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  3. You are the administrator of a SQL Server 2000 computer. The server contains a database that stores financial data. You want to

You are the administrator of a SQL Server 2000 computer. The server contains a database that stores financial data. You want to

admin2009-05-19  27
问题 You are the administrator of a SQL Server 2000 computer. The server contains a database that stores financial data. You want to use Data Transformation Services packages to import numeric data from other SQL server computers. The precision and scale values of this data are not defined consistently on the other servers.
You want to prevent any loss of data during the import operations. What should you do?
选项 A、Use the ALTER COLUMN clause of the ALTER TABLE statement to change data types in the source tables. Change the data types so that they will use the lowest precision and scale values of the data that will be transferred.
B、Use the ALTER COLUMN clause of the ALTER TABLE statement to change data types in the destination tables. Change the data types to reflect the highest precision and scale values involved in data transfer.
C、Set a flag on each DTS transformation to require an exact match between source and destination columns.
D、Set the maximum error count for each DTS transformation task equal to the number of rows of data you are importing. Use an exception file to store any rows of data that generate errors.
E、Write Microsoft ActiveX script for each DTS transformation. Use the script to recast data types to the destinations precision and scale values.
答案B
解析 Explanation: The ALTER COLUMN clause of the ALTER TABLE statement can be used to change the definition of a column and can be used to alter the precision and scale values of the data types. The destination precision should be changed so no data would be lost. The transformation to a data type with higher precision is automatic and would not require any coding.

Note: The precision of the data type refers to the number of digits in a number while the scale is the number of digits to the right of the decimal point in a number. Thus the number 702.85 has a precision of 5 and a scale of 2. The default maximum precision of numeric and decimal data types is 38.

Incorrect Answers:
A: The ALTER COLUMN clause of the ALTER TABLE statement can be used to change the definition of a column and can be used to alter the precision and scale values of the data types. However, we want to prevent any loss of data therefore we need to ensure that the data being imported correlates with the definition of the destination column. If it does not, any constraint that might exist on the destination column will prevent the data from being inserted.

C: Setting DTS transformation to require an exact match between source and destination columns refers to the data in the columns.

D: When the a maximum error count value for a DTS transformation task specifies the sum of row-level errors detected by the Transform Data task and batch failures. When the Max error count value is exceeded, DTS task execution is terminated. Because rows containing errors detected by the DTS transformation task are discarded before batch submission, these errors do not trigger nor count as batch failures. Errors caught at the destination will fail the batch and add one to the error count regardless of how many rows are in the batch.

E: Recasting data types to the destinations precision could result in loss of data. The destination precision should be changed so no data would be lost.

Note: The capabilities of a Data Transformation Service package can be extended by using
Microsoft ActiveX scripts that implement the objects, properties, methods, and collections of the DTS object model. With ActiveX scripts the data can be formatted and transformed as it is copied from its source to the destination location.

An ActiveX script transformation applies to tasks that work on the source data on a row-by-row basis and can be used to replace a two-digit state code in the source data with the legal abbreviation of the state in the destination data; set columns to a default of spaces, validate important columns in the source data and skip records that contain invalid data to prevent them from being copied to the destination, and alter the precision and scale values of data as the data copied from the source to the destination.
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