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  • Text Trimming in Silverlight 4

    - by dwahlin
    Silverlight 4 has a lot of great features that can be used to build consumer and Line of Business (LOB) applications. Although Webcam support, RichTextBox, MEF, WebBrowser and other new features are pretty exciting, I’m actually enjoying some of the more simple features that have been added such as text trimming, built-in wheel scrolling with ScrollViewer and data binding enhancements such as StringFormat. In this post I’ll give a quick introduction to a simple yet productive feature called text trimming and show how it eliminates a lot of code compared to Silverlight 3. The TextBlock control contains a new property in Silverlight 4 called TextTrimming that can be used to add an ellipsis (…) to text that doesn’t fit into a specific area on the user interface. Before the TextTrimming property was available I used a value converter to trim text which meant passing in a specific number of characters that I wanted to show by using a parameter: public class StringTruncateConverter : IValueConverter { #region IValueConverter Members public object Convert(object value, Type targetType, object parameter, System.Globalization.CultureInfo culture) { int maxLength; if (int.TryParse(parameter.ToString(), out maxLength)) { string val = (value == null) ? null : value.ToString(); if (val != null && val.Length > maxLength) { return val.Substring(0, maxLength) + ".."; } } return value; } public object ConvertBack(object value, Type targetType, object parameter, System.Globalization.CultureInfo culture) { throw new NotImplementedException(); } #endregion } To use the StringTruncateConverter I'd define the standard xmlns prefix that referenced the namespace and assembly, add the class into the application’s Resources section and then use the class while data binding as shown next: <TextBlock Grid.Column="1" Grid.Row="3" ToolTipService.ToolTip="{Binding ReportSummary.ProjectManagers}" Text="{Binding ReportSummary.ProjectManagers, Converter={StaticResource StringTruncateConverter},ConverterParameter=16}" Style="{StaticResource SummaryValueStyle}" /> With Silverlight 4 I can define the TextTrimming property directly in XAML or use the new Property window in Visual Studio 2010 to set it to a value of WordEllipsis (the default value is None): <TextBlock Grid.Column="1" Grid.Row="4" ToolTipService.ToolTip="{Binding ReportSummary.ProjectCoordinators}" Text="{Binding ReportSummary.ProjectCoordinators}" TextTrimming="WordEllipsis" Style="{StaticResource SummaryValueStyle}"/> The end result is a nice trimming of the text that doesn’t fit into the target area as shown with the Coordinator and Foremen sections below. My data binding statements are now much smaller and I can eliminate the StringTruncateConverter class completely.   For more information about onsite, online and video training, mentoring and consulting solutions for .NET, SharePoint or Silverlight please visit http://www.thewahlingroup.com.

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  • GoldenGate 12c Trail Encryption and Credentials with Oracle Wallet

    - by hamsun
    I have been asked more than once whether the Oracle Wallet supports GoldenGate trail encryption. Although GoldenGate has supported encryption with the ENCKEYS file for years, Oracle GoldenGate 12c now also supports encryption using the Oracle Wallet. This helps improve security and makes it easier to administer. Two types of wallets can be configured in Oracle GoldenGate 12c: The wallet that holds the master keys, used with trail or TCP/IP encryption and decryption, stored in the new 12c dirwlt/cwallet.sso file.   The wallet that holds the Oracle Database user IDs and passwords stored in the ‘credential store’ stored in the new 12c dircrd/cwallet.sso file.   A wallet can be created using a ‘create wallet’  command.  Adding a master key to an existing wallet is easy using ‘open wallet’ and ‘add masterkey’ commands.   GGSCI (EDLVC3R27P0) 42> open wallet Opened wallet at location 'dirwlt'. GGSCI (EDLVC3R27P0) 43> add masterkey Master key 'OGG_DEFAULT_MASTERKEY' added to wallet at location 'dirwlt'.   Existing GUI Wallet utilities that come with other products such as the Oracle Database “Oracle Wallet Manager” do not work on this version of the wallet. The default Oracle Wallet can be changed.   GGSCI (EDLVC3R27P0) 44> sh ls -ltr ./dirwlt/* -rw-r----- 1 oracle oinstall 685 May 30 05:24 ./dirwlt/cwallet.sso GGSCI (EDLVC3R27P0) 45> info masterkey Masterkey Name:                 OGG_DEFAULT_MASTERKEY Creation Date:                  Fri May 30 05:24:04 2014 Version:        Creation Date:                  Status: 1               Fri May 30 05:24:04 2014        Current   The second wallet file is used for the credential used to connect to a database, without exposing the user id or password. Once it is configured, this file can be copied so that credentials are available to connect to the source or target database.   GGSCI (EDLVC3R27P0) 48> sh cp ./dircrd/cwallet.sso $GG_EURO_HOME/dircrd GGSCI (EDLVC3R27P0) 49> sh ls -ltr ./dircrd/* -rw-r----- 1 oracle oinstall 709 May 28 05:39 ./dircrd/cwallet.sso   The encryption wallet file can also be copied to the target machine so the replicat has access to the master key to decrypt records that are encrypted in the trail. Similar to the old ENCKEYS file, the master keys wallet created on the source host must either be stored in a centrally available disk or copied to all GoldenGate target hosts. The wallet is in a platform-independent format, although it is not certified for the iSeries, z/OS, and NonStop platforms.   GGSCI (EDLVC3R27P0) 50> sh cp ./dirwlt/cwallet.sso $GG_EURO_HOME/dirwlt   The new 12c UserIdAlias parameter is used to locate the credential in the wallet so the source user id and password does not need to be stored as a parameter as long as it is in the wallet.   GGSCI (EDLVC3R27P0) 52> view param extwest extract extwest exttrail ./dirdat/ew useridalias gguamer table west.*; The EncryptTrail parameter is used to encrypt the trail using the Advanced Encryption Standard and can be used with a primary extract or pump extract. GGSCI (EDLVC3R27P0) 54> view param pwest extract pwest encrypttrail AES256 rmthost easthost, mgrport 15001 rmttrail ./dirdat/pe passthru table west.*;   Once the extracts are running, records can be encrypted using the wallet.   GGSCI (EDLVC3R27P0) 60> info extract *west EXTRACT    EXTWEST   Last Started 2014-05-30 05:26   Status RUNNING Checkpoint Lag       00:00:17 (updated 00:00:01 ago) Process ID           24982 Log Read Checkpoint  Oracle Integrated Redo Logs                      2014-05-30 05:25:53                      SCN 0.0 (0) EXTRACT    PWEST     Last Started 2014-05-30 05:26   Status RUNNING Checkpoint Lag       24:02:32 (updated 00:00:05 ago) Process ID           24983 Log Read Checkpoint  File ./dirdat/ew000004                      2014-05-29 05:23:34.748949  RBA 1483   The ‘info masterkey’ command is used to confirm the wallet contains the key after copying it to the target machine. The key is needed to decrypt the data in the trail before the replicat applies the changes to the target database.   GGSCI (EDLVC3R27P0) 41> open wallet Opened wallet at location 'dirwlt'. GGSCI (EDLVC3R27P0) 42> info masterkey Masterkey Name:                 OGG_DEFAULT_MASTERKEY Creation Date:                  Fri May 30 05:24:04 2014 Version:        Creation Date:                  Status: 1               Fri May 30 05:24:04 2014        Current   Once the replicat is running, records can be decrypted using the wallet.   GGSCI (EDLVC3R27P0) 44> info reast REPLICAT   REAST     Last Started 2014-05-30 05:28   Status RUNNING INTEGRATED Checkpoint Lag       00:00:00 (updated 00:00:02 ago) Process ID           25057 Log Read Checkpoint  File ./dirdat/pe000004                      2014-05-30 05:28:16.000000  RBA 1546   There is no need for the DecryptTrail parameter when using the Oracle Wallet, unlike when using the ENCKEYS file.   GGSCI (EDLVC3R27P0) 45> view params reast replicat reast assumetargetdefs discardfile ./dirrpt/reast.dsc, purge useridalias ggueuro map west.*, target east.*;   Once a record is inserted into the source table and committed, the encryption can be verified using logdump and then querying the target table.   AMER_SQL>insert into west.branch values (50, 80071); 1 row created.   AMER_SQL>commit; Commit complete.   The following encrypted record can be found using logdump. Logdump 40 >n 2014/05/30 05:28:30.001.154 Insert               Len    28 RBA 1546 Name: WEST.BRANCH After  Image:                                             Partition 4   G  s    0a3e 1ba3 d924 5c02 eade db3f 61a9 164d 8b53 4331 | .>...$\....?a..M.SC1   554f e65a 5185 0257                               | UO.ZQ..W  Bad compressed block, found length of  7075 (x1ba3), RBA 1546   GGS tokens: TokenID x52 'R' ORAROWID         Info x00  Length   20  4141 4157 7649 4141 4741 4141 4144 7541 4170 0001 | AAAWvIAAGAAAADuAAp..  TokenID x4c 'L' LOGCSN           Info x00  Length    7  3231 3632 3934 33                                 | 2162943  TokenID x36 '6' TRANID           Info x00  Length   10  3130 2e31 372e 3135 3031                          | 10.17.1501  The replicat automatically decrypted this record from the trail and then inserted the row to the target table using the wallet. This select verifies the row was inserted into the target database and the data is not encrypted. EURO_SQL>select * from branch where branch_number=50; BRANCH_NUMBER                  BRANCH_ZIP -------------                                   ----------    50                                              80071   Book a seat in an upcoming Oracle GoldenGate 12c: Fundamentals for Oracle course now to learn more about GoldenGate 12c new features including how to use GoldenGate with the Oracle wallet, credentials, integrated extracts, integrated replicats, the Oracle Universal Installer, and other new features. Looking for another course? View all Oracle GoldenGate training.   Randy Richeson joined Oracle University as a Senior Principal Instructor in March 2005. He is an Oracle Certified Professional (10g-12c) and a GoldenGate Certified Implementation Specialist (10-11g). He has taught GoldenGate since 2010 and also has experience teaching other technical curriculums including GoldenGate Monitor, Veridata, JD Edwards, PeopleSoft, and the Oracle Application Server.

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  • MVP in 2010

    Microsoft has just named me an MVP for the seventh time in a row!More .NET adventures with me expected in 2010......Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • The blocking nature of aggregates

    - by Rob Farley
    I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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  • The blocking nature of aggregates

    - by Rob Farley
    I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

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  • COLUMNS_UPDATED() for audit triggers

    - by Piotr Rodak
    In SQL Server 2005, triggers are pretty much the only option if you want to audit changes to a table. There are many ways you can decide to store the change information. You may decide to store every changed row as a whole, either in a history table or as xml in audit table. The former case requires having a history table with exactly same schema as the audited table, the latter makes data retrieval and management of the table a bit tricky. Both approaches also suffer from the tendency to consume...(read more)

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  • Oracle Tutor: Create Accessible Content for the Disabled Community

    - by emily.chorba(at)oracle.com
    For many reasons--legal, business, and ethical--Oracle recognizes the need for its applications, and our customers' and partners' products built with our tools, to be usable by the disabled community. The following features of Tutor Author and Publisher software facilitate the creation of accessible HTML content for the disabled community.TablesThe following formatting guidelines will ensure that Tutor documents containing tables will be accessible once they are converted to HTML.• Determine whether a table is a "data table" or whether you are using a table simply for formatting. If it's a data table, you must use a heading for each column, and you should format this heading row as "table heading" style and select Table > Heading Rows Repeat.• For non data tables, it is not necessary to include a heading row.GraphicsTo create accessible graphics, add a caption to the graphic. In Microsoft Office 2000 and greater, right-click on the graphic and select Format Picture > Web (tab) > Alternative Text or select the graphic then Format > Picture > Web (tab) Alternative Text. Enter the appropriate information in the dialog box.When a document containing a graphic with alternative text is converted to HTML by Tutor, the HTML document will contain the appropriate accessibility information.Javascript elementsThe tabbed format and other javascript elements in the HTML version of the Tutor documents may not be accessible to all users. A link to an accessible/printable version of the document is available in the upper right corner of all Tutor documents.Repetitive dataIf repetitive data such as the distribution section and the ownership section are causing accessibility issues with your Tutor documents, you can insert a bookmark in the appropriate location of the document, and, when the document is converted to HTML, the bookmark will be converted to an A NAME reference (also known as an internal link). With this reference, you can create a link in Header.txt that can be prepended to each Tutor document that allows the user to bypass repetitive sections. Tutor and Oracle ApplicationsRegarding accessibility, please check Oracle's website on accessibility http://www.oracle.com/accessibility/ to find out what version of E-Business Suite is certified to work with screen readers. Oracle Tutor 11.5.6A and greater works with screen readers such as JAWS.There is no certification between Oracle Tutor and Oracle Applications because there are no related dependencies. It doesn't matter which version of the Oracle Applications you are running. Therefore, it is possible to use Oracle Tutor with earlier versions of Oracle Applications.Oracle Business Process Converter and Oracle ApplicationsOracle Business Process Converter (OBPC) converts Visio, XPDL, and Tutor models to Oracle Business Process Architect and Oracle Business Process Management. The OBPC is one of a collection of plugins to Oracle JDeveloper. Please see the VPAT as the same considerations apply.Learn MoreFor more information about Tutor, visit Oracle.Com or the Tutor Blog. Post your questions at the Tutor Forum. Emily ChorbaPrinciple Product Manager Oracle Tutor & BPM

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  • Common header file for C++ and JavaScipt

    - by paperjam
    I have an app that runs a C++ server backend and Javascript on the client. I would like to define certain strings once only, for both pieces of code. For example, I might have a CSS class "row-hover" - I want to define this class name in one place only in case I change it later. Is there an easy way to include, or read, some sort of common definitions file into both C++ and JavaScript? Ideally as a compile / preprocessing step but any neat approach good.

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  • Integrating Oracle Hyperion Smart View Data Queries with MS Word and Power Point

    - by Andreea Vaduva
    Untitled Document table { border: thin solid; } Most Smart View users probably appreciate that they can use just one add-in to access data from the different sources they might work with, like Oracle Essbase, Oracle Hyperion Planning, Oracle Hyperion Financial Management and others. But not all of them are aware of the options to integrate data analyses not only in Excel, but also in MS Word or Power Point. While in the past, copying and pasting single numbers or tables from a recent analysis in Excel made the pasted content a static snapshot, copying so called Data Points now creates dynamic, updateable references to the data source. It also provides additional nice features, which can make life easier and less stressful for Smart View users. So, how does this option work: after building an ad-hoc analysis with Smart View as usual in an Excel worksheet, any area including data cells/numbers from the database can be highlighted in order to copy data points - even single data cells only.   TIP It is not necessary to highlight and copy the row or column descriptions   Next from the Smart View ribbon select Copy Data Point. Then transfer to the Word or Power Point document into which the selected content should be copied. Note that in these Office programs you will find a menu item Smart View;from it select the Paste Data Point icon. The copied details from the Excel report will be pasted, but showing #NEED_REFRESH in the data cells instead of the original numbers. =After clicking the Refresh icon on the Smart View menu the data will be retrieved and displayed. (Maybe at that moment a login window pops up and you need to provide your credentials.) It works in the same way if you just copy one single number without any row or column descriptions, for example in order to incorporate it into a continuous text: Before refresh: After refresh: From now on for any subsequent updates of the data shown in your documents you only need to refresh data by clicking the Refresh button on the Smart View menu, without copying and pasting the context or content again. As you might realize, trying out this feature on your own, there won’t be any Point of View shown in the Office document. Also you have seen in the example, where only a single data cell was copied, that there aren’t any member names or row/column descriptions copied, which are usually required in an ad-hoc report in order to exactly define where data comes from or how data is queried from the source. Well, these definitions are not visible, but they are transferred to the Word or Power Point document as well. They are stored in the background for each individual data cell copied and can be made visible by double-clicking the data cell as shown in the following screen shot (but which is taken from another context).   So for each cell/number the complete connection information is stored along with the exact member/cell intersection from the database. And that’s not all: you have the chance now to exchange the members originally selected in the Point of View (POV) in the Excel report. Remember, at that time we had the following selection:   By selecting the Manage POV option from the Smart View meny in Word or Power Point…   … the following POV Manager – Queries window opens:   You can now change your selection for each dimension from the original POV by either double-clicking the dimension member in the lower right box under POV: or by selecting the Member Selector icon on the top right hand side of the window. After confirming your changes you need to refresh your document again. Be aware, that this will update all (!) numbers taken from one and the same original Excel sheet, even if they appear in different locations in your Office document, reflecting your recent changes in the POV. TIP Build your original report already in a way that dimensions you might want to change from within Word or Power Point are placed in the POV. And there is another really nice feature I wouldn’t like to miss mentioning: Using Dynamic Data Points in the way described above, you will never miss or need to search again for your original Excel sheet from which values were taken and copied as data points into an Office document. Because from even only one single data cell Smart View is able to recreate the entire original report content with just a few clicks: Select one of the numbers from within your Word or Power Point document by double-clicking.   Then select the Visualize in Excel option from the Smart View menu. Excel will open and Smart View will rebuild the entire original report, including POV settings, and retrieve all data from the most recent actual state of the database. (It might be necessary to provide your credentials before data is displayed.) However, in order to make this work, an active online connection to your databases on the server is necessary and at least read access to the retrieved data. But apart from this, your newly built Excel report is fully functional for ad-hoc analysis and can be used in the common way for drilling, pivoting and all the other known functions and features. So far about embedding Dynamic Data Points into Office documents and linking them back into Excel worksheets. You can apply this in the described way with ad-hoc analyses directly on Essbase databases or using Hyperion Planning and Hyperion Financial Management ad-hoc web forms. If you are also interested in other new features and smart enhancements in Essbase or Hyperion Planning stay tuned for coming articles or check our training courses and web presentations. You can find general information about offerings for the Essbase and Planning curriculum or other Oracle-Hyperion products here (please make sure to select your country/region at the top of this page) or in the OU Learning paths section , where Planning, Essbase and other Hyperion products can be found under the Fusion Middleware heading (again, please select the right country/region). Or drop me a note directly: [email protected] . About the Author: Bernhard Kinkel started working for Hyperion Solutions as a Presales Consultant and Consultant in 1998 and moved to Hyperion Education Services in 1999. He joined Oracle University in 2007 where he is a Principal Education Consultant. Based on these many years of working with Hyperion products he has detailed product knowledge across several versions. He delivers both classroom and live virtual courses. His areas of expertise are Oracle/Hyperion Essbase, Oracle Hyperion Planning and Hyperion Web Analysis.  

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  • Oracle Flashback Technologies - Overview

    - by Sridhar_R-Oracle
    Oracle Flashback Technologies - IntroductionIn his May 29th 2014 blog, my colleague Joe Meeks introduced Oracle Maximum Availability Architecture (MAA) and discussed both planned and unplanned outages. Let’s take a closer look at unplanned outages. These can be caused by physical failures (e.g., server, storage, network, file deletion, physical corruption, site failures) or by logical failures – cases where all components and files are physically available, but data is incorrect or corrupt. These logical failures are usually caused by human errors or application logic errors. This blog series focuses on these logical errors – what causes them and how to address and recover from them using Oracle Database Flashback. In this introductory blog post, I’ll provide an overview of the Oracle Database Flashback technologies and will discuss the features in detail in future blog posts. Let’s get started. We are all human beings (unless a machine is reading this), and making mistakes is a part of what we do…often what we do best!  We “fat finger”, we spill drinks on keyboards, unplug the wrong cables, etc.  In addition, many of us, in our lives as DBAs or developers, must have observed, caused, or corrected one or more of the following unpleasant events: Accidentally updated a table with wrong values !! Performed a batch update that went wrong - due to logical errors in the code !! Dropped a table !! How do DBAs typically recover from these types of errors? First, data needs to be restored and recovered to the point-in-time when the error occurred (incomplete or point-in-time recovery).  Moreover, depending on the type of fault, it’s possible that some services – or even the entire database – would have to be taken down during the recovery process.Apart from error conditions, there are other questions that need to be addressed as part of the investigation. For example, what did the data look like in the morning, prior to the error? What were the various changes to the row(s) between two timestamps? Who performed the transaction and how can it be reversed?  Oracle Database includes built-in Flashback technologies, with features that address these challenges and questions, and enable you to perform faster, easier, and convenient recovery from logical corruptions. HistoryFlashback Query, the first Flashback Technology, was introduced in Oracle 9i. It provides a simple, powerful and completely non-disruptive mechanism for data verification and recovery from logical errors, and enables users to view the state of data at a previous point in time.Flashback Technologies were further enhanced in Oracle 10g, to provide fast, easy recovery at the database, table, row, and even at a transaction level.Oracle Database 11g introduced an innovative method to manage and query long-term historical data with Flashback Data Archive. The 11g release also introduced Flashback Transaction, which provides an easy, one-step operation to back out a transaction. Oracle Database versions 11.2.0.2 and beyond further enhanced the performance of these features. Note that all the features listed here work without requiring any kind of restore operation.In addition, Flashback features are fully supported with the new multi-tenant capabilities introduced with Oracle Database 12c, Flashback Features Oracle Flashback Database enables point-in-time-recovery of the entire database without requiring a traditional restore and recovery operation. It rewinds the entire database to a specified point in time in the past by undoing all the changes that were made since that time.Oracle Flashback Table enables an entire table or a set of tables to be recovered to a point in time in the past.Oracle Flashback Drop enables accidentally dropped tables and all dependent objects to be restored.Oracle Flashback Query enables data to be viewed at a point-in-time in the past. This feature can be used to view and reconstruct data that was lost due to unintentional change(s) or deletion(s). This feature can also be used to build self-service error correction into applications, empowering end-users to undo and correct their errors.Oracle Flashback Version Query offers the ability to query the historical changes to data between two points in time or system change numbers (SCN) Oracle Flashback Transaction Query enables changes to be examined at the transaction level. This capability can be used to diagnose problems, perform analysis, audit transactions, and even revert the transaction by undoing SQLOracle Flashback Transaction is a procedure used to back-out a transaction and its dependent transactions.Flashback technologies eliminate the need for a traditional restore and recovery process to fix logical corruptions or make enquiries. Using these technologies, you can recover from the error in the same amount of time it took to generate the error. All the Flashback features can be accessed either via SQL command line (or) via Enterprise Manager.  Most of the Flashback technologies depend on the available UNDO to retrieve older data. The following table describes the various Flashback technologies: their purpose, dependencies and situations where each individual technology can be used.   Example Syntax Error investigation related:The purpose is to investigate what went wrong and what the values were at certain points in timeFlashback Queries  ( select .. as of SCN | Timestamp )   - Helps to see the value of a row/set of rows at a point in timeFlashback Version Queries  ( select .. versions between SCN | Timestamp and SCN | Timestamp)  - Helps determine how the value evolved between certain SCNs or between timestamps Flashback Transaction Queries (select .. XID=)   - Helps to understand how the transaction caused the changes.Error correction related:The purpose is to fix the error and correct the problems,Flashback Table  (flashback table .. to SCN | Timestamp)  - To rewind the table to a particular timestamp or SCN to reverse unwanted updates Flashback Drop (flashback table ..  to before drop )  - To undrop or undelete a table Flashback Database (flashback database to SCN  | Restore Point )  - This is the rewind button for Oracle databases. You can revert the entire database to a particular point in time. It is a fast way to perform a PITR (point-in-time recovery). Flashback Transaction (DBMS_FLASHBACK.TRANSACTION_BACKOUT(XID..))  - To reverse a transaction and its related transactions Advanced use cases Flashback technology is integrated into Oracle Recovery Manager (RMAN) and Oracle Data Guard. So, apart from the basic use cases mentioned above, the following use cases are addressed using Oracle Flashback. Block Media recovery by RMAN - to perform block level recovery Snapshot Standby - where the standby is temporarily converted to a read/write environment for testing, backup, or migration purposes Re-instate old primary in a Data Guard environment – this avoids the need to restore an old backup and perform a recovery to make it a new standby. Guaranteed Restore Points - to bring back the entire database to an older point-in-time in a guaranteed way. and so on..I hope this introductory overview helps you understand how Flashback features can be used to investigate and recover from logical errors.  As mentioned earlier, I will take a deeper-dive into to some of the critical Flashback features in my upcoming blogs and address common use cases.

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  • Agile PLM 9.3 Service Pack 2 (SP2 or 9.3.0.2) is released along with AUT 1.6.2.0 and AutoVue 20 for

    - by Shane Goodwin
    Oracle released Agile PLM 9.3 SP2 on June 14 and the Agile installer for AutoVue 20 for Agile PLM on April 30. Also available are the new versions of AUT and Averify - 1.6.3 for both tools. 9.3 SP2 is a combined English and NLS release for use on any version of 9.3.0. SP2 contains many bug fixes and rolls up several Hot Fixes - please review the Readme for all the details. In addition, this release also addresses some scalability issues when working with very large Exports and Reports. When exporting very large BOMs, the export module will now release objects more efficiently to reduce the amount of memory consumed on the Application Server. Adminstrators can also control the maximum row limits for Users verses system processes, like ACS. Several out of the box BOM reports have also been changed to use a new row limit option. The combination of all these changes will provide more stability on the application server for customers managing very large datasets. 9.3 SP2 also adds support for Oracle Database 11gR2 for Windows, Oracle Internet Directory (OID) and Oracle Access Manager (OAM). Please note that currently the Variant Patch is not intended to be released for SP2. Customers running the Variant Patch should remain on 9.3.0.0 or 9.3.0.1. Back in April, we also released the AutoVue 20 for Agile PLM installer. AutoVue 20 has many new features which will help Agile PLM customers. Large multi-page Word documents and 2D CAD documents will open more quickly to the first page or first rendition. Memory usage is less when working with 3D Models. There are many new formats supported for MCAD, 2D Cad, and EDA. AutoVue 20 is immediately available for Windows and Linux platforms. The new software can be found in Edelivery or Metalink / Oracle Support: - AutoVue 20 for Agile PLM is on E-Delivery with part number B58963-01 - Oracle Agile PLM 9.3 Service Pack 2 (9.3.0.2) My Oracle Support Patch ID 9782736 - AVERIFY 1.6.3 My Oracle Support Patch ID 9791892 - AUT 1.6.3 My Oracle Support Patch ID 9791908 - Agile PLM 9.3 SP2 Documentation is available on the OTN Agile Documentation Page

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  • MySQL Input Parameters Add Flexibility to Crosstab Stored Procedures

    When generating a result set where the query contains an unknown number of column and/or row values we can use a combination of Prepared Statements, which allows us to tailor the output based on the number of data values. We can also add input parameters to a procedure to assign the field names, aliases, and even the aggregate function!

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  • MySQL Input Parameters Add Flexibility to Crosstab Stored Procedures

    When generating a result set where the query contains an unknown number of column and/or row values we can use a combination of Prepared Statements, which allows us to tailor the output based on the number of data values. We can also add input parameters to a procedure to assign the field names, aliases, and even the aggregate function!

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  • Geek City: Where are LOBs stored?

    - by Kalen Delaney
    When researching a question from one of the students in my class last week, I was reading the documentation for CREATE TABLE about storing LOB columns at http://msdn.microsoft.com/en-us/library/ms174979.aspx . For this discussion LOB columns includes text, image, ntext, xml and the MAX columns when they are over 8000 bytes and stored outside the regular data row. I knew that SQL Server gives us the capability of storing LOB columns in a separate filegroup with the TEXTIMAGE_ON clause, but I was surprised...(read more)

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  • WPF: Reloading app parts to handle persistence as well as memory management.

    - by Ingó Vals
    I created a app using Microsoft's WPF. It mostly handles data reading and input as well as associating relations between data within specific parameters. As a total beginner I made some bad design decision ( not so much decisions as using the first thing I got to work ) but now understanding WPF better I'm getting the urge to refactor my code with better design principles. I had several problems but I guess each deserves it's own question for clarity. Here I'm asking for proper ways to handle the data itself. In the original I wrapped each row in a object when fetched from database ( using LINQ to SQL ) somewhat like Active Record just not active or persistence (each app instance had it's own data handling part). The app has subunits handling different aspects. However as it was setup it loaded everything when started. This creates several problems, for example often it wouldn't be neccesary to load a part unless we were specifically going to work with that part so I wan't some form of lazy loading. Also there was problem with inner persistance because you might create a new object/row in one aspect and perhaps set relation between it and different object but the new object wouldn't appear until the program was restarted. Persistance between instances of the app won't be huge problem because of the small amount of people using the program. While I could solve this now using dirty tricks I would rather refactor the program and do it elegantly, Now the question is how. I know there are several ways and a few come to mind: 1) Each aspect of the program is it's own UserControl that get's reloaded/instanced everytime you navigate to it. This ensures you only load up the data you need and you get some persistancy. DB server located on same LAN and tables are small so that shouldn't be a big problem. Minor drawback is that you would have to remember the state of each aspect so you wouldn't always start at beginners square. 2) Having a ViewModel type object at the base level of the app with lazy loading and some kind of timeout. I would then propegate this object down the visual tree to ensure every aspect is getting it's data from the same instance 3) Semi active record data layer with static load methods. 4) Some other idea What in your opinion is the most practical way in WPF, what does MVVM assume?

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  • 'sudo su -' vs 'sudo -i' vs 'sudo /bin/bash' - when does it matter which is used, or does it matter at all?

    - by Paul
    When I'm doing something that requires root be typed in dozens of times in a row, I prefer to switch my session to a root session. In the various tutorials and instructions I have used on the Internet, I see sudo su, sudo su -, sudo -i and sudo /bin/bash being used to open a root session, but I'm not clear on the difference between these and when or if that difference matters. Can someone clear this up for me?

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  • MySQL CASE Statements in Multi-Aggregated Crosstab Columns

    Inserting additional columns to a crosstab query is less straightforward than adding row data, because SQL naturally groups data by rows. Moreover, the efficacy of the CASE statement within an aggregate function decreases in direct proportion to the complexity of the criteria. Read on to learn more...

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  • MySQL CASE Statements in Multi-Aggregated Crosstab Columns

    Inserting additional columns to a crosstab query is less straightforward than adding row data, because SQL naturally groups data by rows. Moreover, the efficacy of the CASE statement within an aggregate function decreases in direct proportion to the complexity of the criteria. Read on to learn more...

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  • Uploaded Four New ADF Examples

    - by Steve Muench
    I've uploaded four new examples for your learning pleasure:  162. Set Binding to Attr Value from Selected SelectBooleanRadio Button in Data-Driven Button Group 163. Binding SelectBooleanRadio to True/False Value in DB Row 164. Method Action Invoking Managed Bean Method Without Making Bean a DataControl 165. Using a Headless Taskflow to Perform Work in an Autononmous Transaction Enjoy.

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  • GNU/Linux interactive table content GUI editor?

    - by sdaau
    I often find myself in the need to gather data (say from the internet), into a table, for comparison reasons. I usually need the final table output in HTML or MediaWiki mostly, but often times also Latex. My biggest problem is that I often forget the correct table syntax for these markup languages, as well as what needs to be properly escaped in the inline data, for the table to render correctly. So, I often wish there was a GUI application, which provides a tabular framework - which I could stick "Always on Top" as a desktop window, and I could paste content into specific cells - before finally exporting the table as a code in the correct language. One application that partially allows this is Open/LibreOffice calc: The good thing here is that: I can drag and drop browser content into a specifically targeted table cell (here B2) "Rich" text / HTML code gets pasted For long content, the cell (column) width stays put as it originally was The bad thing is, that: when the cell height (due to content size) becomes larger than the calc window, it becomes nearly impossible to scroll calc contents up and down (at least with the mousewheel), as the view gets reset to top-right corner of the selected cell calc shows an "endless"/unlimited field of cells, so not exactly a "table" - which I find visually very confusing (and cognitively taxing) Can only export table to HTML What I would need is an application that: Allows for a limited size table, but with quick adding of rows and columns (e.g. via corresponding + buttons) Allows for quick setup of row and column height and width (as well as table size) Stays put at those sizes, regardless of size of content pasted in; if cell content overflows, cell scrollbars are shown (cell content could be possibly re-edited in a separate/new window); if table overflows over window size, window scrollbars are shown Exports table in multiple formats (I'd need both HTML and mediawiki), properly escaping cell content for each (possibility to strip HTML tags from content pasted in cells, to get plain text, is a plus) Targeting a specific cell in the table for the content paste operation is a must - it doesn't have to be drag'n'drop though, a right click over a cell with "Paste content" is enough. I'd also want the ability to click in a specific cell and type in (plain text) content immediately. So, my question is: is there an application out there that already does something like this? The reason I'm asking is that - as the screenshots show - for instance Libre/OpenOffice allows it, but only somewhat (as using it for that purpose is tedious). I know there exist some GUI editors for Linux (both for UI like guile or HTML like amaya); but I don't know them enough to pinpoint if any of them would offer this kind of functionality (and at least in my searches, that kind of functionality, if present in diverse software, seems not to be advertised). Note I'm not interested in styling an HTML table, which is why I haven't used "table designer" in the title, but "table editor" (in lack of better terms) - I'm interested in (quickly) adjusting row/column size of the table, and populating it with pasted data (which is possibly HTML) in a GUI; and finally exporting such a table as self-contained HTML (or other) code.

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  • RPi and Java Embedded GPIO: Sensor Connections for Java Enabled Interface

    - by hinkmond
    Now we're ready to connect the hardware needed to make a static electricity sensor for the Raspberry Pi and use Java code to access it through a GPIO port. First, very carefully bend the NTE312 (or MPF-102) transistor "gate" pin (see the diagram on the back of the package or refer to the pin diagram on the Web). You can see it in the inset photo on the bottom left corner. I bent the leftmost pin of the NTE312 transistor as I held the flat part toward me. That is going to be your antenna. So, connect one of the jumper wires to the bent pin. I used the dark green jumper wire (looks almost black; coiled at the bottom) in the photo. Then push the other 2 pins of the transistor into your breadboard. Connect one of the pins to Pin # 1 (3.3V) on the GPIO header of your RPi. See the diagram if you need to glance back at it. In the photo, that's the orange jumper wire. And connect the final unconnected transistor pin to Pin # 22 (GPIO25) on the RPi header. That's the blue jumper wire in my photo. For reference, connect the LED anode (long pin on a common anode LED/short pin on a common cathode LED, check your LED pin diagram) to the same breadboard hole that is connecting to Pin # 22 (same row of holes where the blue wire is connected), and connect the other pin of the LED to GROUND (row of holes that connect to the black wire in the photo). Test by blowing up a balloon, rubbing it on your hair (or your co-worker's hair, if you are hair-challenged) to statically charge it, and bringing it near your antenna (green wire in the photo). The LED should light up when it's near and go off when you pull it away. If you need more static charge, find a co-worker with really long hair, or rub the balloon on a piece of silk (which is just as good but not as fun). Next blog post is where we do some Java coding to access this sensor on your RPi. Finally, back to software! Ha! Hinkmond

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  • 2D Grid Map Connectivity Check (avoiding stack overflow)

    - by SombreErmine
    I am trying to create a routine in C++ that will run before a more expensive A* algorithm that checks to see if two nodes on a 2D grid map are connected or not. What I need to know is a good way to accomplish this sequentially rather than recursively to avoid overflowing the stack. What I've Done Already I've implemented this with ease using a recursive algorithm; however, depending upon different situations it will generate a stack overflow. Upon researching this, I've come to the conclusion that it is overflowing the stack because of too many recursive function calls. I am sure that my recursion does not enter an infinite loop. I generate connected sets at the beginning of the level, and then I use those connected sets to determine connectivity on the fly later. Basically, the generating algorithm starts from left-to-right top-to-bottom. It skips wall nodes and marks them as visited. Whenever it reaches a walkable node, it recursively checks in all four cardinal directions for connected walkable nodes. Every node that gets checked is marked as visited so they aren't handled twice. After checking a node, it is added to either a walls set, a doors set, or one of multiple walkable nodes sets. Once it fills that area, it continues the original ltr ttb loop skipping already-visited nodes. I've also looked into flood-fill algorithms, but I can't make sense of the sequential algorithms and how to adapt them. Can anyone suggest a better way to accomplish this without causing a stack overflow? The only way I can think of is to do the left-to-right top-to-bottom loop generating connected sets on a row basis. Then check the previous row to see if any of the connected sets are connected and then join the sets that are. I haven't decided on the best data structures to use for that though. I also just thought about having the connected sets pre-generated outside the game, but I wouldn't know where to start with creating a tool for that. Any help is appreciated. Thanks!

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  • I'm blogging again, and about time too

    - by fatherjack
    No, seriously, this one is about time. I recently had an issue in a work database where a query was giving random results, sometimes the query would return a row and other times it wouldn't. There was quite a bit of work distilling the query down to find the reason for this and I'll try to explain by demonstrating what was happening by using some sample data in a table with rather a contrived use case. Let's assume we have a table that is designed to have a start and end date for something, maybe...(read more)

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