Parquet is a columnar storage file format that is optimized for performance in Snowflake. It is designed to be efficient for both storage and query performance, particularly for complex queries onlarge datasets. Parquet files support efficient compression and encoding schemes, which can lead to significant savings in storage and speed in query processing, making it the most performant file format for loading data into Snowflake.
[References:, [COF-C03] SnowPro Core Certification Exam Study Guide, Snowflake Documentation on Data Loading1, , ]
Question 173
What is a responsibility of Snowflake ' s virtual warehouses?
The primary responsibility of Snowflake’s virtual warehouses is to execute queries. Virtual warehouses are one of the key components of Snowflake’s architecture, providing the compute power required to perform data processing tasks such as running SQL queries, performing joins, aggregations, and other data manipulations.
[References:, [COF-C03] SnowPro Core Certification Exam Study Guide, SnowflakeDocumentation on Virtual Warehouses1, , ]
Question 174
What is a key feature of Snowflake architecture?
Options:
A.
Zero-copy cloning creates a mirror copy of a database that updates with the original
B.
Software updates are automatically applied on a quarterly basis
C.
Snowflake eliminates resource contention with its virtual warehouse implementation
D.
Multi-cluster warehouses allow users to run a query that spans across multiple clusters
E.
Snowflake automatically sorts DATE columns during ingest for fast retrieval by date
One of the key features of Snowflake’s architecture is its unique approach to eliminating resource contention through the use of virtual warehouses. This is achieved by separating storage and compute resources, allowing multiple virtual warehouses to operate independently on the same data without affecting each other. This means that different workloads, such as loading data, running queries, or performing complex analytics, can be processed simultaneously without any performance degradation due to resource contention.
[References:, Snowflake Documentation on Virtual Warehouses, SnowPro® Core Certification Study Guide, , ]
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Question 175
What is a limitation of a Materialized View?
Options:
A.
A Materialized View cannot support any aggregate functions
B.
A Materialized View can only reference up to two tables
C.
A Materialized View cannot be joined with other tables
Materialized Views in Snowflake are designed to store the result of a query and can be refreshed to maintain up-to-date data. However, they have certain limitations, one of which is that they cannot be defined using a JOIN clause. This means that a Materialized View can only be created based on a single source table and cannot combine data from multiple tables using JOIN operations.
[References:, Snowflake Documentation on Materialized Views, SnowPro® Core Certification Study Guide, , ]
