Inserting Multiple Rows in SQL Server via a XML

15. February 2014 12:33 by Parakh in SQL Server, XML  //  Tags: , , ,   //   Comments
This post discusses how to post multiple rows worth of data to a SQL Server database using XML to minimize calls made to the database to store data.

Key take away:

My last two posts touched on the two methods available in SQL Server to flatten hierarchical XML data into flat relational form. In this post I will build upon those concepts and will cover how to leverage them to insert multiple rows worth of data into a SQL Server database in a single call.

Read on:

Hierarchical XML data can be flattened at SQL Server database level using one of the two ways:

1. OPENXML method

2. Nodes method

One of the reason why we would want to convert XML data into relational data at database level is to push in multiple rows worth of data to be inserted into a single or multiple tables in a single database call. Opening and closing a connection to a database for doing operation can be a costly affair for a website storing a sizeable amount of data at every call. The cost can be minimized by sending all the related data in a single call and parsing it out into distinct rowsets and storing them in the desired table(s). This scenario is especially true when you provide editing capabilities in a tabular or gridview kind of an environment and allow user to check in all the changes in one button click.

The technique of storing multiple rows with the help of XML works on the following strategy:

1. Convert the information into XML hierarchy.

2. Pass the XML to SQL Server.

3. Parse the hierarchy via one of the methods – OPENXML or nodes method and convert it into relational form.

4. Parse the relational form and store it via normal insert query.

To demonstrate I will be using a very simple data model consisting of three tables: Student, Course and an association table supporting many-to-many relationship between Student and Course, StudentCourse.

The Entity-Relationship diagram will clarify the relationship between the tables:

ERD diagram

 

 

 

 

 

 

 

According the ER diagram, a student can take many courses and a course can be taken by many students. The insertion of courses that a student is interested in the association table is an ideal application of this technique.

The following ASP.NET webform that is the web front end that we will use to form a complete example to demonstrate this approach:

image

 

 

 

 

 

 

 

 

 

 

 

 

The coding for the webpage is very simple. The pseudo-code is as follows:

1. Select a student from the drop down.

2. Select from the available courses that the student needs enrollment for.

3. Click on the submit button.

I am going to leave it up to the reader to understand the programming in the web application. It is straight forward and the domain model powering the application is a reflection of the data model depicted above.

The main work is being done at two places:

1. Web application’s repository method which does the work of making a hierarchical XML data from the objects.

2. The stored procedure that converts incoming XML data into relational data and stores it into table.

Consider the following repository method:

   1:  public int GetEnrolled(List<Course> courses, int studentID)
   2:          {
   3:              DataTable table = new DataTable("data");
   4:              table.Columns.Add("StudentID");
   5:              table.Columns.Add("CourseID");
   6:   
   7:              foreach (Course course in courses)
   8:              {
   9:                  table.Rows.Add(new object[] { studentID, course.CourseID});
  10:              }
  11:   
  12:              string data;
  13:              using (StringWriter sw = new StringWriter())
  14:              {
  15:                  table.WriteXml(sw);
  16:                  data = sw.ToString();
  17:              }
  18:   
  19:   
  20:              string sql = @"dbo.EnrollStudentInCourses";
  21:   
  22:              int result = 0;
  23:   
  24:              SqlParameter xml = new SqlParameter("XML", data);
  25:   
  26:              using (SqlConnection connection = new SqlConnection(connectionString))
  27:              {
  28:                  using (SqlCommand command = new SqlCommand(sql, connection))
  29:                  {
  30:                      command.CommandType = CommandType.StoredProcedure;
  31:                      command.Parameters.Add(xml);
  32:   
  33:                      connection.Open();
  34:                      result = command.ExecuteNonQuery();
  35:                      connection.Close();
  36:                  }
  37:              }
  38:   
  39:              return result;
  40:          }

 

The point of interest in the code mentioned above are the lines that push the object data into a datatable and the code that converts the datatable into an XML hierarchy. Please note that the hierarchy will include the name of the datatable that gets set in the .Net code. So please name it appropriately. The resulting XML hierarchy looks something as shown below:

   1:  <DocumentElement>
   2:      <data>
   3:          <StudentID>1</StudentID>
   4:          <CourseID>4</CourseID>
   5:      </data>
   6:      <data>
   7:          <StudentID>1</StudentID>
   8:          <CourseID>5</CourseID>
   9:      </data>
  10:      <data>
  11:          <StudentID>1</StudentID>
  12:          <CourseID>6</CourseID>
  13:      </data>
  14:  </DocumentElement>

It is this XML that gets passed to the SQL Server and is de-serialized into relational form using the nodes method. I have discussed the fundamentals of the nodes method in my last post. The de-serialization can also be carried out by using the OPENXML method.

The core of the dbo.EnrollStudentInCourses stored procedure, responsible for recording the course enrollment data for a student is made of the following code:

   1:  Insert into StudentCourse (StudentID, CourseID)
   2:  SELECT
   3:  data.value('(StudentID/text())[1]','int') as StudentID,
   4:  data.value('(CourseID/text())[1]','int') as CourseID
   5:  FROM @XML.nodes('/DocumentElement/data')
   6:  as StudentCourses(data)
 

NOTE: The SQL code is made keeping in mind the name of the datatable used to capture the data in the .Net code.

The sample code for this post consists of the web application and the powering database. Download it from:

Converting XML data into Relational Form using nodes method

2. November 2013 11:40 by Parakh in SQL Server, XML  //  Tags: , ,   //   Comments
This post describes how to convert XML data into relational form using the nodes method available in SQL Server.

Key take away:

In my last post I covered the topic of converting XML data into relational form using OPENXML function available in SQL Server. In this post I will be covering a second way of converting XML data into relational form using the nodes method. Nodes method, like OPENXML function, uses a valid XQuery expression to parse through XML hierarchy, but offers a bit more flexibility and in general is more readable. This post is a prelude to the forthcoming post on the topic of inserting multiple rows in SQL Server database table via XML.

Read on:

There are sometimes requirements that dictate XML data be sent to the database and de-serialized to be stored in relational form at the database itself. There are two methods available to achieve this in SQL Server – OPENXML function and nodes method for XML data type. I have described using an example on how to flatten XML data to relational using OPENXML function in my previous post. In this post I will describe doing same using nodes method available for XML data type in SQL Server.

Nodes method approach:

The nodes method is a rowset provider just like a table or a view which allows access to XML data in relational form. The nodes method is applicable on XML data type and takes a valid XQuery representing the portion of XML data which is desired to be flattened out into relational form. Unlike the OPENXML function, there’s no requirement in the nodes approach to prepare an in-memory representation of the XML data. Thus there are no system stored procedures that you have to run to create and wipe off the intermediate in-memory representation of data. This results in a clean, self-sufficient and a more readable query. Let’s take an example and see the nodes method in action.

Consider the following code:

DECLARE @XML xml = 
'<Students>
    <Student id="1">
        <FName>Parakh</FName>
        <LName>Singhal</LName>
        <Age>30</Age>
        <Courses>
            <Course id="1">Fundamentals of Databases</Course>
            <Course id="10">Fundamentals of Networking</Course>
            <Course id="15">Fundamentals of Security</Course>
        </Courses>
    </Student>
    <Student id="2">
        <FName>Glen</FName>
        <LName>Bennet</LName>
        <Age>31</Age>
        <Courses>
            <Course id="12">Fundamentals of Data Warehousing</Course>
            <Course id="15">Fundamentals of Security</Course>
        </Courses>
    </Student>    
</Students>';
 
SELECT
Student.value('@id','int') as StudentID,
Student.value('(FName/text())[1]','varchar(50)') as StudentFirstName,
Student.value('(LName/text())[1]','varchar(50)') as StudentLastName,
Student.value('(Age/text())[1]','int') as StudentAge,
Student.value('(Courses/Course/text())[1]','varchar(50)') as EnrolledCourse1,
Student.value('(Courses/Course/text())[2]','varchar(50)') as EnrolledCourse2,
Student.value('(Courses/Course/text())[3]','varchar(50)') as EnrolledCourse3
FROM @XML.nodes('/Students/Student')
as StudentTable(Student)

This gives us the following result:

SQl Result nodes method

Explanation of code:

The sample XML data is a collection of students under the appropriately named root node “Students”. Each “Student” node further consists of information about the student and the courses that he’s enrolled in. The sample XML is sufficiently complex to give us an opportunity to learn the following;

a) How to query data available in the form of attribute of an element like “id” of a student.

b) How to query various node elements like “FName”,” LName” and “Age”.

c) How to query a hierarchy available in the form of “Course” information.

Our code takes the XML type variable and uses the instance of nodes method available per the semantics of XML data type in SQL Server. We extract the hierarchy from the XML type variable in the FROM clause by providing the right XQuery path, and aliased the returned rowset as StudentTable with a single column Student. It is this Student that we have to use in conjunction with the value method to extract the data desired.

The syntax to extract attribute values requires using the “@” symbol suffixed with the name of the attribute as it appears in the XML hierarchy. The values of various elements in the hierarchy can be extracted by using their names, the form of data they need to be extracted as like text() and a valid data type available in SQL Server compatible to be used in the rowset form, like varchar, int, char etc. When there is multiple rows worth of data in the XML hierarchy, we have to use metadata property for elements in XML hierarchy to denote the occurrence that needs to be extracted.

For example,

Student.value('(FName/text())[1]','varchar(50)') as StudentFirstName

 

means that we want to extract the data in the “FName” element as varchar(50) data type and we want to extract data corresponding to EVERY first occurrence of the “FName” element in the XML hierarchy. So that means that if there is a second occurrence of the “FName” element in the XML hierarchy, our sql query is going to ignore it. The “Courses” portion of the sql query is a good example to drive home the point. Over there we have to mention explicitly about which occurrence of “Course” we want to extract the data of. Play with it and see how it will give you different results.

I feel that sql query formed using the nodes method is more readable, less scary than the query formed using the OPENXML function.

In my next post I will be covering the topic that my two posts on processing XML data to relational data leads to, i.e. inserting multiple rows worth of data into SQL Server in a single call, using the XML approach from a sample ASP.NET web application.

NOTE: There is a lot of debate going on internet as to which way of shredding XML data to relational form is more efficient – OPENXML function or the nodes method. I believe that this varies from case to case, and should be best judged after doing a thorough analysis with different sets of expected conditions.

References:

1. Nodes method at Technet

2. Flattening XML data in SQL Server

3. XML at W3c Schools

Converting XML data into Relational Form using OPENXML

16. October 2013 08:42 by Parakh in SQL Server, XML  //  Tags: , ,   //   Comments
This post describes how XML data can be parsed using the OPENXML function in SQL Server.

Key take away:

Sometimes there are requirements direct or tangential, which require us to de-serialize data from hierarchical XML format into relational form. There are two approaches to do that in SQL Server. One using the OPENXML function which relies on the native features available in SQL Server. The other approach uses the “nodes” method of the XQuery language (A query language used to search XML documents) which has been baked right into SQL Server’s T-SQL. In this post I will be covering the OPENXML approach. This post is a prelude to the forthcoming post on the topic of inserting multiple rows in SQL Server database table via XML.

Read on:

One of the realities of doing software development is handling various data formats. Most of the time, it can be cleanly done at the application level, but sometimes you may be required to handle that at the database level. One such requirement is operating on multiple rows worth of table data in a single call to the database. One of the approaches of doing so deals with supplying the data in XML form, and de-serializing it at the database level in relational form and then perform the desired operation on the data. This post deals with the preliminary step that is required before you do any of the CRUD operation on the data i.e. converting the XML data into relational form. In this post I will cover the OPENXML approach to flatten the XML data in relational rowset form.

OPENXML approach:

The OPENXML is a rowset provider just like a table or a view which allows access to XML data in relational form. OPENXML uses an in-memory representation of XML data to facilitate the relational form of data. The parsing of XML data and its push into system’s memory can achieved with the help of a system stored procedure sp_xml_preparedocument, which takes in the xml data in string format and returns a handle to the in-memory representation of the xml data. This handle, which is an integer, is then consumed by the OPENXML function and data can be queried from there onwards. One important point to note here is that since the XML data is parsed into memory, it becomes the responsibility of the developer to free up the memory after running the desired operation on the parsed XML data. This is achieved with the help of sp_xml_removedocument system stored procedure. Thus the pseudo-code for entire operation would look like:

1. Parse the xml document into memory by sp_xml_preparedocument.

2. Run the desired data operation using OPENXML, providing it the handle to the in-memory xml data returned by sp_xml_preparedocument.

3. Clean up the system memory by running sp_xml_removedocument, providing it the handle to the data that needs to be removed (provided by sp_xml_preparedocument earlier).

Consider the following code:

 

DECLARE @XML xml = 
'<Students>
    <Student id="1">
        <FName>Parakh</FName>
        <LName>Singhal</LName>
        <Age>30</Age>
        <Courses>
            <Course id="1">Fundamentals of Databases</Course>
            <Course id="10">Fundamentals of Networking</Course>
            <Course id="15">Fundamentals of Security</Course>
        </Courses>
    </Student>
    <Student id="2">
        <FName>Glen</FName>
        <LName>Bennet</LName>
        <Age>30</Age>
        <Courses>
            <Course id="12">Fundamentals of Data Warehousing</Course>
            <Course id="15">Fundamentals of Security</Course>
        </Courses>
    </Student>    
</Students>';
 
DECLARE @docpointer int;
 
EXEC sp_XML_preparedocument @docpointer OUTPUT, @XML;
 
SELECT
StudentID,
StudentFirstName,
StudentLastName,
StudentAge,
EnrolledCourse1,
EnrolledCourse2,
EnrolledCourse3
FROM OPENXML(@docpointer,'/Students/Student',2)
WITH
(StudentID int '@id', 
StudentFirstName varchar(50) 'FName', 
StudentLastName varchar(50) 'LName',
StudentAge int 'Age',
EnrolledCourse1 varchar(50) '(Courses/Course)[1]',
EnrolledCourse2 varchar(50) '(Courses/Course)[2]',
EnrolledCourse3 varchar(50) '(Courses/Course)[3]');
 
EXEC sp_xml_removedocument @docpointer;

This gives us the following result:

SQL result

 

 

 

Explanation of code:

The sample XML data is a collection of students under the appropriately named root node “Students”. Each “Student” node further consists of information about the student and the courses that he’s enrolled in. The sample XML is sufficiently complex to give us an opportunity to learn the following;

a) How to query data available in the form of attribute of an element like “id” of a student.

b) How to query various node elements like “FName”,” LName” and “Age”.

c) How to query a hierarchy available in the form of “Course” information.

The code first declares an int type variable. This will be used to store handle to point to the in-memory XML data parsed with the help of the system stored procedure sp_xml_preparedocument. The data is then parsed with sp_xml_preparedocument.

The OPENXML function within the Select query is where all the action happens. The OPENXML function takes three input parameters into account – the handle to the in-memory XML data representation, the XPath expression that emits the XML to be parsed into relational rowset form, and a bit flag used to represent the type of mapping desired – attribute-centric, element-centric or a hybrid of both. I am using the element-centric mapping. For more information on the syntax of OPENXML and the associated bit flags, please visit TechNet site.

The associated With clause of the OPENXML describes the schema declaration that needs to be applied to the xml data in order to give it a desired rowset shape. Alternatively, name of a table that already exists in the database and represents the desired rowset schema, could be provided. We can opt to get all the data back from the parsed XML, or be selective about it. In the provided example I am parsing everything, sans the “id” attribute of the “Course” elements.

The schema declaration takes in three parameters – Name of the column as desired, a valid SQL Server data type mapped to corresponding value of attribute or element being queried and a valid XPath expression describing how the XML nodes should be mapped to the corresponding column. If you look closely then you will find that there’s a number appearing in square brackets in the portion of schema declaration that deals with “Course” elements. That’s the meta-property describing the relative position of the XML node in the hierarchy and mapping it to the desired column.

E.g. “EnrolledCourse2 varchar(50) '(Courses/Course)[2]' “signifies that the second “Course” element in the Courses hierarchy should be mapped with the EnrolledCourse2 column.

Once we have done the schema declaration, we use the same column names in the Select clause as described in the schema declaration to query the XML data. Once you get the correct results, you can insert the data, update the existing data or delete the data from the existing table in your database.

In my next post I will be covering on parsing XML data with the help of nodes function of the XQuery language available natively in T-SQL.

NOTE: I have deliberately not gone into the explanation of syntax of OPENXML function, as that can be perused from the official resources given in the references section.

References:

1. OPENXML (Transact-SQL) at TechNet

2. OPENXML at PerfectXML

Inserting Multiple Rows in SQL Server via a Comma Separated Values List

29. September 2013 09:59 by Parakh in SQL Server, ASP.NET  //  Tags: , , , ,   //   Comments
There are three approaches to key in multiple rows into a single table in SQL Server database. One of them is comma separated list, discussed in this post.

 

Key takeaway:

Frequently there are scenarios here you might be required to key in multiple rows into a SQL Server database table. In order to do that with minimum number of calls and a low memory footprint, there are several approaches available. I know of three, of which I am presenting the comma separated values (CSV) list approach.

Read on:

A few days ago, I ran into a requirement that required me to insert multiple rows of data into a table in a SQL Server database. There are a couple of approaches to do this and I am planning to do a series on this. Some of the approaches to do this are the following:

1. Passing a comma separated value (CSV) list to the database and parsing it at the database level with the help of a user defined function to split the list into rows and inserting those rows.

2. Passing the data as XML hierarchy,

3. Using Table Valued Functions, a feature that SQL Server supports version 2008 onwards.

All the three approaches are valid approaches and usage depends upon the kind of constraints that you are operating with. I was dealing with a legacy codebase, that did not afforded me the luxury of table valued parameters, which is the most straight forward and efficient way of accomplishing this, and had to settle for the CSV list and eventually the XML way.

In this post I will be covering the CSV list method. The comma separated values list method requires the following main ingredient: a user defined function that can be used to split text on the defined delimiter. Since this post is all about demonstrating the comma separated values list approach, I will not delve into the internal mechanics of such function. I just grabbed the first function that I could get off of the internet, and made it work.

I got the split function from the following url: SQL Server Forums - Best split function courtesy of the member Corey alias Seventhnight.

The technique works on the following strategy:

1. Parse the information that needs to be stored in the database in the form of a CSV list.

2. Pass it to the database packed in an appropriate type of parameter.

3. De-serialize the information into a table variable with the help of the aforementioned splitter function.

4. Depending upon the total number of columns in the target table, run a combination of insert and update commands, fetching the information from the table variable. A combination is made this way in order to minimize the disk activity, and complete the operation in as short duration as possible.

To demonstrate I will be using a very simple data model consisting of three tables: Student, Course and an association table supporting many-to-many relationship between Student and Course, StudentCourse. The Entity-Relationship diagram will clarify the relationship between the tables:

clip_image002

 

 

 

 

 

 

 

According the ER diagram, a student can take many courses and a course can be taken by many students. The insertion of courses that a student is interested in the association table is an ideal application of this technique.

The following ASP.NET webform that is the web front end that we will use to form a complete example to demonstrate this approach:

clip_image004

 

 

 

 

 

 

 

 

 

 

 

The coding for the webpage is very simple. The pseudo-code is as follows:

1. Select a student from the drop down.

2. Select from the available courses that the student needs enrollment for.

3. Click on the submit button.

I am going to leave it up to the reader to understand the programming in the web application. It is straight forward and the domain model powering the application is a reflection of the data model depicted above.

All the magic happens in the stored procedure powering the enrollment of a student in one of the listed courses. The stored procedure is as follows:

   1:  CREATE PROCEDURE [dbo].[EnrollStudentInCourses]
   2:   
   3:  @StudentID int,
   4:   
   5:  @Courses nvarchar(max)
   6:   
   7:  AS
   8:   
   9:  BEGIN
  10:   
  11:  Declare @TempStudentCourseTable Table
  12:   
  13:  (
  14:   
  15:  StudentID int null,
  16:   
  17:  CourseID int null
  18:   
  19:  );
  20:   
  21:  Insert into @TempStudentCourseTable (CourseID)
  22:   
  23:  Select CONVERT(int,Data) from dbo.Split(@Courses,',');
  24:   
  25:  Update @TempStudentCourseTable Set StudentID = @StudentID;
  26:   
  27:  Insert into dbo.StudentCourse (StudentID,CourseID)
  28:   
  29:  Select StudentID,CourseID from @TempStudentCourseTable;
  30:   
  31:  END
  32:   
  33:  GO
  34:   

 

The pseudo-code for the stored procedure is as follows:

1. There are two parameters in the stored procedure – The student ID of the student, who needs to be enrolled, and the courses passed as an nvarchar(max) parameter representing a CSV list of the courses in which the enrollment needs to be done.

2. The procedure uses a table variable that mimics the table structure of the StudentCourse table, sans the primary key.

3. Insert command is carried out on the table variable, with the CSV list comprised of the courses passed to the splitter function. Since out splitter function returns a table, with two columns – ID (int type identity column), and Data (nvarchar type), we can right away leverage the Data field, and insert it into the table variable by carrying out required conversion on the fly. Here I am converting the Data to integer, since CourseID is of type int.

4. Once the insertion has been done, I update the StudentID field in the table variable with the passed parameter value.

5. Once this is complete, I ran the Insert…Select… command to key in data into the final StudentCourse table. Depending upon the settings in the database, this will be a minimally logged operation, thereby giving you speed benefits.

Note that this is an overly simple example of the stored procedure, not employing transaction, error handling etc. and is meant to convey the concept of usage of comma separated values list in inserting multiple rows.

Emerging pattern:

If you look at this and carry it forward to more complicated use cases, then you’ll see a pattern emerging out. The pattern is:

1. Model the table variable after the final table that is supposed to receive the data.

2. Insert the most variable information in the table variable first.

3. Follow up the insertion with updation of table variable with information that is not changing much, like the StudentID in this example. It remains constant for all the courses inserted into the table variable.

4. If you need selective action within the table variable, make use of an integer type identity column. In this example, we did not require that.

5. The complexity of the procedure will depend upon the total columns in the final table. The more the columns, the more the number of update commands. There will also be a loop that you will have to manage in order to update the table variable with the right row form the table emitted by the splitter function.

In the next post I will cover how to insert multiple rows in SQL Server database using XML.

The sample code for this post consists of the web application and the powering database. Download it from:

Microsoft Reporting Services – The quirky uncle in the family

This post explains the caution that one needs to excercise when overriding a strongly typed dataset with an in-code dataset to power a Microsoft Reporting Services report.

Key take away:

A Microsoft Reporting Services report needs a strongly typed dataset to work with, but it is generally overridden with an in-code dataset that is used to power the report. The report is sensitive to the name of the in-code dataset, and only works if provided with same name as what gets recorded in the XML innards of the report.

Read on:

Recently I got an opportunity to help a team shift their reports from Microsoft Reporting Services (MRS) to SQL Server reporting Services. Now I had left working with Microsoft Reporting Services back in 2010, when my team migrated all the reports to hosted SSRS environment, so I spent some time creating a simple yet effective proof of concept ASP.NET application working with a Microsoft Reporting Services report that I can show to the team in transition, on how import MRS reports in hosted SSRS environment. Nearly two-third of my time got spent in dealing with a quirk in Microsoft Reporting Services, which is providing the correct name of the dataset in the code, as the report wants it. I remembered this quirk from my days of working with Microsoft Reporting Services, but had forgotten the specifics of remedying the problem.

Microsoft Reporting Services is a port of SSRS that produces report(s) you can store in an ASP.NET application, along with the app contents and use the computing resources of the web application server to process data and serve the rendered view to the client. SSRS reports are bit more capable, easier to work with and can be offloaded to a dedicated report server, and thus computing resources (compute cycles, memory, bandwidth etc.) be saved on your primary web application server. Microsoft Reporting Services reports are a good choice when your reporting needs are simple, report generation is less frequent, and when on a shoe string budget. Otherwise, try to always opt for hosted SSRS environment.

clip_image001

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1. Setup in Microsoft Reporting Services compared with hosted SQL Server Reporting Services (SSRS)

Microsoft Reporting Services requires a strongly typed dataset to work with, and process data from it. For SSRS the requirements are the same, but the process of making and dealing with a strongly typed dataset is easy and somewhat hidden. Both the types of reports use Report Definition Language (RDL), a format used to convey the report contents and related artifacts. RDL in turn is based on XML, which means that RDL is case sensitive and any change in the schema can potentially render your report unusable. SSRS reports inherit the extension of “.rdl” while Microsoft Reporting Services reports end with “.rdlc” extension, with “c” in “.rdlc” denoting client, i.e. processing at application server.

Now that we have understood a little background about the Microsoft Reporting Services, let’s understand the quirk.

Almost always, when developers deal with Microsoft Reporting Services reports, they make a report with a very simple strongly typed dataset; connect artifacts on the report with this simple dataset (tablix, matrix, charts etc.), but then override this dataset in their application code, containing data table(s) filled with data from the actual query that essentially produces the same columns, but different data qualitatively. I usually do this because strongly typed datasets cannot be de-bugged, and they are generally more time consuming to deal with than actual verbose code. Once the functionality to override the dataset is in place the strongly typed dataset can be removed entirely. But till the overriding facility is not in place, you have to retain the strongly typed dataset in place, otherwise the report won’t build.

Here I present a simple example consisting of three tables in a data model. The tables are self-explanatory in nature. I have filled the tables up with some junk data. I will use these to make a report in an ASP.NET Webforms website, and will show where one needs to be careful in producing code that over-rides the strongly typed dataset powering the report.

clip_image002

 

 

 

 

 

 

 

 

 

 

 

Figure 2 Data model

Use case: I might bind a tablix on an MRS report with a simple query of “Select FirstName, MiddleName, LastName, DateOfBirth from Person”. While the actual query that I want to run is “Select FirstName, MiddleName, LastName, DateOfBirth fromPerson inner join Address on Person.PersonID = Address.PersonID where Address.State = @State” to get me details of people living in a certain state. So the columns that need to go on report are the same, but the data that will now appear is different qualitatively.

clip_image004

Figure 3 Dataset name appears as “DataSet1” in MRS report powering my tablix.

The moment you insert a tablix, MRS is going to prompt to create a data source containing a dataset powering the tablix. Once you finish the operation, you will find a strongly typed dataset in the App_Code folder of your ASP.NET web application.

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Figure 4 Dataset name as it appears in a strongly typed dataset.

You can double click the typed dataset and get the name of the strongly typed dataset by clicking in the blue section and bringing up the properties. The name came “DatabaseDataSet” came up by default. You can change that, but what matters is what is getting registered in the report.

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Figure 5 The name of the dataset as it appears in XML that makes up the report is of most importance.

Now here’s the code that you have to produce very carefully.

Make sure that when you are passing the report data source object to the report, it bears the same name as that of the dataset bound to the report, and more appropriately as found in the XML of the report. It doesn’t matter what is the name of the strongly bound dataset.

To see the name as it appears in the report’s innards, open with the inbuilt XML editor or just open it in Notepad and look for the entry with the name.

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Figure 6 The name of the dataset that you provide in a report data source should be the same as in report's innards.

This is quirk is only applicable on the name of the dataset that you need to provide. The name of the data source can be anything, and so is the name of the data table that carries the actual data in the dataset.

The sample code consists of two ASP.NET websites. One consists of a strongly typed dataset, while the other one does not consists of it. Both the websites have the same report being powered by an in-code dataset. The code was made in Visual Studio 2012 and targets .NET Framework 4.5. The code can be downloaded from:

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