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| Section | Weight | Objectives |
|---|---|---|
| Data Loading, Unloading & Connectivity | 18% | - Unloading Data, Export Options - Stages, File Formats, COPY INTO, Snowpipe - Bulk Load, Streaming, Dynamic Tables - External Integrations, Connectors, SnowSQL |
| Data Collaboration & Protection | 10% | - Data Protection, Retention, Time Travel, Fail-safe - Data Clean Rooms, Collaboration Features - Secure Data Sharing, Listings, Marketplace |
| Snowflake Architecture & Core Concepts | 31% | - Snowsight Interface, Core Platform Features - Databases, Schemas, Objects, Data Types - Cloud Services Layer, Compute Layer, Storage Layer - Virtual Warehouses, Clustering, Caching |
| Account Management & Data Governance | 20% | - Governance: Resource Monitors, Data Masking, Row/Column Security - Trust Center, Data Lineage, Compliance - Access Control: RBAC, DAC, Roles, Privileges - Security: Network Policies, MFA, Encryption |
| Performance Optimization, Querying & Transformation | 21% | - Cortex AI, Notebooks, Apache Iceberg Tables - Materialized Views, Streams, Tasks, Pipelines - Query Processing, Profiling, Optimization - SQL Transformations, Semi-structured/Unstructured Data |
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NEW QUESTION # 212
What are valid sub-clauses to the OVER clause for a window function? (Select TWO).
Answer: B,D
Explanation:
Valid sub-clauses to theOVERclause for a window function in SQL are:
C). ORDER BY: This clause specifies the order in which the rows in a partition are processed by the window function. It is essential for functions that depend on the row order, such as ranking functions.
D). PARTITION BY: This clause divides the result set into partitions to which the window function is applied.
Each partition is processed independently of other partitions, making it crucial for functions that compute values across sets of rows that share common characteristics.
These clauses are fundamental to defining the scope and order of data over which the window function operates, enabling complex analytical computations within SQL queries.
References:
Snowflake Documentation: Window Functions
NEW QUESTION # 213
In Snowpipe, what is the default behavior of the ON_ERROR copy option?
Answer: D
Explanation:
The correct answer is B. SKIP_FILE .
Important correction:
The provided answer A. CONTINUE is not correct for Snowpipe.
For regular bulk loading with COPY INTO < table > , the default ON_ERROR behavior is commonly associated with ABORT_STATEMENT. However, Snowpipe has different behavior. In Snowpipe, the default ON_ERROR option is SKIP_FILE .
Why B is correct:
With ON_ERROR = SKIP_FILE, if Snowpipe encounters an error while loading a file, the file is skipped instead of causing the entire continuous loading process to fail.
Why the other options are incorrect:
A). CONTINUE continues loading and skips individual error rows, but it is not the default Snowpipe behavior.
C). SKIP_FILE_ < num > skips a file after a specified number of errors, but it is not the default.
D). ABORT_STATEMENT is associated with standard COPY INTO < table > behavior, not the default Snowpipe behavior.
Official Snowflake documentation reference:
Snowflake documentation for Snowpipe explains that the default ON_ERROR copy option for Snowpipe is SKIP_FILE.
Reference: Snowflake Documentation - Snowpipe; Snowflake Documentation - CREATE PIPE; Snowflake Documentation - COPY INTO < table > copy options; SnowPro Core Study Guide - Data Loading and Unloading.
==
NEW QUESTION # 214
What does the NULL_IF parameter do when loading CSV data into Snowflake?
Answer: C
Explanation:
NULL_IF identifies one or more source-file strings that Snowflake should interpret as SQL NULL while loading data. For example, a file format can define NULL_IF = ( ' NULL ' , ' NUL ' , ' \N ' , ' ' ).
When Snowflake encounters any specified value in the CSV input, it loads a SQL NULL into the corresponding target column. The parameter does not remove rows or values from the dataset, convert binary content, or automatically replace NULL values with empty strings. Snowflake applies the conversion to every occurrence of a configured value, regardless of whether that value visually resembles text or a number. When unloading data, NULL_IF works in the opposite direction by converting SQL NULL values into the first specified output string, but this question specifically concerns loading CSV data.
NEW QUESTION # 215
A user received a set of PDF files that are available on an external stage. Text, data, and layout elements need to be extracted from the files. Which Snowflake AI function should be used?
Answer: B
Explanation:
PARSE_DOCUMENT is used to extract information from documents, including text and layout elements. It is part of Snowflake Cortex document processing functionality.
Why the other options are incorrect:
TRANSCRIBE is for audio transcription, COMPLETE is for large language model completion, and EMBED generates vector embeddings.
Reference: Snowflake Documentation - Cortex PARSE_DOCUMENT; Document AI; Snowflake Cortex.
==
NEW QUESTION # 216
Which methods can be used to delete staged files from a Snowflake stage? (Choose two.)
Answer: B,D
Explanation:
To delete staged files from a Snowflake stage, you can specify the PURGE option in the COPY INTO <table>command, which will automatically delete the files after they have been successfully loaded.Additionally, you can use the REMOVEcommand after the load completes to manually delete the files from the stage12.
References =DROP STAGE,REMOVE
NEW QUESTION # 217
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