SQL Server MVP Deep Dives- P20

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SQL Server MVP Deep Dives- P20

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SQL Server MVP Deep Dives- P20: Each year Microsoft invites all the MVPs from every technology and country to Redmond for an MVP Summit—all top secret—“don’t tweet what you see!” During the MVP Summit, each product team holds a series of presentations where they explain their technologies, share their vision, and listen to some honest feedback.

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  1. 714 CHAPTER 56 Incorporating data profiling in the ETL process inside the package. Typically, you will store the XML in a file if you are profiling data to be reviewed by a person at a later time, and plan on using the Data Profile Viewer application to review it. Storing the XML output in a variable is most often done when you want to use the profile information later in the same package, perhaps to make an automated decision about data quality. The XML output includes both the profile requests (the input to the task) and the output from each profile requested. The format of the output varies depending on which profile generated it, so you will see different elements in the XML for a Column Null Ratio profile than you will for a Column Length Distribution profile. The XML contains a lot of information, and it can be difficult to sort through to find the infor- mation you are looking for. Fortunately, there is an easier user interface to use. The Data Profile Viewer, shown in figure 2, provides a graphical interface to the data profile information. You can open XML files generated by the Data Profiling task in it and find specific information much more easily. In addition, the viewer repre- sents some of the profile information graphically, which is useful when you are look- ing at large quantities of data. For example, the Column Length Distribution profile displays the count associated with specific lengths as a stacked bar chart, which means you can easily locate the most frequently used lengths. Figure 2 Data Profile Viewer Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  2. Introduction to the Data Profiling task 715 The Data Profile Viewer lets you sort most columns in the tables that it displays, which can aid you in exploring the data. It also allows you to drill down into the detail data in the source system. This is particularly useful when you have located some bad data in the profile, because you can see the source rows that contain the data. This can be valuable if, for example, the profile shows that several customer names are unusually long. You can drill into the detail data to see all the data associated with these outlier rows. This feature does require a live connection to the source database, though, because the source data is not directly included in the data profile output. One thing to be aware of with the Data Profile Viewer: not all values it shows are directly included in the XML. It does some additional work on the data profiles before presenting them to you. For example, in many cases it calculates the percentage of rows that a specific value in the profile applies to. The raw XML for the data profile only stores the row counts, not the percentages. This means that if you want to use the XML directly, perhaps to display the information on a web page, you may need to cal- culate some values manually. This is usually a straightforward task. Constraints of the Data Profiling task As useful as the Data Profiling task is, there are still some constraints that you need to keep in mind when using it. The first one most people encounter is in the types of data sources it will work with. The Data Profiling task requires that the data to be pro- filed be in SQL Server 2000 or later. This means you can’t use it to directly profile data in Oracle tables, Access databases, Excel spreadsheets, or flat files. You can work around this by importing the data you need into SQL Server prior to profiling it. In fact, there are other reasons why you may want the data in SQL Server in advance, which will be touched on in this section. The Data Profiling task also requires that you use an ADO.NET connection man- ager. Typically, in SSIS, OLE DB connection managers are used, as they tend to per- form better. This may mean creating two connection managers to the same database, if you need to both profile data and import it in the same package. Using the Data Profile Viewer does require a SQL Server installation, because the viewer is not packaged or licensed as a redistributable component. It is possible to transform the XML output into a more user-friendly format by using XSL Transforma- tions (XSLT) to translate it into HTML, or to write your own viewer for the information. The task’s performance can vary greatly, depending both on the volume of data you are profiling and on the types of profiles you have requested. Some profiles, such as the Column Pattern profile, are resource intensive and can take quite a while on a large table. One way to address this is to work with a subset of the data, rather than the entire table. It’s important to get a representative sample of the data for these pur- poses, so that the data profile results aren’t skewed. This is another reason that having the data in SQL Server can be valuable. You can copy a subset of the data to another table for profiling, using a SELECT that returns a random sampling of rows (as dis- cussed in “Selecting Rows Randomly from a Large Table” from MSDN: http:/ / msdn.microsoft.com/en-us/library/cc441928.aspx). If the data is coming from an external source, such as a flat file, you can use the Row Sampling or Percentage Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  3. 716 CHAPTER 56 Incorporating data profiling in the ETL process Sampling components in an SSIS data flow to create a representative sample of the data to profile. Note that when sampling data, care must be taken to ensure the data is truly representative, or the results can be misleading. Generally it’s better to profile the entire data set. Making the Data Profiling task dynamic Why would you want to make the Data Profiling task dynamic? Well, as an example, think about profiling a new database. You could create a new SSIS package, add a Data Profiling task, and use the Quick Profile option to create profile requests for all the tables in the database. You’d then have to repeat these steps for the next new database that you want to profile. Or what if you don’t want to profile all the tables, but only a subset of them? To do this through the task’s editor, you would need to add each table individually. Wouldn’t it be easier to be able to dynamically update the task to profile different tables in your database? Most tasks in SSIS can be made dynamic by using configurations and expressions. Configurations are used for settings that you wish to update each time a package is loaded, and expressions are used for settings that you want to update during the pack- age execution. Both expressions and configurations operate on the properties of tasks in the package, but depending on what aspect of the Data Profiling task you want to change, it may require special handling to behave in a dynamic manner. Changing the database Because the Data Profiling task uses connection managers to control the connection to the database, it is relatively easy to change the database it points to. You update the connection manager, using one of the standard approaches in SSIS, such as an expres- sion that sets the ConnectionString property, or a configuration that sets the same property. You can also accomplish this by overriding the connection manager’s setting at runtime using the /Connection switch of DTEXEC. Bear in mind that although you can switch databases this way, the task will only work if it is pointing to a SQL Server database. Also, connection managers only control the database that you are connecting to, and not the specific tables. The profile requests in the task will still be referencing the original tables, so if the new database does not contain tables with the same names, the task will fail. What is needed is a way to change the profile requests to reference new tables. Altering the profile requests As noted earlier, you can configure the Data Profiling task through the Data Profiling Task Editor, which configures and stores the profile requests in the task’s Profile- Requests property. But this property is a collection object, and collection objects can’t be set through expressions or configurations, so, at first glance, it appears that you can’t update the profile requests. Fortunately, there is an additional property that can be used for this on the Data Pro- filing task. This is the ProfileInputXml property, which stores the XML representation Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  4. Making the Data Profiling task dynamic 717 of the profile requests. The ProfileInputXml property is not visible in the Properties window in BIDS, but you can see it in the Property Expressions Editor dialog box, or in the Package Configuration Wizard’s property browser. You can set an XML string into this property using either an expression or a configuration. For it to work properly, the XML must conform to the DataProfile.xsd schema mentioned earlier. Setting the ProfileInputXml property So how can you go about altering the ProfileInputXml property to profile a different table? One way that works well is to create a string variable in the SSIS package to hold the table name (named TableName) and a second variable to hold the schema name (named SchemaName). Create a third variable that will hold the XML for the profile requests (named ProfileXML), and set the EvaluateAsVariable property of the ProfileXML variable to True. In the Expression property, you’ll need to enter the XML string for the profile, and concatenate in the table and schema variables. To get the XML to use as a starting point, you can configure and run the Data Pro- file task with its output directed to a file. You’ll then need to remove the output infor- mation from the file, which can be done by removing all of the elements between the and tags, so that the XML looks similar to listing 1. You may have more or less XML, depending on how many profiles you configured the task for initially. Listing 1 Data profile XML prior to making it dynamic Exact 0 {8D7CF241-6773-464A-87C8-60E95F386FB2} {8D7CF241-6773-464A-87C8-60E95F386FB2} No profile output should be included Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  5. 718 CHAPTER 56 Incorporating data profiling in the ETL process Once you have the XML, you need to change a few things to use it in an expression. First, the entire string needs to be put inside double quotes ("). Second, any existing double quotes need to be escaped, using a backslash ( \ ). For example, the ID attri- bute ID="StatisticsReq" needs to be formatted as ID=\"StatisticsReq\". Finally, the profile requests need to be altered to include the table name variable created pre- viously. These modifications are shown in listing 2. Listing 2 Data profiling XML after converting to an expression " Exact 0 {8D7CF241-6773-464A-87C8-60E95F386FB2} {8D7CF241-6773-464A-87C8-60E95F386FB2} " To apply this XML to the Data Profiling task, open the Property Expressions Editor by opening the Data Profiling Task Editor and going to the Expressions page. Select the ProfileInputXml property, and set the expression to be the ProfileXML variable. Now the task is set up so that you can change the target table by updating the Schema- Name and TableName variables, with no modification to the task necessary. Now that we’ve made the task dynamic, let’s move on to making decisions based on the output of the task. Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  6. Making data-quality decisions in the ETL 719 Expressions in SSIS Expressions in SSIS are limited to producing output no longer than 4,000 characters. Although that is enough for the example in this chapter, you may need to take it into account when working with multiple profiles. You can work around the limitation by executing the Data Profiling task multiple times, with a subset of the profiles in each execution to keep the expression under the 4,000-character limit. Making data-quality decisions in the ETL The Data Profiling task output can be used to make decisions about the quality of your data, and by incorporating the task output into your ETL process, you can auto- mate these decisions. By taking things a little further, you can make these decisions self-adjusting as your data changes over time. We’ll take a look at both scenarios in the following sections. Excluding data based on quality Most commonly, the output of the Data Profiling task will change the flow of your ETL depending on the quality of the data being processed in your ETL. A simple example of this might be using the Column Null Ratio profile to evaluate a Customer table prior to extracting it from the source system. If the null ratio is greater than 30 per- cent for the Customer Name column, you might have your SSIS package set up to abort the processing and log an error message. This is an example of using data profil- ing information to prevent bad data from entering your data warehouse. In situations like the preceding, though, a large percentage of rows that may have had acceptable data quality would also be excluded. For many data warehouses, that’s not acceptable. It’s more likely that these “hard” rules, such as not allowing null values in certain columns, will be implemented on a row-by-row basis, so that all acceptable data will be loaded into the warehouse, and only bad data will be excluded. In SSIS, this is often accomplished in the data flow by using Conditional Split transformations to send invalid data to error tables. Adjusting rules dynamically A more complex example involves using data profiling to establish what good data looks like, and then using this information to identify data of questionable quality. For example, if you are a retailer of products from multiple manufactures, your Product table will likely have the manufacturer’s original part number, and each manufacturer may have its own format for part numbers. In this scenario, you might use the Column Pattern profile against a known good source of part numbers, such as your Product table or your Product master, to identify the regular expressions that match the part numbers. During the execution of your ETL process, you could compare new incom- ing part numbers with these regular expressions to determine if they match the Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  7. 720 CHAPTER 56 Incorporating data profiling in the ETL process known formats for part numbers. As new products are added to the known good source of part numbers, new patterns will be included in the profile, and the rule will be adjusted dynamically. It’s worth noting that this type of data-quality check is often implemented as a “soft” rule, so the row is not prohibited from entering the data warehouse. After all, the manufacturer may have implemented a new part-numbering scheme, or the part number could have come from a new manufacturer that is not in the Product dimen- sion yet. Instead of redirecting the row to an error table, you might set a flag on the row indicating that there is a question as to the quality of the information, but allow it to enter the data warehouse anyway. This would allow the part number to be used for recording sales of that product, while still identifying a need for someone to follow up and verify that the part number is correct. Once they have validated the part number, and corrected it if necessary, the questionable data flag would be removed, and that product could become part of the known good set of products. The next time that you generate a Column Pattern profile against the part numbers, the new pattern will be included, and new rows that conform to it will no longer be flagged as questionable. As mentioned earlier, implementing this type of logic in your ETL process can allow it to dynamically adjust data-quality rules over time, and as your data quality gets better, the ETL process will get better at flagging questionable data. Now let’s take a look at how to use the task output in the package. Consuming the task output As mentioned earlier, the Data Profiling task produces its output as XML, which can be stored in a variable or a file. This XML output will include both the profile requests and the output profiles for each request. Capturing the output If you are planning to use the output in the same package that the profiling task is in, you will usually want to store the output XML in a package variable. If the output will be used in another package, how you store it will depend on how the other package will be executed. If the second package will be executed directly from the package performing the profiling through an Execute Package task, you can store the output in a variable and use a Parent Package Variable configuration to pass it between the packages. On the other hand, if the second package will be executed in a separate process or at a different time, storing the output in a file is the best option. Regardless of whether the output is stored in a variable or a file, it can be accessed in a few different ways. Because the output is stored as XML, you can make use of the XML task to use it in the control flow, or the XML source to use it in the data flow. You can also use the Script task or the Script component to manipulate the XML output directly using .NET code. Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  8. Consuming the task output 721 Using SSIS XML functionality The XML task is provided in SSIS so that you can work with XML in the control flow. Because the Data Profiling task produces XML, it is a natural fit to use the XML task to process the data profile output. Primarily, the XSLT or XPATH operations can be used with the profile XML. The XSLT operation can be used to transform the output into a format that’s easier to use, such as filtering the profile output down to specific profiles that you are inter- ested in, which is useful if you want to use the XML source to process it. The XSLT operation can also be used to remove the default namespace from the XML docu- ment, which makes using XPATH against it much easier. XPATH operations can be used to retrieve a specific value or set of nodes from the profile. This option is illustrated by the Trim Namespaces XML task in the sample package that accompanies this chapter, showing how to retrieve the null count for a particular column using XPATH. NOTE The sample package for this chapter can be found on the book’s website at http://www.manning.com/SQLServerMVPDeepDives. New to XML? If you are new to XML, the preceding discussion may be a bit confusing, and the rea- sons for taking these steps may not be obvious. If you’d like to learn more about working with XML in SSIS, please review these online resources: General XML information: http://msdn.microsoft.com/en-us/xml/default.aspx Working with XML in SSIS: http://blogs.msdn.com/mattm/archive/tags/XML/ default.aspx In the data flow, the XML source component can be used to get information from the Data Profiling task output. You can do this in two ways, one of which is relatively straightforward if you are familiar with XSLT. The other is more complex to imple- ment but has the benefit of not requiring in-depth XSLT knowledge. If you know XSLT, you can use an XML task to transform and simplify the Data Pro- filing task output prior to using it in the XML source, as mentioned previously. This can help avoid having to join multiple outputs from the XML source, which is dis- cussed shortly. If you don’t know XSLT, you can take a few additional steps and use the XML source directly against the Data Profiling task output. First, you must provide an .XSD file for the XML source, but the .XSD published by Microsoft at http:/ /schemas.micro- soft.com/sqlserver/2008/DataDebugger/DataProfile.xsd is too complex for the XML source. Instead, you will need to generate a schema using an existing data profile that you have saved to a file. Second, you have to identify the correct outputs from the XML source. The XML source creates a separate output for each distinct element type in the XML: the output from the Data Profiling task includes at least three distinct Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  9. 722 CHAPTER 56 Incorporating data profiling in the ETL process elements for each profile you include, and for most profiles it will have four or more. This can lead to some challenges in finding the appropriate output information from the XML source. Third, because the XML source does not flatten the XML output, you have to join the multiple outputs together to assemble meaningful information. The sample package on the book’s website (http:/ /www.manning.com/SQLServerMVP- DeepDives) has an example of doing this for the Column Pattern profile. The data flow is shown in figure 3. In the data flow shown in figure 3, the results of the Column Pattern profile are being transformed from a hierarchical structure (typical for XML) to a flattened struc- ture suitable for saving into a database table. The hierarchy for a Column Pattern pro- file has five levels that need to be used for the information we are interested in, and each output from the XML source includes one of these levels. Each level contains a column that ties it to the levels used below it. In the data flow, each output from the XML source is sorted, so that consistent ordering is ensured. Then, each output, which represents one level in the hierarchical structure, is joined to the output repre- senting the next level down in the hierarchy. Most of the levels have a ColumnPattern- Profile_ID, which can be used in the Merge Join transformation to join the levels, but there is some special handling required for the level representing the patterns, as they need to be joined on the TopRegexPatterns_ID instead of the ColumnPattern- Profile_ID. This data flow is included in the sample package for this chapter, so you can review the logic if you wish. Figure 3 Data flow to reassemble a Column Pattern profile Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  10. Consuming the task output 723 Using scripts Script tasks and components provide another means of accessing the information in the Data Profiling task output. By saving the output to a package variable, you make it accessible within a Script task. Once in the Script task, you have the choice of per- forming direct string manipulation to get the information you want, or you can use the XmlDocument class from the System.Xml namespace to load and process the out- put XML. Both of these approaches offer a tremendous amount of flexibility in work- ing with the XML. As working with XML documents using .NET is well documented, we won’t cover it in depth here. Another approach that requires scripting is the use of the classes in the DataPro- filer.dll assembly. These classes facilitate loading and interacting with the data profile through a custom API, and the approach works well, but this is an undocumented and unsupported API, so there are no guarantees when using it. If this doesn’t scare you off, and you are comfortable working with unsupported features (that have a good chance of changing in new releases), take a look at “Accessing a data profile program- matically” on the SSIS Team Blog (http://blogs.msdn.com/mattm/archive/2008/03/ 12/accessing-a-data-profile-programmatically.aspx) for an example of using the API to load and retrieve information from a data profile. Incorporating the values in the package Once you have retrieved values from the data profile output, using one of the meth- ods discussed in the previous sections, you need to incorporate it into the package logic. This is fairly standard SSIS work. Most often, you will want to store specific values retrieved from the profile in a package variable, and use those variables to make dynamic decisions. For example, consider the Column Null Ratio profiling we discussed earlier. After retrieving the null count from the profile output, you could use an expression on a precedence con- straint to have the package stop processing if the null count is too high. In the data flow, you will often use Conditional Split or Derived Column transfor- mations to implement the decision-making logic. For example, you might use the Data Profiling task to run a Column Length Distribution profile against the product description column in your Product table. You could use a Script task to process the profile output and determine that 95 percent of your product descriptions fall between 50 and 200 characters. By storing those boundary values in variables, you could check for new product descriptions that fall outside of this range in your ETL. You could use the Conditional Split transformation to redirect these rows to an error table, or the Derived Column transformation to set a flag on the row indicating that there might be a data-quality issue. Some data-quality checking is going to require more sophisticated processing. For the Column Pattern checking scenario discussed earlier, you would need to imple- ment a Script component in the data flow that can take a list of regular expressions and apply them against the column that you wanted to check. If the column value Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  11. 724 CHAPTER 56 Incorporating data profiling in the ETL process matched one or more of the regular expressions, it would be flagged as OK. If the col- umn value didn’t match any of the regular expressions, it would be flagged as ques- tionable, or redirected to an error table. Listing 3 shows an example of the code that can perform this check. It takes in a delimited list of regular expression patterns, and then compares each of them to a specified column. Listing 3 Script component to check column values against a list of patterns public class ScriptMain : UserComponent { List regex = new List(); public override void PreExecute() { base.PreExecute(); string[] regExPatterns; IDTSVariables100 vars = null; this.VariableDispenser.LockOneForRead("RegExPatterns", ref vars); regExPatterns = vars["RegExPatterns"].Value.ToString().Split("~".ToCharArray()); vars.Unlock(); foreach (string pattern in regExPatterns) { regex.Add(new Regex(pattern, RegexOptions.Compiled)); } } public override void Input0_ProcessInputRow(Input0Buffer Row) { if (Row.Size_IsNull) return; foreach (Regex r in regex) { Match m = r.Match(Row.Size); if (m.Success) { Row.GoodRow = true; } else { Row.GoodRow = false; } } } } Summary Over the course of this chapter, we’ve looked at a number of ways that the Data Profil- ing task can be used in SSIS, from using it to get a better initial understanding of your data to incorporating it into your ongoing ETL processes. Being able to make your ETL process dynamic and more resilient to change is important for ongoing mainte- nance and usability of the ETL system. As data volumes continue to grow, and more Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  12. Summary 725 data is integrated into data warehouses, the importance of data quality increases as well. Establishing ETL processes that can adjust to new data and still provide valid feedback about the quality of that data is vital to keeping up with the volume of infor- mation we deal with today. About the author John Welch is Chief Architect with Mariner, a consulting firm spe- cializing in enterprise reporting and analytics, data warehousing, and performance management solutions. John has been working with business intelligence and data warehousing technologies for seven years, with a focus on Microsoft products in heterogeneous environments. He is an MVP and has presented at Professional Association for SQL Server (PASS) conferences, the Microsoft Busi- ness Intelligence conference, Software Development West (SD West), Software Management Conference (ASM/SM), and others. He has also contrib- uted to two recent books on SQL Server 2008: Microsoft SQL Server 2008 Management and Administration (Sams, 2009) and Smart Business Intelligence Solutions with Microsoft SQL Server 2008 (Microsoft Press, 2009). Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  13. 57 Expressions in SQL Server Integration Services Matthew Roche SQL Server Integration Services (SSIS) is Microsoft’s enterprise extract, transform, and load (ETL) platform, and is used in large-scale business intelligence projects and small-scale import/export jobs around the world. Although SSIS contains an impressive set of features for solving a range of data-centric problems, one fea- ture—expressions—stands out as the most important for SSIS developers to master. Expressions in SSIS are a mechanism to add dynamic functionality to SSIS pack- ages; they are the primary tool that SSIS developers can use to build packages to solve complex real-world problems. This chapter examines SSIS expressions from the per- spective of providing elegant solutions to common problems and presents a set of tested techniques that will allow you to take your SSIS packages to the next level. SSIS packages: a brief review Before we can dive into the deep end with expressions, we need to look at SSIS packages—the context in which expressions are used. Packages in SSIS are the units of development and deployment; they’re what you build and execute, and have a few common components, including Control flow—The execution logic of the package, which is made up of tasks, containers, and precedence constraints. Each package has a single control flow. Data flow—The high-performance data pipeline that powers the core ETL functionality in SSIS, and is made up of sources, transformations, and desti- nations. The SSIS data flow is implemented as a task, which allows multiple data flow tasks to be added to a package’s control flow. Connection managers—Shared components that allow the control flow and data flow to connect to databases, files, and other resources outside of the package. 726 Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  14. Expressions: a quick tour 727 Variables—The sole mechanism for sharing information between components in an SSIS package; variables have deep integration with expressions as well. SSIS packages include more than just these elements, but for the purposes of this chapter, that’s enough review. Let’s move on to the good stuff: expressions! Expressions: a quick tour Expressions add dynamic functionality to SSIS packages using a simple syntax based on a subset of the C language. Expression syntax does not include any control of flow (looping, branching, and so on) or data modification capabilities. Each expression evaluates to a single scalar value, and although this can often seem restrictive to devel- opers who are new to SSIS, it allows expressions to be used in a variety of places within a package. How can we use expressions in a package? The simplest way is to use property expressions. All containers in SSIS, including tasks and the package itself, have an Expressions property, which is a collection of expressions and the properties to which their values will be assigned. This allows SSIS package developers to specify their own code—the expression—that is evaluated whenever a property of a built-in or third- party component is accessed. How many other development tools let you do that? Let’s look at an example. Figure 1 shows the properties for an Execute SQL Task configured to execute a DELETE statement. Although this Execute SQL Task is functional, it isn’t particularly useful unless the package always needs to delete the order details for [OrderID]=5. This task would be much more useful if it instead deleted whatever order number was current for the pack- age execution. To implement this dynamic behavior, we’re going to take two steps. First, we’re going to add a new variable, named OrderID, to the package. (If you don’t Figure 1 Static task properties Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  15. 728 CHAPTER 57 Expressions in SQL Server Integration Services Figure 2 Adding a property expression know how to do this already, consider it an exercise—we won’t walk through adding a variable step by step.) Second, we’re going to add a property expression to the Sql- StatementSource property of the Execute SQL Task. To do this, we’ll follow the steps illustrated in figure 2. 1 In the Properties window, select Execute SQL Task and then click on the ellipsis (...) button next to the Expressions property. This will cause the Property Expressions Editor dialog box to be displayed. 2 In the Property Expressions Editor dialog box, select the SqlStatementSource property from the drop-down list in the Property column. 3 Click on the ellipsis button in the Expression column. This will cause the Expression Builder dialog box to be displayed. (Please note that figure 2 shows only a subset of the Expression Builder dialog box to better fit on the printed page.) 4 Enter the following expression in the Expression text box: "DELETE FROM [dbo].[Order Details] WHERE [OrderID] = " + (DT_WSTR, 50) @[User::OrderID] 5 Click on the Evaluate Expression button to display the output of the expression in the Evaluated Value text box. (At this point it may be useful to copy and paste this value into a SQL Server Management Studio query window to ensure that the expression was constructed correctly.) Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  16. Expressions in the control flow 729 6 Click on the OK buttons to close the Expression Builder and Property Expres- sions Editor windows and save all changes. 7 Execute the package to ensure that the functionality added through the expres- sion behaves as required. Several important techniques are demonstrated in these steps: We started with a valid static value before we added the expression. Instead of starting off with a dynamic SQL statement, we started with a static statement which we tested to ensure that we had a known good starting point. We added a single piece of dynamic functionality at a time. Because our exam- ple was simple, we only added a single piece of dynamic functionality in total; but if we were adding both a dynamic WHERE clause and a dynamic table name, we would’ve added each dynamic expression element to the static SQL state- ment individually. We tested the expression after each change. This basic technique is often over- looked, but it’s a vital timesaver. The Expression Editor has limited debugging capabilities, and locating errors in a complex expression can be painfully diffi- cult. By testing the expression after each change, the scope of debugging can be significantly reduced. With this example setting the stage, let’s dive deeper into SSIS expressions by illustrat- ing how they can be used to add dynamic functionality to our packages, and solve real- world problems. Expressions in the control flow We’ll continue by looking at expressions in the SSIS control flow. Although the exam- ple in the previous section is technically a control flow example (because we applied a property expression to a property of a task, and tasks are control flow components) there are more interesting examples and techniques we can explore. One of the most important—and overlooked—techniques is using expressions with precedence con- straints to conditionally execute tasks. Consider the following requirements: If a specific table exists in the target database, execute a data flow task. If the table does not exist, execute an Execute SQL Task to create the table, and then execute the data flow task. If this problem needed to be solved using a traditional programming language, the developer would add an if statement and that would be that. But SSIS does not include an if statement, a branching task, or the like, so the solution, although sim- ple, is not always obvious. An often-attempted approach to solve this problem is to add a property expression to the Disabled property of the Execute SQL Task. The rationale here is that if the Exe- cute SQL Task is disabled then it won’t execute, and only the data flow task will run. The main problem with this approach is that the Disabled property is designed to be used Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  17. 730 CHAPTER 57 Expressions in SQL Server Integration Services only at design time; setting Disabled to True is similar to commenting out a task so that it remains part of the control flow—but as far as the SSIS runtime is concerned, the task doesn’t exist. The preferred way to achieve this goal is to use expressions on the precedence con- straints that connect the various tasks in the control flow. In addition to the three dif- ferent constraints that can be used (success, failure, and completion), each precedence constraint can be edited to include an expression that determines whether or not this particular branch of the control flow logic will execute. The expression must have a Boolean return value—it must evaluate to true or false—and this value controls the conditional execution. Figure 3 illustrates the control flow configuration necessary to implement the required behavior using expressions. Implementing this solution has three primary steps: 1 The results of the SELECT statement run by the Execute SQL Task are stored in a Boolean package variable named TableExists. To map the value into a Bool- ean variable, CAST the data type to BIT in the SELECT statement, returning 1 if the table exists, and 0 if not. 2 Each precedence constraint has been edited to apply the Expression and Con- straint Evaluation operation option, with the appropriate expression (for one, @TableExists; for the other, !@TableExists) specified to enforce the required logic. Note that the two expressions are both mutually exclusive (they cannot both be true at the same time) and also inclusive—there is no condition that’s not represented by one of the two expressions. 3 The @TableExists precedence constraint has been edited to specify the Logi- cal OR option—this is why the constraints that reference the data flow task are displayed with dotted lines. This is required because, as you’ll recall, the two Check to See if ✔ Table Exists ƒx ƒx Success and @TableExists Success and !@TableExists Create Missing ✔ Table Success Load Data Into Figure 3 Conditional Table execution with expressions Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  18. Expressions in the control flow 731 paths from the first Execute SQL Task are mutually exclusive, but both paths end at the data flow task. Unless one of the two precedence constraints that end at the data flow task is so edited (you only need to edit one, because the change in operation will apply to all precedence constraints that end at the same task)—the data flow task will never execute. Self-documenting precedence constraints If you would like your precedence constraints to include the constraint options and expressions shown in figure 3, all you need to do is set the ShowAnnotation property for each precedence constraint. The default value for this property is AsNeeded, and does not cause this information to be displayed; but setting this property to Con- straintOptions for each precedence constraint will cause these annotations to be displayed. Unfortunately, SSIS does not support setting a default value for this prop- erty, but it is easy to select multiple precedence constraints and set this property for all of them at one time. Taking this step will make your packages self-documenting, and easier to debug and maintain. The final settings for the @TableExists precedence constraint can be seen in figure 4. One additional requirement for this approach is the need for a task from which the precedence constraints can originate. In this example, the need for the Execute SQL Task is obvious—the package uses this task to check to see if the target table exists. But Figure 4 Precedence constraint with expression Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  19. 732 CHAPTER 57 Expressions in SQL Server Integration Services there are other common scenarios, such as when the state upon which the conditional logic must be based is set via a package configuration, and the first task in the package must be executed or skipped based on this state, where the natural package logic does not include a task from which the expression-based precedence constraints should originate. This can pose a predicament, because precedence constraints must originate from a task or container, and this type of conditional logic is implemented in SSIS by using precedence constraints and expressions. In situations such as these, a useful technique is to add a placeholder task—one that serves as the starting point for precedence constraints—to the control flow. Two obvi- ous candidates for this placeholder role are the Script Task and the Sequence Con- tainer; each of these components will work without any configuration required, and won’t alter the package logic. Additional reading online For more detailed examples on how to use expressions in the control flow, see these online resources: Expressions and precedence constraints: http://bi-polar23.blogspot.com/ 2008/02/expressions-and-precedence-constraints.html Using placeholder tasks: http://bi-polar23.blogspot.com/2007/05/ conditional-task-execution.html Expressions and the Foreach Loop Container: http://bi-polar23. blogspot.com/2007/08/loading-multiple-excel-files-with-ssis.html Expressions and variables In addition to using property expressions, you can also use expressions with SSIS vari- ables. In fact, variables in SSIS have a special ability related to expressions: they not only have a Value property, but also an EvaluateAsExpression property. If this Bool- ean property is set to true, when the variable’s value is accessed, instead of returning the value of the Value property, the variable will evaluate the expression that's stored in its Expression property. Configuring variables to evaluate as expressions is a powerful technique. Instead of always returning a hard-coded value—or relying on the Script Task or other com- ponents to update the variable’s value—the variable can return a dynamic value that reflects the current state of the executing package. For developers with object- oriented programming experience, this is analogous to using a property get accessor instead of a field; it provides a mechanism by which you can add custom code that is run whenever the variable’s value is read. This technique allows you to use variables as containers for expressions, so that they can be used in multiple places throughout the package. Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
  20. Expressions and variables 733 One real-life example of this technique is managing the loca- tions of filesystem resources. Consider a package that works with files in a folder structure, like the one shown in figure 5. As you can see, there is a DeploymentRoot folder that con- tains subfolders for the different types of files with which the Figure 5 package interacts. In the real world, the root folder could exist Deployment folders on different drives and in different locations in the filesystem structure, on the different machines to which the package may be deployed. To handle this eventuality, you’d use package configurations—or a simi- lar mechanism—to inform the package where the files are located, probably by using the configuration to set the value of a @DeploymentRootPath variable. You could then use multiple configurations to set the values of multiple variables, one for each folder, but there is a better way. And as you have likely guessed—this better way uses expressions. For the folder structure shown in figure 5, you could create four additional vari- ables, one for each subfolder, configured to evaluate as the following expressions: @ErrorFilePath - @DeploymentRootPath + "\\ErrorFiles" @ImportFilePath - @DeploymentRootPath + "\\ImportFiles" @LogFilePath - @DeploymentRootPath + "\\LogFiles" @OutputFilePath - @DeploymentRootPath + "\\LogFiles" And it doesn’t stop there. It’s not uncommon to see packages where a different sub- folder must be used per client, or per year, or per day—and having a set of variables based on expressions that can in turn be used as the basis for more granular expres- sions is a great way to achieve reuse within a package. And, in this scenario, only one configuration is required—the value for the @DeploymentRootPath variable can be set via a configuration, and all other filesystem paths will be automatically updated because they’re based on expressions that use this variable as their source. Additional reading online For more detailed examples on how to use expressions with package variables, see these online resources: Filesystem deployment: http://bi-polar23.blogspot.com/2007/05/flexible- file-system-deployment.html Dynamic filename expressions: http://bi-polar23.blogspot.com/2008/06/ file-name-expressions.html Dynamic filenames and dates: http://bi-polar23.blogspot.com/2008/06/ looking-for-date-what-in-name.html Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.
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