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| Certification Vendor: | Snowflake |
|---|---|
| Exam Name: | SnowPro® Core Certification Exam |
| Exam Number: | COF-C02 |
| Certificate Validity Period: | 2 years |
| Related Certifications: | SnowPro Core Recertification (COF-R02) SnowPro Advanced: Architect SnowPro Advanced: Data Engineer |
| Exam Format: | Multiple choice, Multiple select |
| Passing Score: | 750 (scale 0–1000) |
| Exam Duration: | 115 minutes |
| Exam Price: | 175 USD |
| Available Languages: | Spanish, English |
| Real Exam Qty: | 100 |
| Recommended Training: | Snowflake Official Learning Paths Snowflake Documentation & Tutorials |
| Exam Registration: | Official Registration Pearson VUE Registration |
| Sample Questions: | Snowflake COF-C02 Sample Questions |
| Exam Way: | Online proctored or in-person at Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; 6+ months hands-on experience with Snowflake strongly recommended |
| Official Syllabus URL: | https://learn.snowflake.com/en/certifications/snowpro-core/ |
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Snowflake COF-C02 exam is vendor-agnostic and focuses on the core concepts of data warehousing, data processing, and data analysis. COF-C02 exam covers a wide range of topics, including Snowflake architecture, data loading, data unloading, data modeling, and data querying. SnowPro Core Certification Exam certification exam consists of 90 multiple-choice questions and has a time limit of 2 hours. COF-C02 Exam is proctored and can be taken remotely.
NEW QUESTION # 1001
A JSON document is stored in the source_colum of type VARIANT. The document has an array called elements. The array contains the name key that has a string value How can a Snowflake user extract the name from the first element?
Answer: D
Explanation:
In Snowflake, when dealing with semi-structured data such as a JSON document stored in a VARIANT column, the proper syntax to extract a value is to use the column name followed by the path to the specific element. Since arrays in JSON are zero-indexed, the first element is referenced with [0]. Therefore, to extract the name from the first element of the elements array, the correct syntax is Source_column:elements[0].name.
Reference: Snowflake Documentation on Semi-Structured Data
NEW QUESTION # 1002
Which Snowflake data type is used to store JSON key value pairs?
Answer: A
Explanation:
The VARIANT data type in Snowflake is used to store JSON key-value pairs along with other semi-structured data formats like AVRO, BSON, and XML. The VARIANT data type allows for flexible and dynamic data structures within a single column, accommodating complex and nested data. This data type is crucial for handling semi-structured data in Snowflake, enabling users to perform SQL operations on JSON objects and arrays directly.
Reference:
Snowflake Documentation: Semi-structured Data Types
NEW QUESTION # 1003
Taking which step will minimize the number of queries waiting to run on a virtual warehouse?
Answer: D
Explanation:
The correct answer is D. Increase the value of the MAX_CLUSTER_COUNT .
Queries wait in a queue when a warehouse does not have enough available compute capacity to handle the current concurrency. For a multi-cluster warehouse, increasing MAX_CLUSTER_COUNT allows Snowflake to start more clusters when concurrency increases.
Why D is correct:
Increasing MAX_CLUSTER_COUNT allows a multi-cluster warehouse in Auto-scale mode to add more clusters, up to the configured maximum. This helps reduce query queuing for concurrent workloads.
Why the other options are incorrect:
A). Increasing WAREHOUSE_SIZE gives each cluster more compute power, which can help individual queries run faster, but it is not the best direct solution for reducing queued concurrent queries.
B). Increasing AUTO_SUSPEND keeps the warehouse running longer but does not increase concurrency capacity.
C). WAIT_FOR_COMPLETION = FALSE is used with warehouse resize behavior and does not reduce query queuing.
Official Snowflake documentation reference:
Snowflake documentation explains that multi-cluster warehouses improve concurrency by starting additional clusters as query demand increases. The MAX_CLUSTER_COUNT property defines the maximum number of clusters that can run.
Reference: Snowflake Documentation - Multi-cluster warehouses; Snowflake Documentation - Warehouse properties; SnowPro Core Study Guide - Snowflake Account and Resource Management.
NEW QUESTION # 1004
A clustering key was defined on a table, but It is no longer needed. How can the key be removed?
Answer: A
Explanation:
To remove a clustering key that was previously defined on a table in Snowflake, the correct SQL command is ALTER TABLE <TABLE NAME> DROP CLUSTERING KEY. This command removes the existing clustering key from the table, after which Snowflake will no longer re-cluster data based on that key during maintenance operations or after data loading operations.
Reference: Snowflake Documentation on altering tables, specifically the section on modifying clustering keys:
https://docs.snowflake.com/en/sql-reference/sql/alter-table.html#modifying-clustering-keys
NEW QUESTION # 1005
What common query issues can be identified using the Query Profile? (Select TWO)
Answer: D,E
NEW QUESTION # 1006
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