A source in the SSIS Data Flow is where you specify the location of your source data. Most sources will point to a Connection Manager in SSIS. By pointing to a Connection Manager, you can reuse connections throughout your package, because you need only change the connection in one place.
SOURCE ASSISTANT AND DESTINATION ASSISTANT
The Source Assistant and Destination Assistant are two components designed to remove the complexity of configuring a source or a destination in the Data Flow. The components determine what drivers you have installed and show you only the applicable drivers. It also simplifies the selection of a valid connection manager based on the database platform you select that you wish to connect to.
In the Source Assistant or Destination Assistant (the Source Assistant is shown in the below diagram), only the data providers that you have installed are actually shown. Once you select how you want to connect, you’ll see a list of Connection Managers on the right that you can use to connect to your selected source. You can also create a new Connection Manager from the same area on the right. If you uncheck the “Show only installed source types” option, you’ll see other providers like DB2 or Oracle for which you may not have the right software installed.
The OLE DB Source is the most common type of source, and it can point to any OLE DB–compliant Data Sources such as SQL Server, Oracle, or DB2. To configure the OLE DB Source, double-click the source once you have added it to the design pane in the Data Flow tab. In the Connection Manager page of the OLE DB Source Editor (see below diagram), select the Connection Manager of your OLE DB Source from the OLE DB Connection Manager dropdown box. You can also add a new Connection Manager in the editor by clicking the New button.
The “Data access mode” option specifies how you wish to retrieve the data. Your options here are Table/View or SQL Command, or you can pull either from a package variable. Once you select the data access mode, you need the table or view, or you can type a query. For multiple reasons that will be explained momentarily, it is a best practice to retrieve the data from a query. This query can also be a stored procedure. Additionally, you can pass parameters into the query by substituting a question mark (?) for where the parameter should be and then clicking the Parameters button. You’ll learn more about parameterization of your queries in Chapter 5.
As with most sources, you can go to the Columns page to set columns that you wish to output to the Data Flow, as shown in the below diagram. Simply check the columns you wish to output, and you can then assign the name you want to send down the Data Flow in the Output column. Select only the columns that you want to use, because the smaller the data set, the better the performance you will get.
From a performance perspective, this is a case where it’s better to have typed the query in the Connection Manager page rather than to have selected a table. Selecting a table to pull data from essentially selects all columns and all rows from the target table, transporting all that data across the network. Then, going to the Columns page and unchecking the unnecessary columns applies a client-side filter on the data, which is not nearly as efficient as selecting only the necessary columns in the SQL query. This is also gentler on the amount of buffers you fill as well.
Optionally, you can go to the Error Output page (shown in below diagram) and specify how you wish to handle rows that have errors. For example, you may wish to output any rows that have a data type conversion issue to a different path in the Data Flow. On each column, you can specify that if an error occurs, you wish the row to be ignored, be redirected, or fail. If you choose to ignore failures, the column for that row will be set to NULL. If you redirect the row, the row will be sent down the red path in the Data Flow coming out of the OLE DB Source.
The Truncation column specifies what to do if data truncation occurs. A truncation error would happen, for example, if you try to place 200 characters of data into a column in the Data Flow that supports only 100. You have the same options available to you for Truncation as you do for the Error option. By default, if an error occurs with data types or truncation, an error will occur, causing the entire Data Flow to fail.
The Excel Source is a source component that points to an Excel spreadsheet, just like it sounds. Once you point to an Excel Connection Manager, you can select the sheet from the “Name of the Excel sheet” dropdown box, or you can run a query by changing the Data Access Mode. This source treats Excel just like a database, where an Excel sheet is the table and the workbook is the database. If you do not see a list of sheets in the dropdown box, you may have a 64-bit machine that needs the ACE driver installed or you need to run the package in 32-bit mode. How to do this is documented in the next section in this chapter.
SSIS supports Excel data types, but it may not support them the way you wish by default. For example, the default format in Excel is General. If you right-click a column and select Format Cells, you’ll find that most of the columns in your Excel spreadsheet have probably been set to General. SSIS translates this general format as a Unicode string data type. In SQL Server, Unicode translates into nvarchar, which is probably not what you want. If you have a Unicode data type in SSIS and you try to insert it into a varchar column, it will potentially fail. The solution is to place a Data Conversion Transformation between the source and the destination in order to change the Excel data types. You can read more about Data Conversion Transformations later in this chapter.
If you are connecting to an Excel 2007 spreadsheet or later, ensure that you select the proper Excel version when creating the Excel Connection Manager. You will not be able to connect to an Excel 2007, Excel 2010, or Excel 2013 spreadsheet otherwise. Additionally, the default Excel driver is a 32-bit driver only, and your packages have to run in 32-bit mode when using Excel connectivity. In the designer, you would receive the following error message if you do not have the correct driver installed:
The ‘Microsoft.ACE.OLEDB.12.0’ provider is not registered on the local machine.
To fix this, simply locate this driver on the Microsoft site and you’ll be able to run packages with an Excel source in 64-bit.
The Flat File Source provides a data source for connections such as text files or data that are delimited. Flat File Sources are typically comma- or tabdelimited files, or they could be fixed-width or ragged-right. A fixed-width file is typically received from the mainframe or government entities and has fixed start and stop points for each column. This method enables a fast load, but it takes longer at design time for the developer to map each column. You specify a Flat File Source the same way you specify an OLE DB Source. Once you add it to your Data Flow pane, you point it to a Connection Manager connection that is a flat file or a multi-flat file. Next, from the Columns tab, you specify which columns you want to be presented to the Data Flow. All the specifications for the flat file, such as delimiter type, were previously set in the Flat File Connection Manager.
In this example, you’ll create a Connection Manager that points to a file called FactSales.csv, which you can download from this book’s website at WWW.WROX.COM/GO/PROSSIS2014. The file has a date column, a few string columns, integer columns, and a currency column. Because of the variety of data types, it includes, this example presents an interesting case study for learning how to configure a Flat File Connection Manager.
First, right-click in the Connection Manager area of the Package Designer and select New Flat File Connection Manager. This will open the Flat File Connection Manager Editor, as shown in Figure 4-5. Name the Connection Manager Fact Sales and point it to wherever you placed the FactSales.csv file. Check the “Column names in the first data row” option, which specifies that the first row of the file contains a header row with the column names.
Another important option is the “Text qualifier” option. Although there isn’t one for this file, sometimes your comma-delimited files may require that you have a text qualifier. A text qualifier places a character around each column of data to show that any comma delimiter inside that symbol should be ignored. For example, if you had the most common text qualifier of double-quotes around your data, a row may look like the following, whereby there are only three columns even though the commas may indicate five:
“Knight,Brian”, 123, “Jacksonville, FL”
In the Columns page of the Connection Manager, you can specify what will delimit each column in the flat file if you chose a delimited file. The row delimiter specifies what will indicate a new row. The default option is a carriage return followed by a line feed. The Connection Manager’s file is automatically scanned to determine the column delimiter and, as shown in Figure 4-6, use a tab delimiter for the example file.
NOTE Often, once you make a major change to your header delimiter or your text qualifier, you’ll have to click the Reset Columns button. Doing so requeries the file in order to obtain the new column names. If you click this option, though, all your metadata in the Advanced page will be recreated as well, and you may lose a sizable amount of work.
The Advanced page of the Connection Manager is the most important feature in the Connection Manager. In this tab, you specify the data type for each column in the flat file and the name of the column, as shown in Figure 4-7. This column name and data type will be later sent to the Data Flow. If you need to change the data types or names, you can always come back to the Connection Manager, but be aware that you need to open the Flat File Source again to refresh the metadata.
NOTE Making a change to the Connection Manager’s data types or columns requires that you refresh any Data Flow Task using that Connection Manager. To do so, open the Flat File Source Editor, which will prompt you to refresh the metadata of the Data Flow. Answer yes, and the metadata will be corrected throughout the Data Flow.
If you don’t want to specify the data type for each individual column, you can click the Suggest Types button on this page to have SSIS scan the first 100 records (by default) in the file to guess the appropriate data types. Generally speaking, it does a bad job at guessing, but it’s a great place to start if you have a lot of columns.
If you prefer to do this manually, select each column and then specify its data type. You can also hold down the Ctrl key or Shift key and select multiple columns at once and change the data types or column length for multiple columns at the same time.
A Flat File Connection Manager initially treats each column as a 50-character string by default. Leaving this default behaviour harms performance when you have a true integer column that you’re trying to insert into SQL Server, or if your column contains more data than 50 characters of data. The settings you make in the Advanced page of the Connection Manager are the most important work you can do to ensure that all the data types for the columns are properly defined. You should also keep the data types as small as possible. For example, if you have a zipcode column that’s only 9 digits in length, define it as a 9-character string. This will save an additional 41 bytes in memory multiplied by however many rows you have.
A frustrating point with SSIS sometimes is how it deals with SQL Server data types. For example, varchar maps in SSIS to a string column. It was designed this way to translate well into the .NET development world and to provide an agnostic product. The following table contains some of the common SQL Server data types and what they are mapped into a Flat File Connection Manager.
By default, SSIS issues a contract between the Flat File Source and a Data Flow. It states that the source component must validate any numeric or date column. For example, if you have a flat file in which a given column is set to a four-byte integer, every row must first go through a short validation routine to ensure that it is truly an integer and that no character data has passed through. On date columns, a quick check is done to ensure that every date is indeed a valid in-range date.
This validation is fast but it does require approximately 20 to 30 percent more time to validate that contract. To set the FastParse property, go into the Data Flow Task for which you’re using a Flat File Source. Right-click the Flat File Source and select Show Advanced Editor. From there, select the Input and Output Properties tab, and choose any number or date column under Flat File Output ⇒ Output Columns tree. In the right pane, change the FastParse property to True, as shown in the below diagram.
If you know that you want to process a series of flat files in a Data Flow, or you want to refer to many files in the Control Flow, you can optionally use the MultiFlatFile or “Multiple Flat File Connection Manager.” The Multiple Flat File Connection Manager refers to a list of files for copying or moving, or it may hold a series of SQL scripts to execute, similar to the File Connection Manager. The Multiple Flat File Connection Manager gives you the same view as a Flat File Connection Manager, but it enables you to point to multiple files. In either case, you can point to a list of files by placing a vertical bar (|) between each filename:
In the Data Flow, the Multiple Flat File Connection Manager reacts by combining the total number of records from all the files that you have pointed to, appearing like a single merged file. Using this option will initiate the Data Flow process only once for the files whereas the Foreach Loop container will initiate the process once per file being processed. In either case, the metadata from the file must match in order to use them in the Data Flow. Most developers lean toward using Foreach Loop Containers because it’s easier to make them dynamic. With these Multiple File or Multiple Flat File Connection Managers, you have to parse your file list and add the vertical bar between them. If you use Foreach Loop Containers, that is taken care of for you.
The Raw File Source is a specialized type of file that is optimized for reading data quickly from SSIS. A Raw File Source is created by a Raw File Destination (discussed later in this chapter). You can’t add columns to the Raw File Source, but you can remove unused columns from the source in much the same way you do in the other sources. Because the Raw File Source requires little translation, it can load data much faster than the Flat File Source, but the price of this speed is little flexibility. Typically, you see raw files used to capture data at checkpoints to be used later in case of a package failure.
These sources are typically used for cross-package or cross-Data Flow communication. For example, if you have a Data Flow that takes four hours to run, you might wish to stage the data to a raw file halfway through the processing in case a problem occurs. Then, the second Data Flow Task would continue the remaining two hours of processing.
The XML source is a powerful SSIS source that can use a local or remote (via HTTP or UNC) XML file as the source. This source component is a bit different from the OLE DB Source in its configuration. First, you point to the XML file locally on your machine or at a UNC path. You can also point to a remote HTTP address for an XML file. This is useful for interaction with a vendor. This source is also very useful when used in conjunction with the Web Service Task or the XML Task. Once you point the data item to an XML file, you must generate an XSD (XML Schema Definition) file by clicking the Generate XSD button or point to an existing XSD file. The schema definition can also be an in-line XML file, so you don’t necessarily need an XSD file. Each of these cases may vary based on the XML that you’re trying to connect. The rest of the source resembles other sources; for example, you can filter the columns you don’t want to see down the chain.
The ADO.NET Source enables you to make a .NET provider a source and make it available for consumption inside the package. The source uses an ADO.NET Connection Manager to connect to the provider. The Data Flow is based on OLE DB, so for best performance, using the OLE DB Source is preferred. However, some providers might require that you use the ADO.NET source. Its interface is identical in appearance to the OLE DB Source, but it does require an ADO.NET Connection Manager.
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Yamuna Karumuri is a content writer at Mindmajix.com. Her passion lies in writing articles on IT platforms including Machine learning, PowerShell, DevOps, Data Science, Artificial Intelligence, Selenium, MSBI, and so on. You can connect with her via LinkedIn.
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