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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Accounts and Security | 25% | - Governance and Compliance
|
| Topic 2: Data Engineering | 25% | - Data Transformation
|
| Topic 3: Performance Optimization | 20% | - Query Performance
|
| Topic 4: Snowflake Architecture | 30% | - Platform Architecture Design
|
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NEW QUESTION # 141
Why does a conditional multi-table insert option support the Data Vault data model?
Answer: C
Explanation:
The Data Vault modeling approach separates data into hubs (business keys), links, and satellites, often requiring simultaneous insertion of related records derived from the same source dataset. Snowflake's conditional multi-table INSERT enables a single source query to populate multiple target tables in parallel based on conditional logic. This capability aligns well with Data Vault patterns, where hubs and satellites are typically loaded together from the same staging data.
By inserting into hubs and satellites in parallel using surrogate keys (Answer A), architects ensure consistency, atomicity, and efficient processing without re-scanning source data multiple times. This approach reduces compute usage and simplifies ETL logic, which is particularly valuable in large-scale, near-real-time ingestion pipelines.
Options involving dimensions and facts relate more closely to star schema modeling, not Data Vault.
Sequential insertion is also less efficient and not the defining advantage of conditional multi-table inserts. For SnowPro Architect candidates, this question emphasizes understanding how Snowflake SQL features support modern data modeling techniques such as Data Vault.
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NEW QUESTION # 142
Following objects can be cloned in snowflake
Answer: B,C,E
Explanation:
* Snowflake supports cloning of various objects, such as databases, schemas, tables, stages, file formats, sequences, streams, tasks, and roles. Cloning creates a copy of an existing object in the system without copying the data or metadata. Cloning is also known as zero-copy cloning1.
* Among the objects listed in the question, the following ones can be cloned in Snowflake:
* Permanent table: A permanent table is a type of table that has a Fail-safe period and a Time Travel retention period of up to 90 days. A permanent table can be cloned using the CREATE TABLE ... CLONE command2. Therefore, option A is correct.
* Transient table: A transient table is a type of table that does not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. A transient table can also be cloned using the CREATE TABLE ... CLONE command2. Therefore, option B is correct.
* External table: An external table is a type of table that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table can be cloned using the CREATE EXTERNAL TABLE ... CLONE command3.
Therefore, option D is correct.
* The following objects listed in the question cannot be cloned in Snowflake:
* Temporary table: A temporary table is a type of table that is automatically dropped when the session ends or the current user logs out. Temporary tables do not support cloning4. Therefore, option C is incorrect.
* Internal stage: An internal stage is a type of stage that is managed by Snowflake and stores files in Snowflake's internal cloud storage. Internal stages do not support cloning5. Therefore, option E is incorrect.
Cloning Considerations : CREATE TABLE ... CLONE : CREATE EXTERNAL TABLE ...
CLONE : Temporary Tables : Internal Stages
NEW QUESTION # 143
Which SQL ALTER command will MAXIMIZE memory and compute resources for a Snowpark stored procedure when executed on the snowpark_opt_wh warehouse?
Answer: C
Explanation:
Snowpark workloads are often memory- and compute-intensive, especially when executing complex transformations, large joins, or machine learning logic inside stored procedures. In Snowflake, the MAX_CONCURRENCY_LEVEL warehouse parameter controls how many concurrent queries can run on a single cluster of a virtual warehouse. Lowering concurrency increases the amount of compute and memory available to each individual query.
Setting MAX_CONCURRENCY_LEVEL = 1 ensures that only one query can execute at a time on the warehouse cluster, allowing that query to consume the maximum possible share of CPU, memory, and I/O resources. This is the recommended configuration when the goal is to optimize performance for a single Snowpark job rather than maximizing throughput for many users. Higher concurrency levels would divide resources across multiple queries, reducing per-query performance and potentially causing spilling to remote storage.
For SnowPro Architect candidates, this question reinforces an important cost and performance tradeoff:
concurrency tuning is a powerful lever. When running batch-oriented or compute-heavy Snowpark workloads, architects should favor lower concurrency to maximize per-query resources, even if that means fewer concurrent workloads.
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NEW QUESTION # 144
An Architect has a VPN_ACCESS_LOGS table in the SECURITY_LOGS schema containing timestamps of the connection and disconnection, username of the user, and summary statistics.
What should the Architect do to enable the Snowflake search optimization service on this table?
Answer: D
Explanation:
According to the SnowPro Advanced: Architect Exam Study Guide, to enable the search optimization service on a table, the user must have the ADD SEARCH OPTIMIZATION privilege on the table and the schema. The privilege can be granted explicitly or inherited from a higher-level object, such as a database or a role. The OWNERSHIP privilege on a table implies the ADD SEARCH OPTIMIZATION privilege, so the user who owns the table can enable the search optimization service on it. Therefore, the correct answer is to assume a role with OWNERSHIP on VPN_ACCESS_LOGS and ADD SEARCH OPTIMIZATION in the SECURITY_LOGS schema. This will allow the user to enable the search optimization service on the VPN_ACCESS_LOGS table and any future tables created in the SECURITY_LOGS schema. The other options are incorrect because they either grant excessive privileges or do not grant the required privileges on the table or the schema. Reference:
SnowPro Advanced: Architect Exam Study Guide, page 11, section 2.3.1
Snowflake Documentation: Enabling the Search Optimization Service
NEW QUESTION # 145
Which SQL alter command will MAXIMIZE memory and compute resources for a Snowpark stored procedure when executed on the snowpark_opt_wh warehouse?
Answer: D
Explanation:
To maximize memory and compute resources for a Snowpark stored procedure, you need to set the MAX_CONCURRENCY_LEVEL parameter for the warehouse that executes the stored procedure. This parameter determines the maximum number of concurrent queries that can run on a single warehouse. By setting it to 16, you ensure that the warehouse can use all the available CPU cores and memory on a single node, which is the optimal configuration for Snowpark-optimized warehouses. This will improve the performance and efficiency of the stored procedure, as it will not have to share resources with other queries or nodes. The other options are incorrect because they either do not change the MAX_CONCURRENCY_LEVEL parameter, or they set it to a lower value than 16, which will reduce the memory and compute resources for the stored procedure. Reference:
[Snowpark-optimized Warehouses] 1
[Training Machine Learning Models with Snowpark Python] 2
[Snowflake Shorts: Snowpark Optimized Warehouses] 3
NEW QUESTION # 146
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