Which operation is used to merge data into a table based on specific conditions?

The operation used to merge data into a table based on specific conditions is known as "MERGE INTO." This command allows users to combine data from one data source (such as a DataFrame or another table) into an existing table, utilizing specified conditions to determine how the records should be integrated. The primary advantage of using the MERGE INTO statement is that it can perform multiple actions in one go—such as inserting new rows, updating existing rows, or deleting rows—depending on whether the specified conditions match.

For instance, you might want to update records in a target table if they exist in the source table and insert them if they don’t. This capability makes the MERGE INTO operation particularly powerful in scenarios where maintaining data consistency and up-to-date information is essential.

Other operations mentioned do not fulfill the same role. COPY INTO is used primarily for loading data from external storage into a table. INSERT TABLE is typically associated with adding new rows directly rather than merging with existing ones. UPDATE TABLE focuses solely on altering existing records without the broader functionality of conditionally inserting or deleting rows based on the relationship between two sets of data. Thus, MERGE INTO is the best fit for merging data with conditions.