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| Section | Objectives |
|---|---|
| Snowflake Architecture and Overview | - Virtual warehouses and resource scaling concepts - Snowflake architecture concepts (cloud data platform, separation of storage and compute) |
| Data Protection, Security, and Performance | - Role-based access control (RBAC) - Time Travel and Fail-safe concepts - Query performance optimization basics |
| Data Loading and Unloading | - Data unloading and external stages - Bulk loading using stages and COPY INTO |
| Data Transformations and Querying | - SQL querying in Snowflake - Semi-structured data handling (VARIANT, JSON, Parquet) |
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NEW QUESTION # 430
What causes objects in a data share to become unavailable to a consumer account?
Answer: C
Explanation:
Objects in a data share become unavailable to a consumer account if the objects in the data share are deleted or if the permissions on these objects are altered without re-applying the grant permissions systematically. This is because the sharing mechanism in Snowflake relies on explicit grants of permissions on specific objects (like tables, views, or secure views) to the share. If these objects are deleted or if their permissions change without updating the share accordingly, consumers can lose access.
The DATA_RETENTION_TIME_IN_DAYS parameter does not directly affect the availability of shared objects, as it controls how long Snowflake retains historical data for time travel and does not impact data sharing permissions.
Running the GRANT IMPORTED PRIVILEGES command in the consumer account is not related to the availability of shared objects; this command is used to grant privileges on imported objects within the consumer's account and is not a routine maintenance command that would need to be run regularly.
Acquiring a data share through a private data exchange does not inherently make objects unavailable; issues would only arise if there were problems with the share configuration or if the shared objects were deleted or had their permissions altered without re-granting access to the share.
NEW QUESTION # 431
Which snowflake objects will incur both storage and cloud compute charges? (Select TWO)
Answer: A,C
Explanation:
In Snowflake, both materialized views and transient tables will incur storage charges because they store data.
They will also incur compute charges when queries are run against them, as compute resources are used to process the queries. References: [COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 432
What is the recommended file sizing for data loading using Snowpipe?
Answer: B
Explanation:
For data loading using Snowpipe, the recommended file size is a compressed file greater than 10 MB and up to 100 MB. This size range is optimal for Snowpipe's continuous, micro-batch loading process, allowing for efficient and timely data ingestion without overwhelming the system with files that are too large or too small.
Reference:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Snowpipe1
NEW QUESTION # 433
Which function, when combined with an INSERT statement, will insert semi-structured data into a VARIANT column?
Answer: A
Explanation:
The correct answer is C. PARSE_JSON .
PARSE_JSON parses a valid JSON-formatted string and returns a VARIANT value. This is commonly used when inserting semi-structured JSON data into a VARIANT column.
Why C is correct:
A VARIANT column can store semi-structured data such as JSON objects and arrays. When the source value is a JSON string, PARSE_JSON converts it into a Snowflake VARIANT.
Example:
CREATE TABLE json_table (
src VARIANT
);
INSERT INTO json_table
SELECT PARSE_JSON( ' { " customer_id " : 101, " region " : " WEST " } ' ); Why the other options are incorrect:
A). TO_JSON converts a VARIANT value into a JSON string. It is commonly used in the opposite direction.
B). TO_VARCHAR converts a value to a string, not to a semi-structured VARIANT.
D). OBJECT_INSERT inserts or updates a key-value pair inside an existing object, but it is not the primary function used to parse JSON text into a VARIANT column.
Official Snowflake documentation reference:
Snowflake documentation describes PARSE_JSON as a function that interprets an input string as JSON and returns a VARIANT value.
Reference: Snowflake Documentation - PARSE_JSON; Snowflake Documentation - Semi-structured data types; SnowPro Core Study Guide - Working with Semi-Structured Data.
NEW QUESTION # 434
Which table function is used to perform additional processing on the results of a previously-run query?
Answer: B
Explanation:
TheRESULT_SCANtable function is used in Snowflake to perform additional processing on the results of a previously-run query. It allows users to reference the result set of a previous query by its query ID, enabling further analysis or transformations without re-executing the original query.
References:
* Snowflake Documentation: RESULT_SCAN
NEW QUESTION # 435
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