SPS-C01 Exam Dumps | You are using Snowpark Python to process a large dataset. You need to persist a DataFrame to a Snowflake

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Question 10/151

You are using Snowpark Python to process a large dataset. You need to persist a DataFrame to a Snowflake table but want to ensure the operation is as efficient as possible and minimizes the data transfer overhead. The table already exists with the appropriate schema. Which of the following strategies would be the MOST efficient way to write the DataFrame to the existing table?

A. Use with the default save mode (which is 'append').

B. Use 'df.write.mode('overwrite').saveAsTable('existing_table'Y.

C. Use 'df.write.insertlnto('existing_table')'.

D. Create a temporary table, load the DataFrame into it using , and then use a 'CREATE OR REPLACE TABLE AS SELECT FROM temp_table' statement.

E. Write the DataFrame to a stage location as Parquet files and then use a 'COPY INTO existing_table FROM command.

Correct Answer: C

is generally the most efficient method for appending data to an existing Snowflake table using Snowpark. It directly inserts the data into the table without the overhead of creating a new table or overwriting the existing one. with the default 'append' mode (A) might work, but 'insertlnto' is more explicit and potentially optimized for this specific scenario. (B) would replace the entire table, which is not efficient if you only want to add new data. Creating a temporary table and then using 'CREATE OR REPLACE TABLE AS SELECT (D) involves unnecessary steps and data transfer. Writing to a stage and then using 'COPY INTO' (E) is also less efficient than directly inserting the data using Snowpark.

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