Andy Leonard : SSIS Design Pattern. Let's take a look at how you can accomplish this in SSIS using the Lookup Transformation (for the join functionality) combined with the Conditional Split (for the WHERE clause conditions) transformations. Before we begin, let's reset our database tables to their original state using the following query: USE SSISIncremental. How to insert new and update existing records using SSIS. Load. Name the project SSISIncremental. Load: Once the project loads, open Solution Explorer and rename Package. SSISIncremental. Load. When prompted to rename the package object, click the Yes button. From the toolbox, drag a Data Flow onto the Control Flow canvas: Double- click the Data Flow task to edit it. From the toolbox, drag and drop an OLE DB Source onto the Data Flow canvas: Double- click the OLE DB Source connection adapter to edit it: Click the New button beside the OLE DB Connection Manager dropdown: Click the New button here to create a new Data Connection: Enter or select your server name. Connect to the SSISIncremental. In SSIS there are two tasks than can be used to execute SQL statements: Execute T-SQL Statement and Execute SQL. What is the difference between the two? Vb.NET ExecuteReader and ExecuteNonQuery ExecuteReader : ExecuteReader used for getting the query results as a DataReader object. It is readonly forward only. Update: For more up-to-date material on this topic, please see the Stairway to Incremental Loads at SQL Server Central for more information! Inside of a Script Task in SSIS, I need to make a call to an SQL database. I have a connection string that was created when I added the database to the data sources. Anoop Kumar shares his top 10 transformations to manage and change data in SSIS. Load. Click the OK button to return to the Connection Manager configuration dialog. Click the OK button to accept your newly created Data Connection as the Connection Manager you wish to define. Drag and drop a Lookup Transformation from the toolbox onto the Data Flow canvas. Connect the OLE DB connection adapter to the Lookup transformation by clicking on the OLE DB Source and dragging the green arrow over the Lookup and dropping it. Right- click the Lookup transformation and click Edit (or double- click the Lookup transformation) to edit: When the editor opens, click the New button beside the OLE DB Connection Manager dropdown (as you did earlier for the OLE DB Source Adapter). Define a new Data Connection - this time to the SSISIncremental. Load. After setting up the new Data Connection and Connection Manager, configure the Lookup transformation to connect to . On the left side are the columns currently in the SSIS data flow pipeline (from SSISIncremental. Load. On the right side are columns available from the Lookup destination you just configured (from SSISIncremental. Load. Follow the following steps: 1. We'll need all the rows returned from the destination table, so check all the checkboxes beside the rows in the destination. We need these rows for our WHERE clauses and for our JOIN ON clauses. We do not want to map all the rows between the source and destination - we only want to map the columns named Col. ID between the database tables. The Mappings drawn between the Available Input Columns and Available Lookup Columns define the JOIN ON clause. Multi- select the Mappings between Col. A, Col. B, and Col. C by clicking on them while holding the Ctrl key. Right- click any of them and click . Add the text . These rows are being appended to the data flow pipeline. This is so we can distinguish between Source and Destination rows farther down the pipeline: Next we need to modify our Lookup transformation behavior. By default, the Lookup operates as an INNER JOIN - but we need a LEFT (OUTER) JOIN. ![]() This tells the Lookup transformation . From the toolbox, drag and drop a Conditional Split Transformation onto the Data Flow canvas. Connect the Lookup to the Conditional Split as shown. Right- click the Conditional Split and click Edit to open the Conditional Split Editor: Expand the NULL Functions folder in the upper right of the Conditional Split Transformation Editor. Expand the Columns folder in the upper left side of the Conditional Split Transformation Editor. Click in the . From the NULL Functions folder, drag and drop the . This defines the WHERE clause for new rows - setting it to . Add the expression . This defines our WHERE clause for detecting changed rows - setting it to . Click on the Conditional Split and connect it to the OLE DB Destination. A dialog will display prompting you to select a Conditional Split Output (those outputs you defined in the last step). Select the New Rows output: Next connect the OLE DB Command transformation to the Conditional Split's . Make sure the Col. ID, Col. A, Col. B, and Col. C source columns are mapped to their matching destination columns (aren't you glad we prepended . Double- click the OLE DB Command to open the . Set the Connection Manager column to your SSISIncremental. Load. Click the elipsis (button with . Enter the following parameterized T- SQL statement into the String Value textbox: UPDATE dbo. Dest. SETCol. A = ?,Col. B = ?,Col. C = ? WHERE Col. ID = ? Map them as shown below - effectively altering the UPDATE statement for each row to read: UPDATE SSISIncremental. Load. For performance with large amounts of data, you will want to employ set- based updates instead. Click the OK button when mapping is completed. Your Data Flow canvas should look like that pictured below: If you execute the package with debugging (press F5), the package should succeed and appear as shown here: Note one row takes the . Although not visible, our third source row doesn't change, and would be sent to the . Any row that doesn't meet any of the predefined conditions in the Conditional Split is sent to the default output. That's all! Congratulations - you've built an incremental database load! Updating Existing Data with SSISI see a lot of questions on the forums about updating existing data in SSIS.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
October 2017
Categories |