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Snowflake SnowPro Core SnowPro Core Dumps in PDF

Free Snowflake SnowPro Core Real Questions (page: 24)

SnowPro Core PDF — 1300 Questions

Assume there is a table consisting of five micro-partitions with values ranging from A to Z.
Which diagram indicates a well-clustered table?





Answer(s): A



What feature can be used to reorganize a very large table on one or more columns?

  1. Micro-partitions
  2. Clustering keys
  3. Key partitions
  4. Clustered partitions

Answer(s): B



What is an advantage of using an explain plan instead of the query profiler to evaluate the performance of a query?

  1. The explain plan output is available graphically.
  2. An explain plan can be used to conduct performance analysis without executing a query.
  3. An explain plan will handle queries with temporary tables and the query profiler will not.
  4. An explain plan's output will display automatic data skew optimization information.

Answer(s): B



Which data types are supported by Snowflake when using semi-structured data? (Choose two.)

  1. VARIANT
  2. VARRAY
  3. STRUCT
  4. ARRAY
  5. QUEUE

Answer(s): A,D



Why does Snowflake recommend file sizes of 100-250 MB compressed when loading data?

  1. Optimizes the virtual warehouse size and multi-cluster setting to economy mode
  2. Allows a user to import the files in a sequential order
  3. Increases the latency staging and accuracy when loading the data
  4. Allows optimization of parallel operations

Answer(s): D



Which of the following features are available with the Snowflake Enterprise edition? (Choose two.)

  1. Database replication and failover
  2. Automated index management
  3. Customer managed keys (Tri-secret secure)
  4. Extended time travel
  5. Native support for geospatial data

Answer(s): D,E



What is the default file size when unloading data from Snowflake using the COPY command?

  1. 5 MB
  2. 8 GB
  3. 16 MB
  4. 32 MB

Answer(s): C



What features that are part of the Continuous Data Protection (CDP) feature set in Snowflake do not require additional configuration? (Choose two.)

  1. Row level access policies
  2. Data masking policies
  3. Data encryption
  4. Time Travel
  5. External tokenization

Answer(s): C,D



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A
AI Tutor Explanation
9/24/2026 11:16:10 AM

Question 5:
Correct answer: A — True
Snowflake supports bulk unloading with COPY INTO <location> using a SELECT statement as the source. This allows you to export either:

  • All or selected columns from a table
  • Filtered rows using WHERE
  • Transformed or joined data

Example: 
sql 
COPY INTO @my_stage/export/ 
FROM ( 
  SELECT customer_id, order_date 
  FROM orders 
  WHERE order_date >= '2025-01-01' 
);
Snowflake writes the query results to files in the specified internal or external stage. The key distinction is that COPY INTO is used for bulk movement of data, while a regular SELECT only returns query results and does not unload them to staged files.

Pune, India
A
AI Tutor Explanation
9/3/2026 5:25:59 AM

Question 1:
Correct answer: B — Clustering keys
Snowflake automatically organizes table data into micro-partitions and uses natural clustering based on how data is loaded. However, for large tables where query performance depends on particular columns, you can define a clustering key.
A clustering key:

  • Specifies one or more columns or expressions Snowflake should use when organizing table data.
  • Helps Snowflake’s automatic reclustering keep related rows grouped together.
  • Can improve pruning for queries that frequently filter or join on those columns.

Why the others are incorrect:
  • Micro-partitions: Snowflake’s storage units; users do not directly define them as an override mechanism.
  • Key partitions: Not a Snowflake feature.
  • Clustered partitions: Not the name of the customer-defined mechanism.

The answer key’s B is correct.

Johannesburg, South Africa
A
AI Tutor Explanation
8/28/2026 11:39:56 AM

Question 17:
Correct answer: D — To accommodate a more complex workload.
Increasing a Virtual Warehouse from X-Small to Medium is vertical scaling. The larger warehouse provides more compute resources, which can improve performance for:

  • Complex queries
  • Large scans or joins
  • Resource-intensive transformations
  • Queries involving substantial processing

Why the others are less appropriate:
  • More users / more queries: This usually calls for multi-cluster warehouses, which add clusters to handle concurrency.
  • Fluctuations in workload: This is typically addressed with auto-suspend/auto-resume or multi-cluster scaling, rather than simply choosing a larger warehouse.

Thus, warehouse size primarily affects the compute power available to individual workloads.

Chennai, India
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