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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Snowflake Architecture & Core Concepts | 31% | - Cloud Services Layer, Compute Layer, Storage Layer - Snowsight Interface, Core Platform Features - Databases, Schemas, Objects, Data Types - Virtual Warehouses, Clustering, Caching |
| Topic 2: Data Loading, Unloading & Connectivity | 18% | - Stages, File Formats, COPY INTO, Snowpipe - External Integrations, Connectors, SnowSQL - Unloading Data, Export Options - Bulk Load, Streaming, Dynamic Tables |
| Topic 3: Account Management & Data Governance | 20% | - Access Control: RBAC, DAC, Roles, Privileges - Security: Network Policies, MFA, Encryption - Governance: Resource Monitors, Data Masking, Row/Column Security - Trust Center, Data Lineage, Compliance |
| Topic 4: Data Collaboration & Protection | 10% | - Secure Data Sharing, Listings, Marketplace - Data Protection, Retention, Time Travel, Fail-safe - Data Clean Rooms, Collaboration Features |
| Topic 5: Performance Optimization, Querying & Transformation | 21% | - SQL Transformations, Semi-structured/Unstructured Data - Materialized Views, Streams, Tasks, Pipelines - Query Processing, Profiling, Optimization - Cortex AI, Notebooks, Apache Iceberg Tables |
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NEW QUESTION # 380
How can a relational table be unloaded into a JSON file?
Answer: B
Explanation:
The correct answer is A. Use the OBJECT_CONSTRUCT function with the COPY INTO < location > command .
When unloading relational data to JSON, each relational row must be transformed into a single semi- structured object. OBJECT_CONSTRUCT creates a JSON-style object from the row's columns, and COPY INTO < location > unloads the result to a stage.
Why A is correct:
Snowflake requires unloaded JSON data to be represented as a single VARIANT, OBJECT, or ARRAY value per row. OBJECT_CONSTRUCT converts relational columns into an object suitable for JSON unload.
Example:
COPY INTO @my_stage/output/
FROM (
SELECT OBJECT_CONSTRUCT(*)
FROM customers
)
FILE_FORMAT = (TYPE = JSON);
Why the other options are incorrect:
B). Setting the file format to JSON alone is not sufficient for relational rows with multiple columns. The rows must be converted into a single semi-structured column.
C). PUT uploads local files to an internal stage. It does not unload table data.
D). GET downloads files from an internal stage to a local machine. It does not unload table data from Snowflake.
Official Snowflake documentation reference:
Snowflake documentation explains that to unload relational data to JSON, the query should return a single column containing semi-structured data, commonly produced with OBJECT_CONSTRUCT.
Reference: Snowflake Documentation - Unloading relational data to JSON; Snowflake Documentation - OBJECT_CONSTRUCT; Snowflake Documentation - COPY INTO < location > ; SnowPro Core Study Guide - Data Loading and Unloading.
NEW QUESTION # 381
While preparing to unload data in Snowflake, the file format option can be specified in which commands?
(Select TWO).
Answer: A,D
Explanation:
Thefile formatoption in Snowflake can be specified in the following commands:
CREATE STAGE: This command allows users to define the file format when creating a stage, which applies to any data loaded or unloaded via that stage.
COPY INTO < location > : This command enables data export from a table to an external location, where the file format can be specified to ensure the data is structured as needed for downstream systems.
Other commands, such as PUT or GET, do not support the specification of file formats directly within the command syntax.
NEW QUESTION # 382
Which stream type can be used for tracking the records in external tables?
Answer: B
Explanation:
The stream type that can be used for tracking the records in external tables is 'External'.This type of stream is specifically designed to track changes in external tables
NEW QUESTION # 383
What operations can be performed while loading a simple CSV file into a Snowflake table using the COPY INTO command? (Select TWO).
Answer: D,E
Explanation:
When loading a simple CSV file into a Snowflake table using the COPY INTO command, you can perform various transformations and adjustments on the data as part of the loading process. Specifically, you can:
B . Reorder the columns: Specify the order of columns in the COPY INTO command to match the structure of the target table if it differs from the order of columns in the source CSV file.
D . Convert the datatypes: Explicitly convert the datatypes of the data being loaded to match the datatypes of the columns in the target table. This can be necessary when the source data's format does not match the target table's expected datatype.
References:
Snowflake Documentation: Using the COPY INTO Command for Data Loading
NEW QUESTION # 384
What is cached during a query on a virtual warehouse?
Answer: B
Explanation:
During a query on a virtual warehouse, the columns in the result set of the query are cached. This allows for faster retrieval of data if the same or a similar query is run again, as the system can retrieve the data from the cache rather than reprocessing the entire query. References: [COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 385
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