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  • WEB203 &ndash; Jump into Silverlight!&hellip; and Become Effective Immediately with Tim Huckaby, Fou

    - by Robert Burger
    Getting ready for the good stuff. Definitely wish there were more Silverlight and WCF RIA sessions, but this is a start.  Was lucky to get a coveted power-enabled seat.  Luckily, due to my trustily slow Verizon data card, I can get these notes out amidst a total Internet outage here.  This is the second breakout session of the day, and is by far standing-room only.  I stepped out before the session started to get a cool Diet COKE and wouldn’t have gotten back in if I didn’t already have a seat. Tim says this is an intro session and that he’s been begging for intro sessions at TechEd for years and that by looking at this audience, he thinks the demand is there.  Admittedly, I didn’t know this was an intro session, or I might have gone elsewhere.  But, it was the very first Silverlight session, so I had to be here. Tim says he will be providing a very good comprehensive reference application at the end of the presentation.  He has just demoed it, and it is a full CRUD-based Sales Manager application based on…  AdventureWorks! Session Agenda What it is / How to get started Declarative Programming Layout and Controls, Events and Commands Working with Data Adding Style to Your Application   Silverlight…  “WPF Light” Why is the download 4.2MB?  Because the direct competitor is a 4.2MB download.  There is no technical reason it is not the entire framework.  It is purely to “be competitive”.   Getting Started Get all of the following downloads from www.silverlight.net/getstarted Install VS2010 or Visual Web Developer Express 2010 Install Silverlight 4 Tools for VS2010 Install Expression Blend 4 Install the Silverlight 4 Toolkit   Reference Application Features Uses MVVM pattern – a way to move data access code that would normally be inline within the UI and placing it in nice data access libraries Images loaded dynamically from the database, converting GIF to PNG because Silverlight does not support GIF. LINQ to SQL is the data access model WCF is the data provider and is using binary message encoding   Declarative Programming XAML replaces code for UI representation Attributes control Layout and Style Event handlers wired-up in XAML Declarative Data Binding   Layout Overview Content rendering flows inside of parent Fixed positioning (Canvas) is seldom used Panels are used to house content Margins and Padding over fixed size   Panels StackPanel – Arranges child elements into a single line oriented horizontally or vertically Grid – A flexible grid are that consists of rows and columns Canvas – An are where positions are specifically fixed WrapPanel (in Toolkit) – Positions child elements in sequential position left to right and top to bottom. DockPanel (in Toolkit) – Positions child controls within a dockable area   Positioning Horizontal and Vertical Alignment Margin – Separates an element from neighboring elements Padding – Enlarges the effective size of an element by a thickness   Controls Overview Not all controls created equal Silverlight, as a subset of WPF, so many WPF controls do not exist in the core Siverlight release Silverlight Toolkit continues to add controls, but are released in different quality bands Plenty of good 3rd party controls to fill the gaps Windows Phone 7 is to have 95% of controls available in Silverlight Core and Toolkit.   Events and Commands Standard .NET Events Routed Events Commands – based on the ICommand interface – logical action that can be invoked in several ways   Adding Style to Your Application Resource Dictionaries – Contains a hash table of key/value pairs.  Silverlight can only use Static Resources whereas WPF can also use Dynamic Resources Visual State Manager Silverlight 4 supports Implicit styles ResourceDictionary.MergedDictionaries combines many different file-based resources   Downloads

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  • July, the 31 Days of SQL Server DMO’s – Day 19 (sys.dm_exec_query_stats)

    - by Tamarick Hill
    The sys.dm_exec_query_stats DMV is one of the most useful DMV’s out there when it comes to performance tuning. If you have been keeping up with this blog series this month, you know that I started out on Day 1 reviewing many of the DMV’s within the ‘exec’ namespace. I’m not sure how I missed this one considering how valuable it is, but hey, they say it’s better late than never right?? On Day 7 and Day 8 we reviewed the sys.dm_exec_procedure_stats and sys.dm_exec_trigger_stats respectively. This sys.dm_exec_query_stats DMV is very similar to these two. As a matter of fact, this DMV will return all of the information you saw in the other two DMV’s, but in addition to that, you can see stats for all queries that have cached execution plans on your server. You can even see stats for statements that are ran Ad-Hoc as long as they are still cached in the buffer pool. To better illustrate this DMV, let have a quick look at it: SELECT * FROM sys.dm_exec_query_stats As you can see, there is a lot of information returned from this DMV. I wont go into detail about each and every one of these columns, but I will touch on a few of them briefly. The first column is the ‘sql_handle’, which if you remember from Day 4 of our blog series, I explained how you can use this column to extract the actual SQL text that was executed. The next columns statement_start_offset and statement_end_offset provide you a way of extracting the exact SQL statement that was executed as part of a batch. The plan_handle column is used to extract the Execution plan that was used, which we talked about during Day 5 of this blog series. Later in the result set, you have columns to identify how many times a particular statement was executed, how much CPU time it used, how many reads/writes it performed, the duration, how many rows were returned, etc. These columns provide you with a solid avenue to begin your performance optimization. The last column I will touch on is the query_plan_hash column. A lot of times when you have Dynamic SQL running on your server, you have similar statements with different parameter values being passed in. Many times these types of statements will get similar execution plans and then a Binary hash value can be generated based on these similar plans. This query plan hash can be used to find the cost of all queries that have similar execution plans and then you can tune based on that plan to improve the performance of all of the individual queries. This is a very powerful way of identifying and tuning Ad-hoc statements that run on your server. As I stated earlier, this sys.dm_exec_query_stats DMV is a very powerful and recommended DMV for performance tuning. You are able to quickly identify statements that are running on your server and analyze their impact on system resources. Using this DMV to track down the biggest performance killers on your server will allow you to make the biggest gains once you focus your tuning efforts on those top offenders. For more information about this DMV, please see the below Books Online link: http://msdn.microsoft.com/en-us/library/ms189741.aspx Follow me on Twitter @PrimeTimeDBA

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  • Stretch in multiple components using af:popup, af:region, af:panelTabbed

    - by Arvinder Singh
    Case study: I have a pop-up(dialogue) that contains a region(separate taskflow) showing a tab. The contents of this tab is in a region having a separate taskflow. The jsff page of this taskflow contains a panelSplitter which in turn contains a table. In short the components are : pop-up(dialogue) --> region(separate taskflow) --> tab --> region(separate taskflow) --> panelSplitter --> table At times the tab is not displayed with 100% width or the table in panelSplitter is not 100% visible or the splitter is not visible. Maintaining the stretch for all the components is difficult......not any more!!! Below is the solution that you can make use of in many similar scenarios. I am mentioning the major code snippets affecting the stretch and alignment. pop-up: <af:popup> <af:dialog id="d2" type="none" title="" inlineStyle="width:1200px"> <af:region value="#{bindings.PriceChangePopupFlow1.regionModel}" id="r1"/> </af:dialog> The above region is a jsff containing multiple tabs. I am showing code for a single tab. I kept the tab in a panelStretchLayout. <af:panelStretchLayout id="psl1" topHeight="300px" styleClass="AFStretchWidth"> <af:panelTabbed id="pt1"> <af:showDetailItem text="PO Details" id="sdi1" stretchChildren="first" > <af:region value="#{bindings.PriceChangePurchaseOrderFlow1.regionModel}" id="r1" binding="# {pageFlowScope.priceChangePopupBean.poDetailsRegion}" /> This "region" displays a .jsff containing a table in a panelSplitter. <af:panelSplitter id="ps1"  orientation="horizontal" splitterPosition="700"> <f:facet name="first"> <af:panelHeader text="PurchaseOrder" id="ph1"> <af:table id="md1" rows="#{bindings.PurchaseOrderVO.rangeSize}" That's it!!! We're done... Note the stretchChildren="first" attribute in the af:showDetailItem. That does the trick for us. Oracle docs say the following about stretchChildren :  Valid Values: none, first The stretching behavior for children. Acceptable values include: "none": does not attempt to stretch any children (the default value and the value you need to use if you have more than a single child; also the value you need to use if the child does not support being stretched) "first": stretches the first child (not to be used if you have multiple children as such usage will produce unreliable results; also not to be used if the child does not support being stretched)

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  • SQL SERVER – Query Hint – Contest Win Joes 2 Pros Combo (USD 198) – Day 1 of 5

    - by pinaldave
    August 2011 we ran a contest where every day we give away one book for an entire month. The contest had extreme success. Lots of people participated and lots of give away. I have received lots of questions if we are doing something similar this month. Absolutely, instead of running a contest a month long we are doing something more interesting. We are giving away USD 198 worth gift every day for this week. We are giving away Joes 2 Pros 5 Volumes (BOOK) SQL 2008 Development Certification Training Kit every day. One copy in India and One in USA. Total 2 of the giveaway (worth USD 198). All the gifts are sponsored from the Koenig Training Solution and Joes 2 Pros. The books are available here Amazon | Flipkart | Indiaplaza How to Win: Read the Question Read the Hints Answer the Quiz in Contact Form in following format Question Answer Name of the country (The contest is open for USA and India residents only) 2 Winners will be randomly selected announced on August 20th. Question of the Day: Which of the following queries will return dirty data? a) SELECT * FROM Table1 (READUNCOMMITED) b) SELECT * FROM Table1 (NOLOCK) c) SELECT * FROM Table1 (DIRTYREAD) d) SELECT * FROM Table1 (MYLOCK) Query Hints: BIG HINT POST Most SQL people know what a “Dirty Record” is. You might also call that an “Intermediate record”. In case this is new to you here is a very quick explanation. The simplest way to describe the steps of a transaction is to use an example of updating an existing record into a table. When the insert runs, SQL Server gets the data from storage, such as a hard drive, and loads it into memory and your CPU. The data in memory is changed and then saved to the storage device. Finally, a message is sent confirming the rows that were affected. For a very short period of time the update takes the data and puts it into memory (an intermediate state), not a permanent state. For every data change to a table there is a brief moment where the change is made in the intermediate state, but is not committed. During this time, any other DML statement needing that data waits until the lock is released. This is a safety feature so that SQL Server evaluates only official data. For every data change to a table there is a brief moment where the change is made in this intermediate state, but is not committed. During this time, any other DML statement (SELECT, INSERT, DELETE, UPDATE) needing that data must wait until the lock is released. This is a safety feature put in place so that SQL Server evaluates only official data. Additional Hints: I have previously discussed various concepts from SQL Server Joes 2 Pros Volume 1. SQL Joes 2 Pros Development Series – Dirty Records and Table Hints SQL Joes 2 Pros Development Series – Row Constructors SQL Joes 2 Pros Development Series – Finding un-matching Records SQL Joes 2 Pros Development Series – Efficient Query Writing Strategy SQL Joes 2 Pros Development Series – Finding Apostrophes in String and Text SQL Joes 2 Pros Development Series – Wildcard – Querying Special Characters SQL Joes 2 Pros Development Series – Wildcard Basics Recap Next Step: Answer the Quiz in Contact Form in following format Question Answer Name of the country (The contest is open for USA and India) Bonus Winner Leave a comment with your favorite article from the “additional hints” section and you may be eligible for surprise gift. There is no country restriction for this Bonus Contest. Do mention why you liked it any particular blog post and I will announce the winner of the same along with the main contest. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Simple Demo of New Cardinality Estimation Features of SQL Server 2014

    - by Pinal Dave
    SQL Server 2014 has new cardinality estimation logic/algorithm. The cardinality estimation logic is responsible for quality of query plans and majorly responsible for improving performance for any query. This logic was not updated for quite a while, but in the latest version of SQL Server 2104 this logic is re-designed. The new logic now incorporates various assumptions and algorithms of OLTP and warehousing workload. Cardinality estimates are a prediction of the number of rows in the query result. The query optimizer uses these estimates to choose a plan for executing the query. The quality of the query plan has a direct impact on improving query performance. ~ Souce MSDN Let us see a quick example of how cardinality improves performance for a query. I will be using the AdventureWorks database for my example. Before we start with this demonstration, remember that even though you have SQL Server 2014 to see the effect of new cardinality estimates, you will need your database compatibility mode set to 120 which is for SQL Server 2014. If your server instance of SQL Server 2014 but you have set up your database compatibility mode to 110 or any other earlier version, you will get performance from your query like older version of SQL Server. Now we will execute following query in two different compatibility mode and see its performance. (Note that my SQL Server instance is of version 2014). USE AdventureWorks2014 GO -- ------------------------------- -- NEW Cardinality Estimation ALTER DATABASE AdventureWorks2014 SET COMPATIBILITY_LEVEL = 120 GO EXEC [dbo].[uspGetManagerEmployees] 44 GO -- ------------------------------- -- Old Cardinality Estimation ALTER DATABASE AdventureWorks2014 SET COMPATIBILITY_LEVEL = 110 GO EXEC [dbo].[uspGetManagerEmployees] 44 GO Result of Statistics IO Compatibility level 120 Table ‘Person’. Scan count 0, logical reads 6, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Employee’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Compatibility level 110 Table ‘Worktable’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Person’. Scan count 0, logical reads 137, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Employee’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. You will notice in the case of compatibility level 110 there 137 logical read from table person where as in the case of compatibility level 120 there are only 6 physical reads from table person. This drastically improves the performance of the query. If we enable execution plan, we can see the same as well. I hope you will find this quick example helpful. You can read more about this in my latest Pluralsight Course. Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Using the RSSBus Salesforce Excel Add-In From Excel Macros (VBA)

    - by dataintegration
    The RSSBus Salesforce Excel Add-In makes it easy to retrieve and update data from Salesforce from within Microsoft Excel. In addition to the built-in wizards that make data manipulation possible without code, the full functionality of the RSSBus Excel Add-Ins is available programmatically with Excel Macros (VBA) and Excel Functions. This article shows how to write an Excel macro that can be used to perform bulk inserts into Salesforce. Although this article uses the Salesforce Excel Add-In as an example, the same process can be applied to any of the Excel Add-Ins available on our website. Step 1: Download and install the RSSBus Excel Add-In available on our website. Step 2: Open Excel and create place holder cells for the connection details that are needed from the macro. In this article, a spreadsheet will be created for batch inserts, and these cells will store the connection details, and will be used to report the job Id, the batch Id, and the batch status. Step 3: Switch to the Developer tab in Excel. Add a new button on the spreadsheet, and create a new macro associated with it. This macro will contain the code needed to insert a batch of rows into Salesforce. Step 4: Add a reference to the Excel Add-In by selecting Tools --> References --> RSSBus Excel Add-In. The macro functions of the Excel Add-In will be available once the reference has been added. The following code shows how to call a Stored Procedure. In this example, a job is created to insert Leads by calling the CreateJob stored procedure. CreateJob returns a jobId that can be used to upload a large number of Leads in one transaction. Note the use of cells B1, B2, B3, and B4 that were created in Step 2 to read the connection settings from the Excel SpreadSheet and to write out the status of the procedure. methodName = "CreateJob" module.SetProviderName ("Salesforce") nameArray = Array("ObjectName", "Action", "ConcurrencyMode") valueArray = Array("Lead", "insert", "Serial") user = Range("B1").value pass = Range("B2").value atoken = Range("B3").value If (Not user = "" And Not pass = "" And Not atoken = "") Then module.SetConnectionString ("User=" + user + ";Password=" + pass + ";Access Token=" + atoken + ";") If module.CallSP(methodName, nameArray, valueArray) Then Dim ColumnCount As Integer ColumnCount = module.GetColumnCount Dim idIndex As Integer For Count = 0 To ColumnCount - 1 Dim colName As String colName = module.GetColumnName(Count) If module.GetColumnName(Count) = "id" Then idIndex = Count End If Next While (Not module.EOF) Range("B4").value = module.GetValue(idIndex) module.MoveNext Wend Else MsgBox "The CreateJob query failed." End If Exit Sub Else MsgBox "Please specify the connection details." Exit Sub End If Error: MsgBox "ERROR: " & Err.Description Step 5: Add the code to your macro. If you use the code above, you can check the results at Salesforce.com. They can be seen at Administration Setup -> Monitoring -> Bulk Data Load Jobs. Download the attached sample file for a more complete demo. Distributing an Excel File With Macros An Excel file with macros is saved using the .xlms extension. The code for the macro remains in the Excel file, and you can distribute your Excel file to any machine where the RSSBus Salesforce Excel Add-In is already installed. Macro Sample File Please download the fully functional sample excel file that includes the code referenced here. You will also need the RSSBus Excel Add-In to make the connection. You can download a free trial here. Note: You may get an error message stating: "Can't find project or library." in Excel 2007, since this example is made using Excel 2010. To resolve this, navigate to Tools -> References and uncheck the "MISSING: RSSBus Excel Add-In", then scroll down and check the "RSSBus Excel Add-In" listed below it.

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  • A quick look at: sys.dm_os_buffer_descriptors

    - by Jonathan Allen
    SQL Server places data into cache as it reads it from disk so as to speed up future queries. This dmv lets you see how much data is cached at any given time and knowing how this changes over time can help you ensure your servers run smoothly and are adequately resourced to run your systems. This dmv gives the number of cached pages in the buffer pool along with the database id that they relate to: USE [tempdb] GO SELECT COUNT(*) AS cached_pages_count , CASE database_id WHEN 32767 THEN 'ResourceDb' ELSE DB_NAME(database_id) END AS Database_name FROM sys.dm_os_buffer_descriptors GROUP BY DB_NAME(database_id) , database_id ORDER BY cached_pages_count DESC; This gives you results which are quite useful, but if you add a new column with the code: …to convert the pages value to show a MB value then they become more relevant and meaningful. To see how your server reacts to queries, start up SSMS and connect to a test server and database – mine is called AdventureWorks2008. Make sure you start from a know position by running: -- Only run this on a test server otherwise your production server's-- performance may drop off a cliff and your phone will start ringing. DBCC DROPCLEANBUFFERS GO Now we can run a query that would normally turn a DBA’s hair white: USE [AdventureWorks2008] go SELECT * FROM [Sales].[SalesOrderDetail] AS sod INNER JOIN [Sales].[SalesOrderHeader] AS soh ON [sod].[SalesOrderID] = [soh].[SalesOrderID] …and then check our cache situation: A nice low figure – not! Almost 2000 pages of data in cache equating to approximately 15MB. Luckily these tables are quite narrow; if this had been on a table with more columns then this could be even more dramatic. So, let’s make our query more efficient. After resetting the cache with the DROPCLEANBUFFERS and FREEPROCCACHE code above, we’ll only select the columns we want and implement a WHERE predicate to limit the rows to a specific customer. SELECT [sod].[OrderQty] , [sod].[ProductID] , [soh].[OrderDate] , [soh].[CustomerID] FROM [Sales].[SalesOrderDetail] AS sod INNER JOIN [Sales].[SalesOrderHeader] AS soh ON [sod].[SalesOrderID] = [soh].[SalesOrderID] WHERE [soh].[CustomerID] = 29722 …and check our effect cache: Now that is more sympathetic to our server and the other systems sharing its resources. I can hear you asking: “What has this got to do with logging, Jonathan?” Well, a smart DBA will keep an eye on this metric on their servers so they know how their hardware is coping and be ready to investigate anomalies so that no ‘disruptive’ code starts to unsettle things. Capturing this information over a period of time can lead you to build a picture of how a database relies on the cache and how it interacts with other databases. This might allow you to decide on appropriate schedules for over night jobs or otherwise balance the work of your server. You could schedule this job to run with a SQL Agent job and store the data in your DBA’s database by creating a table with: IF OBJECT_ID('CachedPages') IS NOT NULL DROP TABLE CachedPages CREATE TABLE CachedPages ( cached_pages_count INT , MB INT , Database_Name VARCHAR(256) , CollectedOn DATETIME DEFAULT GETDATE() ) …and then filling it with: INSERT INTO [dbo].[CachedPages] ( [cached_pages_count] , [MB] , [Database_Name] ) SELECT COUNT(*) AS cached_pages_count , ( COUNT(*) * 8.0 ) / 1024 AS MB , CASE database_id WHEN 32767 THEN 'ResourceDb' ELSE DB_NAME(database_id) END AS Database_name FROM sys.dm_os_buffer_descriptors GROUP BY database_id After this has been left logging your system metrics for a while you can easily see how your databases use the cache over time and may see some spikes that warrant your attention. This sort of logging can be applied to all sorts of server statistics so that you can gather information that will give you baseline data on how your servers are performing. This means that when you get a problem you can see what statistics are out of their normal range and target you efforts to resolve the issue more rapidly.

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  • Big Data – Data Mining with Hive – What is Hive? – What is HiveQL (HQL)? – Day 15 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the operational database in Big Data Story. In this article we will understand what is Hive and HQL in Big Data Story. Yahoo started working on PIG (we will understand that in the next blog post) for their application deployment on Hadoop. The goal of Yahoo to manage their unstructured data. Similarly Facebook started deploying their warehouse solutions on Hadoop which has resulted in HIVE. The reason for going with HIVE is because the traditional warehousing solutions are getting very expensive. What is HIVE? Hive is a datawarehouseing infrastructure for Hadoop. The primary responsibility is to provide data summarization, query and analysis. It  supports analysis of large datasets stored in Hadoop’s HDFS as well as on the Amazon S3 filesystem. The best part of HIVE is that it supports SQL-Like access to structured data which is known as HiveQL (or HQL) as well as big data analysis with the help of MapReduce. Hive is not built to get a quick response to queries but it it is built for data mining applications. Data mining applications can take from several minutes to several hours to analysis the data and HIVE is primarily used there. HIVE Organization The data are organized in three different formats in HIVE. Tables: They are very similar to RDBMS tables and contains rows and tables. Hive is just layered over the Hadoop File System (HDFS), hence tables are directly mapped to directories of the filesystems. It also supports tables stored in other native file systems. Partitions: Hive tables can have more than one partition. They are mapped to subdirectories and file systems as well. Buckets: In Hive data may be divided into buckets. Buckets are stored as files in partition in the underlying file system. Hive also has metastore which stores all the metadata. It is a relational database containing various information related to Hive Schema (column types, owners, key-value data, statistics etc.). We can use MySQL database over here. What is HiveSQL (HQL)? Hive query language provides the basic SQL like operations. Here are few of the tasks which HQL can do easily. Create and manage tables and partitions Support various Relational, Arithmetic and Logical Operators Evaluate functions Download the contents of a table to a local directory or result of queries to HDFS directory Here is the example of the HQL Query: SELECT upper(name), salesprice FROM sales; SELECT category, count(1) FROM products GROUP BY category; When you look at the above query, you can see they are very similar to SQL like queries. Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Pig. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Whether to use UNION or OR in SQL Server Queries

    - by Dinesh Asanka
    Recently I came across with an article on DB2 about using Union instead of OR. So I thought of carrying out a research on SQL Server on what scenarios UNION is optimal in and which scenarios OR would be best. I will analyze this with a few scenarios using samples taken  from the AdventureWorks database Sales.SalesOrderDetail table. Scenario 1: Selecting all columns So we are going to select all columns and you have a non-clustered index on the ProductID column. --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR ProductID =709 OR ProductID =998 OR ProductID =875 OR ProductID =976 OR ProductID =874 --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 709 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 998 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 875 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 976 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 874 So query 1 is using OR and the later is using UNION. Let us analyze the execution plans for these queries. Query 1 Query 2 As expected Query 1 will use Clustered Index Scan but Query 2, uses all sorts of things. In this case, since it is using multiple CPUs you might have CX_PACKET waits as well. Let’s look at the profiler results for these two queries: CPU Reads Duration Row Counts OR 78 1252 389 3854 UNION 250 7495 660 3854 You can see from the above table the UNION query is not performing well as the  OR query though both are retuning same no of rows (3854).These results indicate that, for the above scenario UNION should be used. Scenario 2: Non-Clustered and Clustered Index Columns only --Query 1 : OR SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR ProductID =709 OR ProductID =998 OR ProductID =875 OR ProductID =976 OR ProductID =874 GO --Query 2 : UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 709 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 998 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 875 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 976 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 874 GO So this time, we will be selecting only index columns, which means these queries will avoid a data page lookup. As in the previous case we will analyze the execution plans: Query 1 Query 2 Again, Query 2 is more complex than Query 1. Let us look at the profile analysis: CPU Reads Duration Row Counts OR 0 24 208 3854 UNION 0 38 193 3854 In this analyzis, there is only slight difference between OR and UNION. Scenario 3: Selecting all columns for different fields Up to now, we were using only one column (ProductID) in the where clause.  What if we have two columns for where clauses and let us assume both are covered by non-clustered indexes? --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR CarrierTrackingNumber LIKE 'D0B8%' --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE CarrierTrackingNumber  LIKE 'D0B8%' Query 1 Query 2: As we can see, the query plan for the second query has improved. Let us see the profiler results. CPU Reads Duration Row Counts OR 47 1278 443 1228 UNION 31 1334 400 1228 So in this case too, there is little difference between OR and UNION. Scenario 4: Selecting Clustered index columns for different fields Now let us go only with clustered indexes: --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR CarrierTrackingNumber LIKE 'D0B8%' --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE CarrierTrackingNumber  LIKE 'D0B8%' Query 1 Query 2 Now both execution plans are almost identical except is an additional Stream Aggregate is used in the first query. This means UNION has advantage over OR in this scenario. Let us see profiler results for these queries again. CPU Reads Duration Row Counts OR 0 319 366 1228 UNION 0 50 193 1228 Now see the differences, in this scenario UNION has somewhat of an advantage over OR. Conclusion Using UNION or OR depends on the scenario you are faced with. So you need to do your analyzing before selecting the appropriate method. Also, above the four scenarios are not all an exhaustive list of scenarios, I selected those for the broad description purposes only.

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  • Spritesheet per pixel collision XNA

    - by Jixi
    So basically i'm using this: public bool IntersectPixels(Rectangle rectangleA, Color[] dataA,Rectangle rectangleB, Color[] dataB) { int top = Math.Max(rectangleA.Top, rectangleB.Top); int bottom = Math.Min(rectangleA.Bottom, rectangleB.Bottom); int left = Math.Max(rectangleA.Left, rectangleB.Left); int right = Math.Min(rectangleA.Right, rectangleB.Right); for (int y = top; y < bottom; y++) { for (int x = left; x < right; x++) { Color colorA = dataA[(x - rectangleA.Left) + (y - rectangleA.Top) * rectangleA.Width]; Color colorB = dataB[(x - rectangleB.Left) + (y - rectangleB.Top) * rectangleB.Width]; if (colorA.A != 0 && colorB.A != 0) { return true; } } } return false; } In order to detect collision, but i'm unable to figure out how to use it with animated sprites. This is my animation update method: public void AnimUpdate(GameTime gameTime) { if (!animPaused) { animTimer += (float)gameTime.ElapsedGameTime.TotalMilliseconds; if (animTimer > animInterval) { currentFrame++; animTimer = 0f; } if (currentFrame > endFrame || endFrame <= currentFrame || currentFrame < startFrame) { currentFrame = startFrame; } objRect = new Rectangle(currentFrame * TextureWidth, frameRow * TextureHeight, TextureWidth, TextureHeight); origin = new Vector2(objRect.Width / 2, objRect.Height / 2); } } Which works with multiple rows and columns. and how i call the intersect: public bool IntersectPixels(Obj me, Vector2 pos, Obj o) { Rectangle collisionRect = new Rectangle(me.objRect.X, me.objRect.Y, me.objRect.Width, me.objRect.Height); collisionRect.X += (int)pos.X; collisionRect.Y += (int)pos.Y; if (IntersectPixels(collisionRect, me.TextureData, o.objRect, o.TextureData)) { return true; } return false; } Now my guess is that i have to update the textureData everytime the frame changes, no? If so then i already tried it and miserably failed doing so :P Any hints, advices? If you need to see any more of my code just let me know and i'll update the question. Updated almost functional collisionRect: collisionRect = new Rectangle((int)me.Position.X, (int)me.Position.Y, me.Texture.Width / (int)((me.frameCount - 1) * me.TextureWidth), me.Texture.Height); What it does now is "move" the block up 50%, shouldn't be too hard to figure out. Update: Alright, so here's a functional collision rectangle(besides the height issue) collisionRect = new Rectangle((int)me.Position.X, (int)me.Position.Y, me.TextureWidth / (int)me.frameCount - 1, me.TextureHeight); Now the problem is that using breakpoints i found out that it's still not getting the correct color values of the animated sprite. So it detects properly but the color values are always: R:0 G:0 B:0 A:0 ??? disregard that, it's not true afterall =P For some reason now the collision area height is only 1 pixel..

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  • JDeveloper 11g R1 (11.1.1.4.0) - New Features on ADF Desktop Integration Explained

    - by juan.ruiz
    One of the areas that introduced many new features on the latest release (11.1.1.4.0)  of JDeveloper 11g R1 is ADF Desktop integration - in this article I’ll provide an overview of these new features. New ADF Desktop Integration Ribbon in Excel - After installing the ADF desktop integration add-in and depending on the mode in which you open the desktop integration workbook, the ADF Desktop integration ribbon for design time and runtime are displayed as a separate tab within Excel. In previous version the ADF Desktop integration environment used to be placed inside the add-ins tab. Above you can see both, design time ribbon as well as runtime ribbon. On the design time ribbon you can manage the workbook and worksheet properties, worksheet component properties, diagnostics, execution and publication of the workbook. The runtime version of the ribbon is totally customizable and represents what it used to be the runtime menu on the spreadsheet, in this ribbon you can include all the operations and actions that could be executed by the end user while working with the spreadsheet data. Diagnostics - A very important aspect for developers is how to debug or verify the interactions of the client with the server, for that ADF desktop integration has provided since day one a series of diagnostics tools. In this release the diagnostics tools are more visible and are really easy to configure. You can access the client console while testing the workbook, or you can simple dump all the messages to a log file – having the ability of setting the output level for both. Security - There are a number of enhancements on security but the one with more impact for developers is tha security now is optional when using ADF Desktop Integration. Until this version every time that you wanted to work with ADFdi it was a must that the application was previously secured. In this release security is optional which means that if you have previously defined security on your application, then you must secure the ADFdi servlet as explained in one of my previous (ADD LINK) posts. In the other hand, if but the time that you start working with ADFdi you have not defined security, you can test and publish your workbooks without adding security. Support for Continuous Integration - In this release we have added tooling for continuous integration building. in the ADF desktop integration space, the concept translates to adding functionality that developers can use to publish ADFdi workbooks as part of their entire application build. For that purpose, we have a publish tool that can be easily invoke from an ANT task such that all the design time workbooks are re-published into the latest version of the application building process. Key Column - At runtime, on any worksheet containing editable tables you will notice a new additional column called the key column. The purpose of this column is to make the end user aware that all rows on the table need to be selected at the time of sorting. The users cannot alter the value of this column. From the developers points of view there are no steps required in order to have the key column included into the worksheets. Installation and Creation of New Workbooks - Both use cases can be executed now directly from JDeveloper. As part of the Tools menu options the developer can install the ADF desktop integration designer. Also, creating new workbooks that previously was done through that convert tool shipped with JDeveloper is now automatic done from the New Gallery. Creating a new ADFdi workbook adds metadata information information to the Excel workbook so you can work in design time. Other Enhancements Support for Excel 2010 and the ADF components ready-only enabled don’t allow to change its value – the cell in Excel is automatically protected, this could cause confusion among customers of previous releases.

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  • T-SQL in Chicago – the LobsterPot teams with DataEducation

    - by Rob Farley
    In May, I’ll be in the US. I have board meetings for PASS at the SQLRally event in Dallas, and then I’m going to be spending a bit of time in Chicago. The big news is that while I’m in Chicago (May 14-16), I’m going to teach my “Advanced T-SQL Querying and Reporting: Building Effectiveness” course. This is a course that I’ve been teaching since the 2005 days, and have modified over time for 2008 and 2012. It’s very much my most popular course, and I love teaching it. Let me tell you why. For years, I wrote queries and thought I was good at it. I was a developer. I’d written a lot of C (and other, more fun languages like Prolog and Lisp) at university, and then got into the ‘real world’ and coded in VB, PL/SQL, and so on through to C#, and saw SQL (whichever database system it was) as just a way of getting the data back. I could write a query to return just about whatever data I wanted, and that was good. I was better at it than the people around me, and that helped. (It didn’t help my progression into management, then it just became a frustration, but for the most part, it was good to know that I was good at this particular thing.) But then I discovered the other side of querying – the execution plan. I started to learn about the translation from what I’d written into the plan, and this impacted my query-writing significantly. I look back at the queries I wrote before I understood this, and shudder. I wrote queries that were correct, but often a long way from effective. I’d done query tuning, but had largely done it without considering the plan, just inferring what indexes would help. This is not a performance-tuning course. It’s focused on the T-SQL that you read and write. But performance is a significant and recurring theme. Effective T-SQL has to be about performance – it’s the biggest way that a query becomes effective. There are other aspects too though – such as using constructs better. For example – I can write code that modifies data nicely, but if I haven’t learned about the MERGE statement and the way that it can impact things, I’m missing a few tricks. If you’re going to do this course, a good place to be is the situation I was in a few years before I wrote this course. You’re probably comfortable with writing T-SQL queries. You know how to make a SELECT statement do what you need it to, but feel there has to be a better way. You can write JOINs easily, and understand how to use LEFT JOIN to make sure you don’t filter out rows from the first table, but you’re coding blind. The first module I cover is on Query Execution. Take a look at the Course Outline at Data Education’s website. The first part of the first module is on the components of a SELECT statement (where I make you think harder about GROUP BY than you probably have before), but then we jump straight into Execution Plans. Some stuff on indexes is in there too, as is simplification and SARGability. Some of this is stuff that you may have heard me present on at conferences, but here you have me for three days straight. I’m sure you can imagine that we revisit these topics throughout the rest of the course as well, and you’d be right. In the second and third modules we look at a bunch of other aspects, including some of the T-SQL constructs that lots of people don’t know, and various other things that can help your T-SQL be, well, more effective. I’ve had quite a lot of people do this course and be itching to get back to work even on the first day. That’s not a comment about the jokes I tell, but because people want to look at the queries they run. LobsterPot Solutions is thrilled to be partnering with Data Education to bring this training to Chicago. Visit their website to register for the course. @rob_farley

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  • Recent improvements in Console Performance

    - by loren.konkus
    Recently, the WebLogic Server development and support organizations have worked with a number of customers to quantify and improve the performance of the Administration Console in large, distributed configurations where there is significant latency in the communications between the administration server and managed servers. These improvements fall into two categories: Constraining the amount of time that the Console stalls waiting for communication Reducing and streamlining the amount of data required for an update A few releases ago, we added support for a configurable domain-wide mbean "Invocation Timeout" value on the Console's configuration: general, advanced section for a domain. The default value for this setting is 0, which means wait indefinitely and was chosen for compatibility with the behavior of previous releases. This configuration setting applies to all mbean communications between the admin server and managed servers, and is the first line of defense against being blocked by a stalled or completely overloaded managed server. Each site should choose an appropriate timeout value for their environment and network latency. In the next release of WebLogic Server, we've added an additional console preference, "Management Operation Timeout", to the Console's shared preference page. This setting further constrains how long certain console pages will wait for slowly responding servers before returning partial results. While not all Console pages support this yet, key pages such as the Servers Configuration and Control table pages and the Deployments Control pages have been updated to support this. For example, if a user requests a Servers Table page and a Management Operation Timeout occurs, the table is displayed with both local configuration and remote runtime information from the responding managed servers and only local configuration information for servers that did not yet respond. This means that a troublesome managed server does not impede your ability to manage your domain using the Console. To support these changes, these Console pages have been re-written to use the Work Management feature of WebLogic Server to interact with each server or deployment concurrently, which further improves the responsiveness of these pages. The basic algorithm for these pages is: For each configuration mbean (ie, Servers) populate rows with configuration attributes from the fast, local mbean server Find a WorkManager For each server, Create a Work instance to obtain runtime mbean attributes for the server Schedule Work instance in the WorkManager Call WorkManager.waitForAll to wait WorkItems to finish, constrained by Management Operation Timeout For each WorkItem, if the runtime information obtained was not complete, add a message indicating which server has incomplete data Display collected data in table In addition to these changes to constrain how long the console waits for communication, a number of other changes have been made to reduce the amount and scope of managed server interactions for key pages. For example, in previous releases the Deployments Control table looked at the status of a deployment on every managed server, even those servers that the deployment was not currently targeted on. (This was done to handle an edge case where a deployment's target configuration was changed while it remained running on previously targeted servers.) We decided supporting that edge case did not warrant the performance impact for all, and instead only look at the status of a deployment on the servers it is targeted to. Comprehensive status continues to be available if a user clicks on the 'status' field for a deployment. Finally, changes have been made to the System Status portlet to reduce its impact on Console page display times. Obtaining health information for this display requires several mbean interactions with managed servers. In previous releases, this mbean interaction occurred with every display, and any delay or impediment in these interactions was reflected in the display time for every page. To reduce this impact, we've made several changes in this portlet: Using Work Management to obtain health concurrently Applying the operation timeout configuration to constrain how long we will wait Caching health information to reduce the cost during rapid navigation from page to page and only obtaining new health information if the previous information is over 30 seconds old. Eliminating heath collection if this portlet is minimized. Together, these Console changes have resulted in significant performance improvements for the customers with large configurations and high latency that we have worked with during their development, and some lesser performance improvements for those with small configurations and very fast networks. These changes will be included in the 11g Rel 1 patch set 2 (10.3.3.0) release of WebLogic Server.

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  • Some Original Expressions

    - by Phil Factor
    Guest Editorial for Simple-Talk newsletterIn a guest editorial for the Simple-Talk Newsletter, Phil Factor wonders if we are still likely to find some more novel and unexpected ways of using the newer features of Transact SQL: or maybe in some features that have always been there! There can be a great deal of fun to be had in trying out recent features of SQL Expressions to see if  they provide new functionality.  It is surprisingly rare to find things that couldn’t be done before, but in a different   and more cumbersome way; but it is great to experiment or to read of someone else making that discovery.  One such recent feature is the ‘table value constructor’, or ‘VALUES constructor’, that managed to get into SQL Server 2008 from Standard SQL.  This allows you to create derived tables of up to 1000 rows neatly within select statements that consist of  lists of row values.  E.g. SELECT Old_Welsh, number FROM (VALUES ('Un',1),('Dou',2),('Tri',3),('Petuar',4),('Pimp',5),('Chwech',6),('Seith',7),('Wyth',8),('Nau',9),('Dec',10)) AS WelshWordsToTen (Old_Welsh, number) These values can be expressions that return single values, including, surprisingly, subqueries. You can use this device to create views, or in the USING clause of a MERGE statement. Joe Celko covered  this here and here.  It can become extraordinarily handy to use once one gets into the way of thinking in these terms, and I’ve rewritten a lot of routines to use the constructor, but the old way of using UNION can be used the same way, but is a little slower and more long-winded. The use of scalar SQL subqueries as an expression in a VALUES constructor, and then applied to a MERGE, has got me thinking. It looks very clever, but what use could one put it to? I haven’t seen anything yet that couldn’t be done almost as  simply in SQL Server 2000, but I’m hopeful that someone will come up with a way of solving a tricky problem, just in the same way that a freak of the XML syntax forever made the in-line  production of delimited lists from an expression easy, or that a weird XML pirouette could do an elegant  pivot-table rotation. It is in this sort of experimentation where the community of users can make a real contribution. The dissemination of techniques such as the Number, or Tally table, or the unconventional ways that the UPDATE statement can be used, has been rapid due to articles and blogs. However, there is plenty to be done to explore some of the less obvious features of Transact SQL. Even some of the features introduced into SQL Server 2000 are hardly well-known. Certain operations on data are still awkward to perform in Transact SQL, but we mustn’t, I think, be too ready to state that certain things can only be done in the application layer, or using a CLR routine. With the vast array of features in the product, and with the tools that surround it, I feel that there is generally a way of getting tricky things done. Or should we just stick to our lasts and push anything difficult out into procedural code? I’d love to know your views.

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  • Antenna Aligner Part 4: Role'ing in the deep

    - by Chris George
    Since last time I've been trying to sort out the general workflow of the app. It's fundamentally not hard, there is a list of transmitters, you select a transmitter and it shows the compass view. Having done quite a bit of ajax/asp.net/html in the past, I immediately started off by creating two divs within my 'page', one for the list, one for the compass. Then using the onClick event in the list, this will switch the display attribute on the divs. This seemed to work, but did lead to some dodgy transitional redrawing artefacts which I was not happy with. So after some Googling I realised I was doing it all wrong! JQuery mobile has the concept of giving an object in html a data-role. By giving a div the attribute data-role="page" it is then treated as a separate page on the mobile device. Within the code, this is referenced like a html anchor in the form #mypage. Using this system, page transitions such as fade or slide are automatically applied which adds to the whole authenticity of the app! Here is a simple example: . <a href="#'compasspage">compass</a> . <div data-role="page" id="compasspage" data-add-back-btn="true"> But I don't want just a static link, I want to dynamically create my list, and get each list elements to switch to the compass page with the right information. So here is the jquery that I used to dynamically inject new <li> rows into the <ul> block. $('ul').append($('<li/>', {    //here appendin `<li>`     'data-role': "list-divider" }).append($('<a/>', {    //here appending `<a>` into `<li>`     'href': '#compasspage',     'data-transition': 'none',     'onclick': 'selectTx(' + i + ')',     'html': buttonHtml }))); $('ul').listview('refresh'); This is called within a for loop so the first 5 appropriate transmitters are used. There are several things of interest to note here. Firstly, I could not find a more elegant way to tell the target page which transmitter I've clicked on, so I have used the onclick event as well as the href attribute. The onclick event fires 'selectTx' which simply sets a global member variable to the specific index number I've clicked on. Yes it's not nice, but it works. Secondly, the data-transition attribute is set to 'none'. I wanted the transition between the pages to be a whooshy slidey effect. However this worked going to the compass page, but returning to the list page gave some undesirable visual artefacts (flickering, redrawing etc.). So I decided to remove the transitions all together, which was a shame. Thirdly, rather than embedding loads of html into the append command, I removed this out into a variable 'buttonHtml'. Doing this really tidied up my code. Until next time!

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  • Design pattern for logging changes in parent/child objects saved to database

    - by andrew
    I’ve got a 2 database tables in parent/child relationship as one-many. I’ve got three classes representing the data in these two tables: Parent Class { Public int ID {get; set;} .. other properties } Child Class { Public int ID {get;set;} Public int ParentID {get; set;} .. other properties } TogetherClass { Public Parent Parent; Public List<Child> ChildList; } Lastly I’ve got a client and server application – I’m in control of both ends so can make changes to both programs as I need to. Client makes a request for ParentID and receives a Together Class for the matching parent, and all of the child records. The client app may make changes to the children – add new children, remove or modify existing ones. Client app then sends the Together Class back to the server app. Server app needs to update the parent and child records in the database. In addition I would like to be able to log the changes – I’m doing this by having 2 separate tables one for Parent, one for child; each containing the same columns as the original plus date time modified, by whom and a list of the changes. I’m unsure as to the best approach to detect the changes in records – new records, records to be deleted, records with no fields changed, records with some fields changed. I figure I need to read the parent & children records and compare those to the ones in the Together Class. Strategy A: If Together class’s child record has an ID of say 0, that indicates a new record; insert. Any deleted child records are no longer in the Together Class; see if any of the comparison child records are not found in the Together class and delete if not found (Compare using ID). Check each child record for changes and if changed log. Strategy B: Make a new Updated TogetherClass UpdatedClass { Public Parent Parent {get; set} Public List<Child> ListNewChild {get;set;} Public List<Child> DeletedChild {get;set;} Public List<Child> ExistingChild {get;set;} // used for no changes and modified rows } And then process as per the list. The reason why I’m asking for ideas is that both of these solutions don’t seem optimal to me and I suspect this problem has been solved already – some kind of design pattern ? I am aware of one potential problem in this general approach – that where Client App A requests a record; App B requests same record; A then saves changes; B then saves changes which may overwrite changes A made. This is a separate locking issue which I’ll raise a separate question for if I’ve got trouble implementing. The actual implementation is c#, SQL Server and WCF between client and server - sharing a library containing the class implementations. Apologies if this is a duplicate post – I tried searching various terms without finding a match though.

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  • SQL Server IO handling mechanism can be severely affected by high CPU usage

    - by sqlworkshops
    Are you using SSD or SAN / NAS based storage solution and sporadically observe SQL Server experiencing high IO wait times or from time to time your DAS / HDD becomes very slow according to SQL Server statistics? Read on… I need your help to up vote my connect item – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage. Instead of taking few seconds, queries could take minutes/hours to complete when CPU is busy.In SQL Server when a query / request needs to read data that is not in data cache or when the request has to write to disk, like transaction log records, the request / task will queue up the IO operation and wait for it to complete (task in suspended state, this wait time is the resource wait time). When the IO operation is complete, the task will be queued to run on the CPU. If the CPU is busy executing other tasks, this task will wait (task in runnable state) until other tasks in the queue either complete or get suspended due to waits or exhaust their quantum of 4ms (this is the signal wait time, which along with resource wait time will increase the overall wait time). When the CPU becomes free, the task will finally be run on the CPU (task in running state).The signal wait time can be up to 4ms per runnable task, this is by design. So if a CPU has 5 runnable tasks in the queue, then this query after the resource becomes available might wait up to a maximum of 5 X 4ms = 20ms in the runnable state (normally less as other tasks might not use the full quantum).In case the CPU usage is high, let’s say many CPU intensive queries are running on the instance, there is a possibility that the IO operations that are completed at the Hardware and Operating System level are not yet processed by SQL Server, keeping the task in the resource wait state for longer than necessary. In case of an SSD, the IO operation might even complete in less than a millisecond, but it might take SQL Server 100s of milliseconds, for instance, to process the completed IO operation. For example, let’s say you have a user inserting 500 rows in individual transactions. When the transaction log is on an SSD or battery backed up controller that has write cache enabled, all of these inserts will complete in 100 to 200ms. With a CPU intensive parallel query executing across all CPU cores, the same inserts might take minutes to complete. WRITELOG wait time will be very high in this case (both under sys.dm_io_virtual_file_stats and sys.dm_os_wait_stats). In addition you will notice a large number of WAITELOG waits since log records are written by LOG WRITER and hence very high signal_wait_time_ms leading to more query delays. However, Performance Monitor Counter, PhysicalDisk, Avg. Disk sec/Write will report very low latency times.Such delayed IO handling also occurs to read operations with artificially very high PAGEIOLATCH_SH wait time (with number of PAGEIOLATCH_SH waits remaining the same). This problem will manifest more and more as customers start using SSD based storage for SQL Server, since they drive the CPU usage to the limits with faster IOs. We have a few workarounds for specific scenarios, but we think Microsoft should resolve this issue at the product level. We have a connect item open – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage - (with example scripts) to reproduce this behavior, please up vote the item so the issue will be addressed by the SQL Server product team soon.Thanks for your help and best regards,Ramesh MeyyappanHome: www.sqlworkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • How to display Sharepoint Data in a Windows Forms Application

    - by Michael M. Bangoy
    In this post I'm going to demonstrate how to retrieve Sharepoint data and display it on a Windows Forms Application. 1. Open Visual Studio 2010 and create a new Project. 2. In the project template select Windows Forms Application. 3. In order to communicate with Sharepoint from a Windows Forms Application we need to add the 2 Sharepoint Client DLL located in c:\Program Files\Common Files\Microsoft Shared\Web Server Extensions\14\ISAPI. 4. Select the Microsoft.Sharepoint.Client.dll and Microsoft.Sharepoint.Client.Runtime.dll. (Your solution should look like the one below) 5. Open the Form1 in design view and from the Toolbox menu Add a Button, TextBox, Label and DataGridView on the form. 6. Next double click on the Load Button, this will open the code view of the form. Add Using statement to reference the Sharepoint Client Library then create two method for the Load Site Title and LoadList. See below:   using System; using System.Collections.Generic; using System.ComponentModel; using System.Data; using System.Drawing; using System.Linq; using System.Text; using System.Security; using System.Windows.Forms; using SP = Microsoft.SharePoint.Client;   namespace ClientObjectModel {     public partial class Form1 : Form     {         // url of the Sharepoint site         const string _context = "theurlofthesharepointsite";         public Form1()         {             InitializeComponent();         }         private void Form1_Load(object sender, EventArgs e)         {                    }         private void getsitetitle()         {             SP.ClientContext context = new SP.ClientContext(_context);             SP.Web _site = context.Web;             context.Load(_site);             context.ExecuteQuery();             txttitle.Text = _site.Title;             context.Dispose();         }                 private void loadlist()         {             using (SP.ClientContext _clientcontext = new SP.ClientContext(_context))             {                 SP.Web _web = _clientcontext.Web;                 SP.ListCollection _lists = _clientcontext.Web.Lists;                 _clientcontext.Load(_lists);                 _clientcontext.ExecuteQuery();                 DataTable dt = new DataTable();                 DataColumn column;                 DataRow row;                 column = new DataColumn();                 column.DataType = Type.GetType("System.String");                 column.ColumnName = "List Title";                 dt.Columns.Add(column);                 foreach (SP.List listitem in _lists)                 {                     row = dt.NewRow();                     row["List Title"] = listitem.Title;                     dt.Rows.Add(row);                 }                 dataGridView1.DataSource = dt;             }                   }       private void cmdload_Click(object sender, EventArgs e)         {             getsitetitle();             loadlist();          }     } } 7. That’s it. Hit F5 to run the application then click the Load Button. Your screen should like the one below. Hope this helps.

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  • SSIS Debugging Tip: Using Data Viewers

    - by Jim Giercyk
    When you have an SSIS package error, it is often very helpful to see the data records that are causing the problem.  After all, if your input has 50,000 records and 1 of them has corrupt data, it can be a chore.  Your execution results will tell you which column contains the bad data, but not which record…..enter the Data Viewer. In this scenario I have created a truncation error.  The input length of [lastname] is 50, but the output table has a length of 15.  When it runs, at least one of the records causes the package to fail.     Now what?  We can tell from our execution results that there is a problem with [lastname], but we have no idea WHICH record?     Let’s identify the row that is actually causing the problem.  First, we grab the oft’ forgotten Row Count shape from our toolbar and connect it to the error output from our input query.  Remember that in order to intercept errors with the error output, you must redirect them.     The Row Count shape requires 1 integer variable.  For our purposes, we will not reference the variable, but it is still required in order for the package to run.  Typically we would use the variable to hold the number of rows in the table and refer back to it later in our process.  We are simply using the Row Count as a “Dead End” for errors.  I called my variable RowCounter.  To create a variable, with no shapes selected, right-click on the background and choose Variable.     Once we have setup the Row Count shape, we can right-click on the red line (error output) from the query, and select Data Viewers.  In the popup, we click the add button and we will see this:     There are other fancier options we can play with, but for now we just want to view the output in a grid.  WE select Grid, then click OK on all of the popup windows to shut them down.  We should now see a grid with a pair of glasses on the error output line.     So, we are ready to catch the error output in a grid and see that is causing the problem!  This time when we run the package, it does not fail because we directed the error to the Row Count.  We also get a popup window showing the error record in a grid.  If there were multiple errors we would see them all.     Indeed, the [lastname] column is longer than 15 characters.  Notice the last column in the grid, [Error Code – Description].  We knew this was a truncation error before we added the grid, but if you have worked with SSIS for any length of time, you know that some errors are much more obscure.  The description column can be very useful under those circumstances! Data viewers can be used any time we want to see the data that is actually in the pipeline;  they stop the package temporarily until we shut them.  Also remember that the Row Count shape can be used as a “Dead End”.  It is useful during development when we want to see the output from a dataflow, but don’t want to update a table or file with the data.  Data viewers are an invaluable tool for both development and debugging.  Just remember to REMOVE THEM before putting your package into production

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  • Crime Scene Investigation: SQL Server

    - by Rodney Landrum
    “The packages are running slower in Prod than they are in Dev” My week began with this simple declaration from one of our lead BI developers, quickly followed by an emailed spreadsheet demonstrating that, over 5 executions, an extensive ETL process was running average 630 seconds faster on Dev than on Prod. The situation needed some scientific investigation to determine why the same code, the same data, the same schema would yield consistently slower results on a more powerful server. Prod had yet to be officially christened with a “Go Live” date so I had the time, and having recently been binge watching CSI: New York, I also had the inclination. An inspection of the two systems, Prod and Dev, revealed the first surprise: although Prod was indeed a “bigger” system, with double the amount of RAM of Dev, the latter actually had twice as many processor cores. On neither system did I see much sign of resources being heavily taxed, while the ETL process was running. Without any real supporting evidence, I jumped to a conclusion that my years of performance tuning should have helped me avoid, and that was that the hardware differences explained the better performance on Dev. We spent time setting up a Test system, similarly scoped to Prod except with 4 times the cores, and ported everything across. The results of our careful benchmarks left us truly bemused; the ETL process on the new server was slower than on both other systems. We burned more time tweaking server configurations, monitoring IO and network latency, several times believing we’d uncovered the smoking gun, until the results of subsequent test runs pitched us back into confusion. Finally, I decided, enough was enough. Hadn’t I learned very early in my DBA career that almost all bottlenecks were caused by code and database design, not hardware? It was time to get back to basics. With over 100 SSIS packages and hundreds of queries, each handling specific tasks such as file loads, bulk inserts, transforms, logging, and so on, the task seemed formidable. And yet, after barely an hour spent with Profiler, Extended Events, and wait statistics DMVs, I had a lead in the shape of a query that joined three tables, containing millions of rows, returned 3279 results, but performed 239K logical reads. As soon as I looked at the execution plans for the query in Dev and Test I saw the culprit, an implicit conversion warning on a join predicate field that was numeric in one table and a varchar(50) in another! I turned this information over to the BI developers who quickly resolved the data type mismatches and found and fixed “several” others as well. After the schema changes the same query with the same databases ran in under 1 second on all systems and reduced the logical reads down to fewer than 300. The analysis also revealed that on Dev, the ETL task was pulling data across a LAN, whereas Prod and Test were connected across slower WAN, in large part explaining why the same process ran slower on the latter two systems. Loading the data locally on Prod delivered a further 20% gain in performance. As we progress through our DBA careers we learn valuable lessons. Sometimes, with a project deadline looming and pressure mounting, we choose to forget them. I was close to giving into the temptation to throw more hardware at the problem. I’m pleased at least that I resisted, though I still kick myself for not looking at the code on day one. It can seem a daunting prospect to return to the fundamentals of the code so close to roll out, but with the right tools, and surprisingly little time, you can collect the evidence that reveals the true problem. It is a lesson I trust I will remember for my next 20 years as a DBA, if I’m ever again tempted to bypass the evidence.

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  • A proposal for #DAX Code Formatting #ssas #powerpivot #tabular

    - by Marco Russo (SQLBI)
    I recently published a set of rules for DAX code formatting. The following is an example of what I obtain: CALCULATE (     SUMX (         Orders,         Orders[Amount]     ),     FILTER (         ALL ( Customers ),         CALCULATE (             COUNTROWS ( Sales ),             ALL ( Calendar[Date] )         ) > 42 + 8 – 25 * ( 3 - 1 )             + 2 – 1 + 2 – 1             + CALCULATE (                   2 + 2 – 2                   + 2 - 2               )             – CALCULATE ( 4 )     ) ) The goal is to improve code readability and I look forward to implement a code formatting feature in DAX Studio. The DAX Editor already supports the rules described in the article. I am also considering whether to add a rule specific for ADDCOLUMNS / SUMMARIZE because I would like to see the “pairs” of arguments to define a column in the same row or with a special indentation rule (DAX expression for a column is indented in the line following the column name). EVALUATE CALCULATETABLE (        CALCULATETABLE (         SUMMARIZE (             Audience,             'Date'[Year],             Individuals[Gender],             Individuals[AgeRange],             "Num of Rows", FORMAT (COUNTROWS (Audience), "#,#"),             "Weighted Mean Age",                 SUMX (Audience, Audience[Weight] * Audience[Age]) / SUM (Audience[Weight])         ),         SUMMARIZE (             BridgeIndividualsTargets,             Individuals[ID_Individual]         ),         Audience[Weight] > 0        ),        Targets[Target] = "Maschi",     'Date'[Year] = 2010,     'Date'[MonthName] = "January" ) I would like to get feedback for that – you can use comments here or comments in original article. Thanks!

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  • Where Have All the Ugly Forms Gone? Users and ADF Took Care Of It

    - by ultan o'broin
    Sometimes I hear that our application demos are a bit too "cutsey" and that we never talk about with any user roles that have lots of data entry as a requirement. Some (no names) consider those old clunker forms, with the myriad rows of fields, to be super-productive for data clerks. We do have such roles covered in Oracle Fusion Applications for sure. But consider what is really the issue here: productivity. Check out how the Oracle Fusion Financials Applications User Experience team went about designing for productivity when receiving and entering invoice data, for example. See how Fusion Financials caters so well for input and control of data? Central to all this is knowing the users and how they work: what tasks do they need to perform, and when. Read more about Fusion Financials productivity in the white paper, Get It Done Fast, Get It Done Right: The Oracle Fusion Financials User Experience. Now and then, I see forms that weren't designed for end user activity at all. Instead, they were designed by developers or by the IT department around the database schema. Forms with literally dozens of fields on the same page, sometimes. Forms that give the impression there was only task involved, when there may have been several. At times, completing one of these huge forms accurately became so tedious that, under pressure, it made more sense for the user to complete it quickly as possible and then let somebody else check it for accuracy and fill in the gaps from data emailed along in spreadsheet form. Data accuracy is critical in our business. Not good. Not efficient. Not productive. So here are a few basics on forms design for data entry-type user roles. A great place for developers to start exploring what is possible with forms layout is the Rich Client User Experience (RCUX) guidance on Form Layout, using ADF components. User-Centered Forms Design Considerations The starting point--something you must always keep in mind with your own design--is design for the end user. Find a representative end user, and keep that user engaged throughout the design, deployment, and test process. Consider these points in user testing those forms: Are there automated or technical solutions to entering the data that avoid manual input in the first place? For example, imports, uploads, OCR, whatever. Some day we will be able to tell Siri to do it, but leave that for now. Design your form to reflect the task involved (i.e., the business process) and not the database schema. On the form, group like fields together, logically. Eliminate duplicate data entry or prepopulate from previous data entry. Allow users to complete fields in the order they wish (i.e., no interdependency). Allow for tabbing between fields (keyboard is faster than mouse), so know how the browser supports this (see that RCUX guideline). Allow for final validation at the page level not at field-level entry. Way better for heads-down users. For example, ADF messages allow you to see a list of all validation errors on a page on a final submit or navigation action and to easily navigate to the point of error. Better still, be error tolerant. Allow users to enter data in formats they comfortable with. Bind any relevant user preference setting to the input format allowed (for example, the locale date format). Explore what data entry conversion can do for you automatically too (see the ADF converter demos, convenience patterns can also be written). Only ask for data input when it's needed. Get rid of, or hide optional fields. Cut down on the number of mandatory fields, and mark them clearly (use a *). Clearly label the fields in plain language. I am sure you may have a few more tips on forms design for data entry users. Remember the user before finding the comments.

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  • Good DBAs Do Baselines

    - by Louis Davidson
    One morning, you wake up and feel funny. You can’t quite put your finger on it, but something isn’t quite right. What now? Unless you happen to be a hypochondriac, you likely drag yourself out of bed, get on with the day and gather more “evidence”. You check your symptoms over the next few days; do you feel the same, better, worse? If better, then great, it was some temporal issue, perhaps caused by an allergic reaction to some suspiciously spicy chicken. If the same or worse then you go to the doctor for some health advice, but armed with some data to share, and having ruled out certain possible causes that are fixed with a bit of rest and perhaps an antacid. Whether you realize it or not, in comparing how you feel one day to the next, you have taken baseline measurements. In much the same way, a DBA uses baselines to gauge the gauge health of their database servers. Of course, while SQL Server is very willing to share data regarding its health and activities, it has almost no idea of the difference between good and bad. Over time, experienced DBAs develop “mental” baselines with which they can gauge the health of their servers almost as easily as their own body. They accumulate knowledge of the daily, natural state of each part of their database system, and so know instinctively when one of their databases “feels funny”. Equally, they know when an “issue” is just a passing tremor. They see their SQL Server with all of its four CPU cores running close 100% and don’t panic anymore. Why? It’s 5PM and every day the same thing occurs when the end-of-day reports, which are very CPU intensive, are running. Equally, they know when they need to respond in earnest when it is the first time they have heard about an issue, even if it has been happening every day. Nevertheless, no DBA can retain mental baselines for every characteristic of their systems, so we need to collect physical baselines too. In my experience, surprisingly few DBAs do this very well. Part of the problem is that SQL Server provides a lot of instrumentation. If you look, you will find an almost overwhelming amount of data regarding user activity on your SQL Server instances, and use and abuse of the available CPU, I/O and memory. It seems like a huge task even to work out which data you need to collect, let alone start collecting it on a regular basis, managing its storage over time, and performing detailed comparative analysis. However, without baselines, though, it is very difficult to pinpoint what ails a server, just by looking at a single snapshot of the data, or to spot retrospectively what caused the problem by examining aggregated data for the server, collected over many months. It isn’t as hard as you think to get started. You’ve probably already established some troubleshooting queries of the type SELECT Value FROM SomeSystemTableOrView. Capturing a set of baseline values for such a query can be as easy as changing it as follows: INSERT into BaseLine.SomeSystemTable (value, captureTime) SELECT Value, SYSDATETIME() FROM SomeSystemTableOrView; Of course, there are monitoring tools that will collect and manage this baseline data for you, automatically, and allow you to perform comparison of metrics over different periods. However, to get yourself started and to prove to yourself (or perhaps the person who writes the checks for tools) the value of baselines, stick something similar to the above query into an agent job, running every hour or so, and you are on your way with no excuses! Then, the next time you investigate a slow server, and see x open transactions, y users logged in, and z rows added per hour in the Orders table, compare to your baselines and see immediately what, if anything, has changed!

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  • SQL Server Optimizer Malfunction?

    - by Tony Davis
    There was a sharp intake of breath from the audience when Adam Machanic declared the SQL Server optimizer to be essentially "stuck in 1997". It was during his fascinating "Query Tuning Mastery: Manhandling Parallelism" session at the recent PASS SQL Summit. Paraphrasing somewhat, Adam (blog | @AdamMachanic) offered a convincing argument that the optimizer often delivers flawed plans based on assumptions that are no longer valid with today’s hardware. In 1997, when Microsoft engineers re-designed the database engine for SQL Server 7.0, SQL Server got its initial implementation of a cost-based optimizer. Up to SQL Server 2000, the developer often had to deploy a steady stream of hints in SQL statements to combat the occasionally wilful plan choices made by the optimizer. However, with each successive release, the optimizer has evolved and improved in its decision-making. It is still prone to the occasional stumble when we tackle difficult problems, join large numbers of tables, perform complex aggregations, and so on, but for most of us, most of the time, the optimizer purrs along efficiently in the background. Adam, however, challenged further any assumption that the current optimizer is competent at providing the most efficient plans for our more complex analytical queries, and in particular of offering up correctly parallelized plans. He painted a picture of a present where complex analytical queries have become ever more prevalent; where disk IO is ever faster so that reads from disk come into buffer cache faster than ever; where the improving RAM-to-data ratio means that we have a better chance of finding our data in cache. Most importantly, we have more CPUs at our disposal than ever before. To get these queries to perform, we not only need to have the right indexes, but also to be able to split the data up into subsets and spread its processing evenly across all these available CPUs. Improvements such as support for ColumnStore indexes are taking things in the right direction, but, unfortunately, deficiencies in the current Optimizer mean that SQL Server is yet to be able to exploit properly all those extra CPUs. Adam’s contention was that the current optimizer uses essentially the same costing model for many of its core operations as it did back in the days of SQL Server 7, based on assumptions that are no longer valid. One example he gave was a "slow disk" bias that may have been valid back in 1997 but certainly is not on modern disk systems. Essentially, the optimizer assesses the relative cost of serial versus parallel plans based on the assumption that there is no IO cost benefit from parallelization, only CPU. It assumes that a single request will saturate the IO channel, and so a query would not run any faster if we parallelized IO because the disk system simply wouldn’t be able to handle the extra pressure. As such, the optimizer often decides that a serial plan is lower cost, often in cases where a parallel plan would improve performance dramatically. It was challenging and thought provoking stuff, as were his techniques for driving parallelism through query logic based on subsets of rows that define the "grain" of the query. I highly recommend you catch the session if you missed it. I’m interested to hear though, when and how often people feel the force of the optimizer’s shortcomings. Barring mistakes, such as stale statistics, how often do you feel the Optimizer fails to find the plan you think it should, and what are the most common causes? Is it fighting to induce it toward parallelism? Combating unexpected plans, arising from table partitioning? Something altogether more prosaic? Cheers, Tony.

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  • BizTalk&ndash;Mapping repeating EDI segments using a Table Looping functoid

    - by Bill Osuch
    BizTalk’s HIPAA X12 schemas have several repeating date/time segments in them, where the XML winds up looking something like this: <DTM_StatementDate> <DTM01_DateTimeQualifier>232</DTM01_DateTimeQualifier> <DTM02_ClaimDate>20120301</DTM02_ClaimDate> </DTM_StatementDate> <DTM_StatementDate> <DTM01_DateTimeQualifier>233</DTM01_DateTimeQualifier> <DTM02_ClaimDate>20120302</DTM02_ClaimDate> </DTM_StatementDate> The corresponding EDI segments would look like this: DTM*232*20120301~ DTM*233*20120302~ The DateTimeQualifier element indicates whether it’s the start date or end date – 232 for start, 233 for end. So in this example (an X12 835) we’re saying the statement starts on 3/1/2012 and ends on 3/2/2012. When you’re mapping from some other data format, many times your start and end dates will be within the same node, like this: <StatementDates> <Begin>20120301</Begin> <End>20120302</End> </StatementDates> So how do you map from that and create two repeating segments in your destination map? You could connect both the <Begin> and <End> nodes to a looping functoid, and connect its output to <DTM_StatementDate>, then connect both <Begin> and <End> to <DTM_StatementDate> … this would give you two repeating segments, each with the correct date, but how to add the correct qualifier? The answer is the Table Looping Functoid! To test this, let’s create a simplified schema that just contains the date fields we’re mapping. First, create your input schema: And your output schema: Now create a map that uses these two schemas, and drag a Table Looping functoid onto it. The first input parameter configures the scope (or how many times the records will loop), so drag a link from the StatementDates node over to the functoid. Yes, StatementDates only appears once, so this would make it seem like it would only loop once, but you’ll see in just a minute. The second parameter in the functoid is the number of columns in the output table. We want to fill two fields, so just set this to 2. Now drag the Begin and End nodes over to the functoid. Finally, we want to add the constant values for DateTimeQualifier, so add a value of 232 and another of 233. When all your inputs are configured, it should look like this: Now we’ll configure the output table. Click on the Table Looping Grid, and configure it to look like this: Microsoft’s description of this functoid says “The Table Looping functoid repeats with the looping record it is connected to. Within each iteration, it loops once per row in the table looping grid, producing multiple output loops.” So here we will loop (# of <StatementDates> nodes) * (Rows in the table), or 2 times. Drag two Table Extractor functoids onto the map; these are what are going to pull the data we want out of the table. The first input to each of these will be the output of the TableLooping functoid, and the second input will be the row number to pull from. So the functoid connected to <DTM01_DateTimeQualifier> will look like this: Connect these two functoids to the two nodes we want to populate, and connect another output from the Table Looping functoid to the <DTM_StatementDate> record. You should have a map that looks something like this: Create some sample xml, use it as the TestMap Input Instance, and you should get a result like the XML at the top of this post. Technorati Tags: BizTalk, EDI, Mapping

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