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| Section | Weight | Objectives |
|---|---|---|
| Performance Optimization & Monitoring | 4% | - Query history and monitoring - Query profiling and performance tuning - Resource optimization techniques |
| Security & Access Control | 10% | - Governance best practices - Masking policies - Authentication (SSO, MFA) - Authorization (roles, privileges) - Row-level and column-level security |
| Virtual Warehouses | 15% | - Warehouse sizing and scaling - Warehouse monitoring and troubleshooting - Multi-cluster warehouses - Cache concepts (warehouse, result, metadata) - Warehouse creation and configuration |
| Account Objects | 8% | - Resource monitors - Warehouses, databases, and schemas hierarchy - Organizations and accounts structure |
| Cloud Platform Overview & Snowflake Key Concepts | 8% | - Virtual warehouse concepts and credit usage - Snowflake editions and features - Snowflake architecture layers (storage, compute, services) |
| Data Loading & Unloading | 15% | - File formats (JSON, CSV, Parquet, AVRO) - Bulk loading with COPY command - Data unloading and staging - Data ingestion best practices - Continuous loading with Snowpipe |
| Time Travel & Cloning | 10% | - Time travel concepts and retention - Fail-safe concepts - UNDROP and historical data access - Zero-copy cloning |
| Data Sharing | 12% | - Reader account management - Data listing marketplace - Private sharing vs. Data Exchange - Shares and reader accounts |
| Semi-Structured Data | 10% | - VARIANT data type - Array and object operations - Parsing and flattening semi-structured data |
| Databases, Tables & Views | 18% | - Table types (permanent, transient, temporary) - Data manipulation (DML operations) - Stored procedures and UDFs - Views (standard, materialized, secure) - Column types and sequences - Clustering and micro-partitions |
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NEW QUESTION # 498
What is the purpose of multi-cluster virtual warehouses?
Answer: C
Explanation:
Multi-cluster virtual warehouses in Snowflake are designed to manage user and query concurrency needs.They allow for the allocation of additional clusters of compute resources, either statically or dynamically, to handle increased loads and reduce or eliminate the queuing of concurrent queries2.
https://docs.snowflake.com/en/user-guide/warehouses-multicluster.html#:~:text=Multi%2Dcluster%20warehouses%20enable%20you,during%20peak%20and%20off%20hours.
NEW QUESTION # 499
In Snowflake, what allows users to perform recursive queries?
Answer: B
Explanation:
In Snowflake, theCONNECT BYclause allows users to perform recursive queries. Recursive queries are used to process hierarchical or tree-structured data, such as organizational charts or file systems. TheCONNECT BYclause is used in conjunction with theSTART WITHclause to specify the starting point of the hierarchy and the relationship between parent and child rows.
Snowflake Documentation: Hierarchical Queries
NEW QUESTION # 500
When unloading data from Snowflake using the COPY INTO < location > command, what is a key consideration for handling NULL values?
Answer: B
Explanation:
The correct answer is B. A string value should be specified to represent NULL values using the NULL_IF option .
When unloading data from Snowflake into files using the COPY INTO < location > command, Snowflake needs a textual representation for SQL NULL values in the unloaded files. This can be controlled by the NULL_IF file format option.
Why B is correct:
The NULL_IF option specifies one or more string values that represent SQL NULL values. During unloading, Snowflake uses this option to determine how NULL values should appear in the output files.
For example, a file format could specify:
NULL_IF = ( ' NULL ' )
This means SQL NULL values can be written using the string NULL in the unloaded file.
Why the other options are incorrect:
A). Snowflake does not always automatically convert NULL values to empty strings in all unload scenarios.
The representation depends on file format settings.
C). NULL values do not cause the unload process to stop with an error by default.
D). NULL values are not automatically skipped during unloading. They are included in the output using the configured representation.
Official Snowflake documentation reference:
Snowflake documentation for file format options explains that NULL_IF specifies the string used to represent SQL NULL values when loading or unloading data.
Reference: Snowflake Documentation - COPY INTO < location > command; Snowflake Documentation - File format options, NULL_IF; SnowPro Core Study Guide - Data Loading and Unloading.
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NEW QUESTION # 501
Which command is used to unload files from an internal or external stage to a local file system?
Answer: A
Explanation:
The command used to unload files from an internal or external stage to a local file system in Snowflake is the GET command.This command allows users to download data files that have been staged, making them available on the local file system for further use23.
NEW QUESTION # 502
What are value types that a VARIANT column can store? (Select TWO)
Answer: A,C
Explanation:
A VARIANT column in Snowflake can store semi-structured data types. This includes:
B . OBJECT: An object is a collection of key-value pairs in JSON, and a VARIANT column can store this type of data structure.
D . ARRAY: An array is an ordered list of zero or more values, which can be of any variant-supported data type, including objects or other arrays.
The VARIANT data type is specifically designed to handle semi-structured data like JSON, Avro, ORC, Parquet, or XML, allowing for the storage of nested and complex data structures.
References:
Snowflake Documentation on Semi-Structured Data Types
SnowPro Core Certification Study Guide
NEW QUESTION # 503
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