If the transformation uses a dynamic cache, you can pass rows to a Filter or Router transformation to filter new rows to the target. If there is no match for the lookup condition, the Integration Service returns the default value for all output ports. An unconnected look up transformation can receive the multi input ports but returns single. An unconnected look up transformation is commonly used when the look is not needed for every record.
An unconnected look up transformation that supports to write expression. The look up function used in conditional statement. The condition is evaluated from each row, but the look up function is only call if the condition evaluates to true. Business purpose:. A source table or file may have a percentage of records with incomplete data. The holes in the data can be filled by performing a look up to another table or table.
As only a percentage of the rows are affected, it is better to perform the look up on only those rows that need it and not the entire data set. A reusable transformation is a reusable meta data object created with business logic using single transformation There are 2 different ways to create reusable transformations.
A user defined function is a power center object which is created using a set of built in function to meet specific requirements. A user defined function created using power center designer client. So in this case it may be better to use a lookup.
Another time when you might use a lookup is when you need it conditionally. For example, if you have an expression and one of the ports is status. This can be handled using unconnected lookups called from the expression transformation. These a just a couple of things I can think of off the top of my head. There are more reasons to use a lookup that other members might want to share. Another very good reason for using lookups is when you are looking up on the target table in order to return, or allocate, a surrogate key.
Especially when there is the potential to have more than one record with the same natural key in the source. This cannot be achieved with a joiner or source qualifier, as the surrogate key is allocated dynamically during the mapping execution.
Dynamic, persistent lookup caches can be used when more than one mapping load the same target table. Otherwise, you should use a lookup, especially if you want to avoid cartesian joins. The performance difference between a joiner and a lookup are very different, lookups tend to perform much better. Also, lookups allow you to use criteria other than equal in the lookup condition. And as already mentioned, you can avoid cartesian results and you can retrieve either the first or last record from a result set.
Joiners are active transformations and will block the data flow until all records are read unless you use the sorted input option but this requires spending time sorting the data. This means ALL records must be stored in memory and will only be released when all records are read. Multiple joiners means multiple times the data gets blocked. Lookups are passive so the data never gets blocked so avoids the problem of having to hold all records in memory.
When you select any other option in the Specify how to handle rows with no matching entries list box, the rows are handled as errors. The Error option on the Error Output page is available. Blog entry, Lookup cache modes on blogs. Use the Connection page of the Lookup Transformation Editor dialog box to select a connection manager.
If you select an OLE DB connection manager, you also select a query, table, or view to generate the reference dataset. The following options are available when you select Full cache and Cache connection manager on the General page of the Lookup Transformation Editor dialog box. Cache connection manager Select an existing Cache connection manager from the list, or create a new connection by clicking New. Use a table or view Select an existing table or view from the list, or create a new table by clicking New.
New Create a new table by using the Create Table dialog box. Use results of an SQL query Choose this option to browse to a preexisting query, build a new query, check query syntax, and preview query results.
Build query Create the Transact-SQL statement to run by using Query Builder , a graphical tool that is used to create queries by browsing through data. Preview Preview results by using the Preview Query Results dialog box. This option displays up to rows. Use the Columns page of the Lookup Transformation Editor dialog box to specify the join between the source table and the reference table, and to select lookup columns from the reference table.
Available Input Columns View the list of available input columns. The input columns are the columns in the data flow from a connected source. The input columns and lookup column must have matching data types. You can also map input columns to lookup columns using the keyboard, by highlighting a column in the Available Input Columns table, pressing the Application key, and then clicking Edit Mappings.
Available Lookup Columns View the list of lookup columns. The lookup columns are columns in the reference table in which you want to look up values that match the input columns. Use the check boxes to select lookup columns in the reference table on which to perform lookup operations. You can also map lookup columns to input columns using the keyboard, by highlighting a column in the Available Lookup Columns table, pressing the Application key, and then clicking Edit Mappings.
Lookup Column View the selected lookup columns. The selections are reflected in the check box selections in the Available Lookup Columns table. Lookup Operation Select a lookup operation from the list to perform on the lookup column.
Output Alias Type an alias for the output for each lookup column. The default is the name of the lookup column; however, you can select any unique, descriptive name. Python Turtle. Verbal Ability. Interview Questions. Company Questions. Artificial Intelligence. Cloud Computing.
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