataPoint(DataPointViewModel model) { super(model); } @Override protected void createComponents() { BeanAdapter beanAdapter = new BeanAdapter(this.getModel(), true); ValueFormat format = new ValueFormat(); JFormattedTextField value = BasicComponentFactory.createFormattedTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_VALUE), format); this.add(value, "w 80, growx, wrap"); JTextField label = BasicComponentFactory.createTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_LABEL)); this.add(label, "growx, wrap"); JTextField category = BasicComponentFactory.createTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_CATEGORY)); this.add(category, "growx, wrap"); } } To sum it up: I need to know how to bind a hash map property to JComponent.components property. JGoodies is in my opinion not very well documented, I spent a long time searching through the internet, but I did not find any solution to my problem. Hope you can help me.

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  • NHibernate - Stream large result sets?

    - by Dan Black
    Hi, I have to read in a large record set, process it, then write it out to a flat file. The large result set comes from a Stored Proc in SQL 2000. I currently have: var results = session.CreateSQLQuery("exec usp_SalesExtract").List(); I would like to be able to read the result set row by row, to reduce the memory foot print Thanks

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  • iPhone plist data, large amounts of text and return key?

    - by user278342
    Basicly iv built my app using a plist. But with the data there is a few times when I need to press return and start a new line. The return key doesn't work in the plist. If I did it the older way it would be \n\n but that doesn't work either. Is there a obvious way I'm overlooking? Or will it be a case off just pressing the space bar allot? Thanks

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  • how to make data that download from google-app-engine readable..

    - by zjm1126
    i use this to download all data from my google app: i follow this article: http://code.google.com/intl/en/appengine/docs/python/tools/uploadingdata.html#Creating_Exporter_Classes and download data use this: bulkloader.py --dump --url=http://zjm1126.appspot.com/remote_api --filename=b.csv but the data is : so how to make the data readable ? thanks

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  • Ruby Large HTML getting error, limit to header size

    - by Joe Stein
    def mailTo(subject,msg,folks) begin Net::SMTP.start('localhost', 25) do |smtp| smtp.send_message "MIME-Version: 1.0\nContent-type: text/html\nSubject: #{subject}\n#{msg}\n#{DateTime.now}\n", '[email protected]', folks end rescue => e puts "Emailing Sending Error - #{e}" end end when the HTML is VERY large I get this exception Emailing Sending Error - 552 5.6.0 Headers too large (32768 max) how can i get a larger html above max to work with Net::SMTP in Ruby

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  • Ruby Large HTML emails getting error, limit to header size

    - by Joe Stein
    def mailTo(subject,msg,folks) begin Net::SMTP.start('localhost', 25) do |smtp| smtp.send_message "MIME-Version: 1.0\nContent-type: text/html\nSubject: #{subject}\n#{msg}\n#{DateTime.now}\n", '[email protected]', folks end rescue => e puts "Emailing Sending Error - #{e}" end end when the HTML is VERY large I get this exception Emailing Sending Error - 552 5.6.0 Headers too large (32768 max) how can i get a larger html above max to work with Net::SMTP in Ruby

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  • Specifying column names from a list in the data.frame command.

    - by MW Frost
    I have a list called cols with column names in it: cols <- c('Column1','Column2','Column3') I'd like to reproduce this command, but with a call to the list: data.frame(Column1=rnorm(10)) Here's what happens when I try it: > data.frame(cols[1]=rnorm(10)) Error: unexpected '=' in "data.frame(I(cols[1])=" The same thing happens if I wrap cols[1] in I() or eval(). How can I feed that item from the vector into the data.frame() command?

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  • writing large excel spreadsheets

    - by pstanton
    has anybody found a library that works well with large spreadsheets? I've tried apache's POI but it fails miserably working with large files - both reading and writing. It uses massive amounts of memory leaving you needing a supercomputer to parse or create a 20+mb spreadsheet. Surely there is a more memory efficient way and someone has written it?!

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  • C++ program to calculate large factorials

    - by xbonez
    How can I write a c++ program to calculate large factorials. Example, if I want to calculate (100!) / (99!), we know the answer is 100, but if i calculate the factorials of the numerator and denominator individually, both the numbers are gigantically large.

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  • How do i make form data not disappear after hitting refresh?

    - by acidzombie24
    I went to test my page on another browser. On google chrome i can fill out a form, hit back and forward and still have the data there. Now i need to refresh the page so certain data is correct (such as session id if the cookie expires or user logs out before submitting). I refresh and lose all data. Is there some option i can set so all data is kept?

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  • Using IF LARGE when there is text in column

    - by Ray
    I have an excel column of numbers and texts. I tried to use "IF LARGE" to find top 3 numbers of the column (A1 to A7), and return "Yes" to the cells right next to the top 3 (in column B). But unfortunately, the cells next to the texts also returned "Yes". This is the data: 0.2 0.3 Yes 0.5 Yes 0.1 0.8 Yes asdf Yes jklm Yes This is the code for cell B7: =IF(A7>=LARGE($A$1:$A$7,3),"Yes","") Any suggestions to fix this? thanks in advance

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  • FairWarning Privacy Monitoring Solutions Rely on MySQL to Secure Patient Data

    - by Rebecca Hansen
    FairWarning® solutions have audited well over 120 billion events, each of which was processed and stored in a MySQL database. FairWarning is the world's leading supplier of privacy monitoring solutions for electronic health records, relied on by over 1,200 Hospitals and 5,000 Clinics to keep their patients' data safe. In January 2014, FairWarning was awarded the highest commendation in healthcare IT as the first ever Category Leader for Patient Privacy Monitoring in the "2013 Best in KLAS: Software & Services" report[1]. FairWarning has used MySQL as their solutions’ database from their start in 2005 to worldwide expansion and market leadership. FairWarning recently migrated their solutions from MyISAM to InnoDB and updated from MySQL 5.5 to 5.6. Following are some of benefits they’ve had as a result of those changes and reasons for their continued reliance on MySQL (from FairWarning MySQL Case Study). Scalability to Handle Terabytes of Data FairWarning's customers have a lot of data: On average, FairWarning customers receive over 700,000 events to be processed daily. Over 25% of their customers receive over 30 million events per day, which equates to over 1 billion events and nearly one terabyte (TB) of new data each month. Databases range in size from a few hundred GBs to 10+ TBs for enterprise deployments (data are rolled off after 13 months). Low or Zero Admin = Few DBAs "MySQL has not required a lot of administration. After it's been tuned, configured, and optimized for size on initial setup, we have very low administrative costs. I can scale and add more customers without adding DBAs. This has had a big, positive impact on our business.” - Chris Arnold, FairWarning Vice President of Product Management and Engineering. Performance Schema  As the size of FairWarning's customers has increased, so have their tables and data volumes. MySQL 5.6’ new maintenance and management features have helped FairWarning keep up. In particular, MySQL 5.6 performance schema’s low-level metrics have provided critical insight into how the system is performing and why. Support for Mutli-CPU Threads MySQL 5.6' support for multiple concurrent CPU threads, and FairWarning's custom data loader allow multiple files to load into a single table simultaneously vs. one at a time. As a result, their data load time has been reduced by 500%. MySQL Enterprise Hot Backup Because hospitals and clinics never stop, FairWarning solutions can’t either. FairWarning changed from using mysqldump to MySQL Enterprise Hot Backup, which has reduced downtime, restore time, and storage requirements. For many of their larger customers, restore time has decreased by 80%. MySQL Enterprise Edition and Product Roadmap Provide Complete Solution "MySQL's product roadmap fully addresses our needs. We like the fact that MySQL Enterprise Edition has everything included; there's no need to purchase separate modules."  - Chris Arnold Learn More>> FairWarning MySQL Case Study Why MySQL 5.6 is an Even Better Embedded Database for Your Products presentation Updating Your Products to MySQL 5.6, Best Practices for OEMs on-demand webinar (audio and / or slides + Q&A transcript) MyISAM to InnoDB – Why and How on-demand webinar (same stuff) Top 10 Reasons to Use MySQL as an Embedded Database white paper [1] 2013 Best in KLAS: Software & Services report, January, 2014. © 2014 KLAS Enterprises, LLC. All rights reserved.

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  • Oracle MDM Maturity Model

    - by David Butler
    A few weeks ago, I discussed the results of a survey conducted by Oracle’s Insight team. The survey was based on the data management maturity model that the Oracle Insight team has developed over the years as they analyzed customer IT organizations to help them get more out of everything they already have. I thought you might like to learn more about the maturity model itself. It can help you figure out where you stand when it comes to getting your organizations data management act together. The model covers maturity levels around five key areas: Profiling data sources; Defining a data strategy; Defining a data consolidation plan; Data maintenance; and Data utilization. Profile data sources: Profiling data sources involves taking an inventory of all data sources from across your IT landscape. Then evaluate the quality of the data in each source system. This enables the scoping of what data to collect into an MDM hub and what rules are needed to insure data harmonization across systems. Define data strategy: A data strategy requires an understanding of the data usage. Given data usage, various data governance requirements need to be developed. This includes data controls and security rules as well as data structure and usage policies. Define data consolidation strategy: Consolidation requires defining your operational data model. How integration is to be accomplished. Cross referencing common data attributes from multiple systems is needed. Synchronization policies also need to be developed. Data maintenance: The desired standardization needs to be defined, including what constitutes a ‘match’ once the data has been standardized. Cleansing rules are a part of this methodology. Data quality monitoring requirements also need to be defined. Utilize the data: What data gets published, and who consumes the data must be determined. How to get the right data to the right place in the right format given its intended use must be understood. Validating the data and insuring security rules are in place and enforced are crucial aspects for full no-risk data utilization. For each of the above data management areas, a maturity level needs to be assessed. Where your organization wants to be should also be identified using the same maturity levels. This results in a sound gap analysis your organization can use to create action plans to achieve the ultimate goals. Marginal is the lowest level. It is characterized by manually maintaining trusted sources; lacking or inconsistent, silo’d structures with limited integration, and gaps in automation. Stable is the next leg up the MDM maturity staircase. It is characterized by tactical MDM implementations that are limited in scope and target a specific division.  It includes limited data stewardship capabilities as well. Best Practice is a serious MDM maturity level characterized by process automation improvements. The scope is enterprise wide. It is a business solution that provides a single version of the truth, with closed-loop data quality capabilities. It is typically driven by an enterprise architecture group with both business and IT representation.   Transformational is the highest MDM maturity level. At this level, MDM is quantitatively managed. It is integrated with Business Intelligence, SOA, and BPM. MDM is leveraged in business process orchestration. Take an inventory using this MDM Maturity Model and see where you are in your journey to full MDM maturity with all the business benefits that accrue to organizations who have mastered their data for the benefit of all operational applications, business processes, and analytical systems. To learn more, Trevor Naidoo and I have written the Oracle MDM Maturity Model whitepaper. It’s free, so go ahead and download it and use it as you see fit.

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  • Indexing data from multiple tables with Oracle Text

    - by Roger Ford
    It's well known that Oracle Text indexes perform best when all the data to be indexed is combined into a single index. The query select * from mytable where contains (title, 'dog') 0 or contains (body, 'cat') 0 will tend to perform much worse than select * from mytable where contains (text, 'dog WITHIN title OR cat WITHIN body') 0 For this reason, Oracle Text provides the MULTI_COLUMN_DATASTORE which will combine data from multiple columns into a single index. Effectively, it constructs a "virtual document" at indexing time, which might look something like: <title>the big dog</title> <body>the ginger cat smiles</body> This virtual document can be indexed using either AUTO_SECTION_GROUP, or by explicitly defining sections for title and body, allowing the query as expressed above. Note that we've used a column called "text" - this might have been a dummy column added to the table simply to allow us to create an index on it - or we could created the index on either of the "real" columns - title or body. It should be noted that MULTI_COLUMN_DATASTORE doesn't automatically handle updates to columns used by it - if you create the index on the column text, but specify that columns title and body are to be indexed, you will need to arrange triggers such that the text column is updated whenever title or body are altered. That works fine for single tables. But what if we actually want to combine data from multiple tables? In that case there are two approaches which work well: Create a real table which contains a summary of the information, and create the index on that using the MULTI_COLUMN_DATASTORE. This is simple, and effective, but it does use a lot of disk space as the information to be indexed has to be duplicated. Create our own "virtual" documents using the USER_DATASTORE. The user datastore allows us to specify a PL/SQL procedure which will be used to fetch the data to be indexed, returned in a CLOB, or occasionally in a BLOB or VARCHAR2. This PL/SQL procedure is called once for each row in the table to be indexed, and is passed the ROWID value of the current row being indexed. The actual contents of the procedure is entirely up to the owner, but it is normal to fetch data from one or more columns from database tables. In both cases, we still need to take care of updates - making sure that we have all the triggers necessary to update the indexed column (and, in case 1, the summary table) whenever any of the data to be indexed gets changed. I've written full examples of both these techniques, as SQL scripts to be run in the SQL*Plus tool. You will need to run them as a user who has CTXAPP role and CREATE DIRECTORY privilege. Part of the data to be indexed is a Microsoft Word file called "1.doc". You should create this file in Word, preferably containing the single line of text: "test document". This file can be saved anywhere, but the SQL scripts need to be changed so that the "create or replace directory" command refers to the right location. In the example, I've used C:\doc. multi_table_indexing_1.sql : creates a summary table containing all the data, and uses multi_column_datastore Download link / View in browser multi_table_indexing_2.sql : creates "virtual" documents using a procedure as a user_datastore Download link / View in browser

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  • Second Day of Data Integration Track at OpenWorld 2012

    - by Doug Reid
    0 false 18 pt 18 pt 0 0 false false false /* 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Our second day at OpenWorld and the Data Integration Team was very active with customer meetings, product updates, product demonstrations, sessions, plus much more.  If the volume of traffic by our demo pods is any indicator, this is a record year for attendance at OpenWorld.  The DIS team have had tremendous number of people stop by our demo pods to learn about the latest product releases or to speak to one of our product managers.    For Oracle GoldenGate, there has been a great deal of interest in Integrated Capture and the  Oracle GoldenGate Monitor plug-in for Enterprise Manager.  Our customer panels this year have been very well attended and on Tuesday we held the “Real World Operational Reporting with Oracle GoldenGate Customer Panel”. On this panel this year we had Michael Wells from Raymond James, Joy Mathew and Venki Govindarajan from Comcast, and Serkan Karatas from Turk Telekom. Our panelists have a great mix of experiences and all are passionate about using Oracle Data Integration products to solve very complex use cases. Each panelist was given a ten minute to overview their use of our product, followed by a barrage of questions from the audience. Michael Wells spoke about using Oracle GoldenGate for heterogeneous real time replication from HP (Tandem) NonStop to SQL Server and emphasized the need for using standard naming conventions for when customers configure GoldenGate, as the practices is immensely helpful when debugging a problem. Joy Mathew and Venkat Govindarajan from Comcast described how they have used GoldenGate for over a decade and their experiences of using the product for replicating data from HP nonstop to Terdata. Serkan Karatas from Turk Telekom dove into using Oracle GoldenGate and the value of archiving data in extremely large databases, which in Turk Telekoms case resulted in a 1 month ROI for the entire project. Thanks again to our panelist and audience participants for making the session interactive and informative.  For Wednesday we have a number of sessions available to attendees plus two hands-on labs, which I have listed below.   If you are unable to attend our hands-on lab for Oracle GoldenGate Veridata, it is available online at youtube.com. Sessions  11:45 AM - 12:45 PM Best Practices for High Availability with Oracle GoldenGate on Oracle Exadata -Moscone South - 102 1:15 PM - 2:15 PM Customer Perspectives: Oracle Data Integrator -Marriott Marquis - Golden Gate C3 Oracle GoldenGate Case Study: Real-Time Operational Reporting Deployment at Oracle -Moscone West - 2003 Data Preparation and Ongoing Governance with the Oracle Enterprise Data Quality Platform -Moscone West - 3000 3:30 PM - 4:30 PM Best Practices for Conflict Detection and Resolution in Oracle GoldenGate for Active/Active -Moscone West - 3000 5:00 PM - 6:00 PM Tuning and Troubleshooting Oracle GoldenGate on Oracle Database -Moscone South - 102 0 false 18 pt 18 pt 0 0 false false false /* 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Hands-on Labs 10:15 AM - 11:15 AM Introduction to Oracle GoldenGate Veridata Marriott Marquis - Salon 1/2 11:45 AM - 12:45 PM Oracle Data Integrator and Oracle SOA Suite: Hands-on Lab -Marriott Marquis - Salon 1/2 If you are at OpenWorld please join us in these sessions. For a full review of data integration track at OpenWorld please see our Focus-On Document.

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