Snowflake Updated SnowPro-Core Exam Questions and Answers by cassandra

Snowflake uses a technique called pruning to limit the number of micro-partitions scanned by each query. Pruning effectively filters out unnecessary micro-partitions based on the query’s filter conditions, which can significantly improve query performance by reducing the amount of data scanned1.

 Snowpark is designed to bring the data programmability to Snowflake, enabling developers to write code in familiar languages like Scala, Java, and Python. It allows for the execution of these codes directly within Snowflake’s virtual warehouses, eliminating the need for a separate cluster. Additionally, Snowpark’s compatibility with Spark allows users to leverage their existing Spark code with minimal changes1.

 In Snowflake, schema objects include Pipes and File formats. Pipes are used for continuous data loading, and File formats specify the format of data files used in loading and unloading operations within Snowflake

 Scaling up the virtual warehouse in Snowflake involves increasing the compute resources available for a single warehouse, which can improve the performance of large and complex queries by providing more CPU and memory resources. References: Based on general cloud data warehousing knowledge as of 2021.