Snowflake Certification Practice Test

Why is the SQL statement "SELECT * FROM TABLE" considered inefficient in Snowflake?

1. It retrieves too many columns

2. It doesn't use any filters

3. There will be little to no horizontal pruning

4. It may cause data corruption

The correct answer is: There will be little to no horizontal pruning

The assertion that the SQL statement "SELECT * FROM TABLE" is considered inefficient due to a lack of horizontal pruning captures an important aspect of how Snowflake optimizes data retrieval. In Snowflake, horizontal pruning refers to the engine's ability to skip over unnecessary partitions of data when executing a query. When using an `SELECT *` statement, all rows from a table are retrieved without any filters or conditions to limit the scope of the query. This means that Snowflake has to scan the entire dataset to fetch all rows, which can lead to excessive resource utilization and longer wait times, especially with large datasets. In scenarios where there are no filters applied, Snowflake cannot effectively leverage any existing clustering or partitioning strategies to minimize the amount of data scanned. This results in the retrieval of more data than might actually be needed for specific analytical requirements, leading to inefficient use of computational resources and slower performance. The other choices highlight relevant issues but do not directly address the core element of horizontal pruning as it pertains specifically to query efficiency in Snowflake. While retrieving too many columns can result in unnecessary data being sent over the network, it doesn't capture the broader inefficiency in terms of data scanning. Similarly, while not applying filters does imply reduced efficiency, the emphasis on