We also see that other values in the file don’t match those data either – for instance, the 0 or 1 of SpefzC looks like a bit and not a varchar. For an example of this, in the below code that creates the table and the below image of the file, we see that the first line of data from the file has values like SpefzA, SpefzB, SpefzC, SpefzD which don’t match the table’s data type (except in 2 cases). We do not necessarily have to keep the column names when we use bulk insert to insert the data, but we should be careful about inserting data into a specific format, if we also insert the first row that doesn’t match that format. With many imports, the first row of data in the file will specify the columns of the file. Skipping Lines and Working With Data Types In this part, we look at these techniques using T-SQL’s native bulk insert. Sometimes we’ll want to skip first and ending lines, log errors and bad records for review after inserting data, and work with data types directly without first importing using a varchar and converting to the data type later. In the first part of reviewing the basics of bulk insert, we looked at importing entire files, specifying delimiters for rows and columns, and bypassing error messages.
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