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  1. Home
  2. Snowflake Certification
  3. ARA-C01 Exam
  4. Snowflake.ARA-C01.v2024-12-26.q155 Dumps
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Question 126

What are some of the characteristics of result set caches? (Choose three.)

Correct Answer: B,C,E
Comprehensive and Detailed Explanation: According to the SnowPro Advanced: Architect documents and learning resources, some of the characteristics of result set caches are:
Snowflake persists the data results for 24 hours. This means that the result set cache holds the results of every query executed in the past 24 hours, and can be reused if the same query is submitted again and the underlying data has not changed1.
Each time persisted results for a query are used, a 24-hour retention period is reset. This means that the result set cache extends the lifetime of the results every time they are reused, up to a maximum of 31 days from the date and time that the query was first executed1.
The retention period can be reset for a maximum of 31 days. This means that the result set cache will purge the results after 31 days, regardless of whether they are reused or not. After 31 days, the next time the query is submitted, a new result is generated and persisted1.
The other options are incorrect because they are not characteristics of result set caches. Option A is incorrect because Time Travel queries cannot be executed against the result set cache. Time Travel queries use the AS OF clause to access historical data that is stored in the storage layer, not the result set cache2. Option D is incorrect because the data stored in the result set cache does not contribute to storage costs. The result set cache is maintained by the service layer, and does not incur any additional charges1. Option F is incorrect because the result set cache is shared between warehouses. The result set cache is available across virtual warehouses, so query results returned to one user are available to any other user on the system who executes the same query, provided the underlying data has not changed1. Reference: Using Persisted Query Results | Snowflake Documentation, Time Travel | Snowflake Documentation
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Question 127

Which data models can be used when modeling tables in a Snowflake environment? (Select THREE).

Correct Answer: B,D,F
Snowflake is a cloud data platform that supports various data models for modeling tables in a Snowflake environment. The data models can be classified into two categories: dimensional and normalized. Dimensional data models are designed to optimize query performance and ease of use for business intelligence and analytics. Normalized data models are designed to reduce data redundancy and ensure data integrity for transactional and operational systems. The following are some of the data models that can be used in Snowflake:
Dimensional/Kimball: This is a popular dimensional data model that uses a star or snowflake schema to organize data into fact and dimension tables. Fact tables store quantitative measures and foreign keys to dimension tables. Dimension tables store descriptive attributes and hierarchies. A star schema has a single denormalized dimension table for each dimension, while a snowflake schema has multiple normalized dimension tables for each dimension. Snowflake supports both star and snowflake schemas, and allows users to create views and joins to simplify queries.
Inmon/3NF: This is a common normalized data model that uses a third normal form (3NF) schema to organize data into entities and relationships. 3NF schema eliminates data duplication and ensures data consistency by applying three rules: 1) every column in a table must depend on the primary key, 2) every column in a table must depend on the whole primary key, not a part of it, and 3) every column in a table must depend only on the primary key, not on other columns. Snowflake supports 3NF schema and allows users to create referential integrity constraints and foreign key relationships to enforce data quality.
Data vault: This is a hybrid data model that combines the best practices of dimensional and normalized data models to create a scalable, flexible, and resilient data warehouse. Data vault schema consists of three types of tables: hubs, links, and satellites. Hubs store business keys and metadata for each entity. Links store associations and relationships between entities. Satellites store descriptive attributes and historical changes for each entity or relationship. Snowflake supports data vault schema and allows users to leverage its features such as time travel, zero-copy cloning, and secure data sharing to implement data vault methodology.
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Question 128

You have an inventory table. You created two views on this table. The views look like as below
CREATE VIEW NON_SECURE_INVENTORY AS
SELECT BIBNUMBER, TITLE, AUTHOR,ISBN
FROM INVENTORY
WHERE BIBNUMBER IN(511784,511805,511988,512044,512052,512063);
CREATE SECURE VIEW SECURE_INVENTORY AS
SELECT BIBNUMBER, TITLE, AUTHOR,ISBN
FROM INVENTORY
WHERE BIBNUMBER IN(511784,511805,511988,512044,512052,512063);
You ran the below queries
ALTER SESSION SET USE_CACHED_RESULT=FALSE;--This is to ensure that we do not retrieve from query cache
SELECT * FROM NON_SECURE_INVENTORY WHERE BIBNUMBER =511784; SELECT * FROM SECURE_INVENTORY WHERE BIBNUMBER =511784;
The query profile for the first query looks as below

However, the query profile for the second one looks like as below

Both the views use the same columns from the same underlying view. So, why is this difference in query profiles.

Correct Answer: A
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Question 129

Running EXPLAIN on a query does not require a running warehouse

Correct Answer: B
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Question 130

Which statement is not true about shared database?

Correct Answer: B
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