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NEW QUESTION # 259
Which commands should be used to grant the privilege allowing a role to select data from all current tables and any tables that will be created later in a schema? (Choose two.)
- A. grant SELECT on all tables in database DB1 to role MYROLE;
- B. grant SELECT on future tables in database DB1 to role MYROLE;
- C. grant USAGE on future tables in schema DB1.SCHEMA to role MYROLE;
- D. grant SELECT on future tables in schema DB1.SCHEMA to role MYROLE;
- E. grant USAGE on all tables in schema DB1.SCHEMA to role MYROLE;
- F. grant SELECT on all tables in schema DB1.SCHEMA to role MYROLE;
Answer: D,F
Explanation:
To grant a role the privilege to select data from all current and future tables in a schema, two separate commands are needed.The first command grants the SELECT privilege on all existing tables within the schema, and the second command grants the SELECT privilege on all tables that will be created in the future within the same schema.
NEW QUESTION # 260
When do Snowflake object owners lose their ability to make grant decisions?
- A. When the object owner has been granted a database role
- B. When the object is part of a managed access schema
- C. When the object is part of a regular schema
- D. When the object owner has been granted an account role
Answer: B
NEW QUESTION # 261
Which Snowflake data governance feature can support auditing when a user query reads column data?
- A. Column-level security
- B. Access History
- C. Object dependencies
- D. Data classification
Answer: B
Explanation:
Access History in Snowflake is a feature designed to support auditing by tracking access to data within Snowflake, including when a user's query reads column data. It provides detailed information on queries executed, including the user who ran the query, the query text, and the objects (e.g., tables, views) accessed by the query. This feature is instrumental for auditing purposes, helping organizations to monitor and audit data access for security and compliance.
NEW QUESTION # 262
What happens when a cloned table is replicated to a secondary database? (Select TWO)
- A. Additional costs for storage are charged to a secondary account
- B. A read-only copy of the cloned tables is stored.
- C. The replication will not be successful.
- D. Metadata pointers to cloned tables are replicated
- E. The physical data is replicated
Answer: D,E
Explanation:
When a cloned table is replicated to a secondary database in Snowflake, the following occurs:
C . The physical data is replicated: The actual data of the cloned table is physically replicated to the secondary database.This ensures that the secondary database has its own copy of the data, which can be used for read-only purposes or failover scenarios1.
E . Metadata pointers to cloned tables are replicated: Along with the physical data, the metadata pointers that refer to the cloned tables are also replicated.This metadata includes information about the structure of the table and any associated properties2.
It's important to note that while the physical data and metadata are replicated, the secondary database is typically read-only and cannot be used for write operations. Additionally, while there may be additional storage costs associated with the secondary account, this is not a direct result of the replication process but rather a consequence of storing additional data.
References:
SnowPro Core Exam Prep - Answers to Snowflake's LEVEL UP: Backup and Recovery Snowflake SnowPro Core Certification Exam Questions Set 10
NEW QUESTION # 263
A Snowflake account administrator has set the resource monitors as shown in the diagram, with actions defined for each resource monitor as "Notify & Suspend Immediately".
What is the MAXIMUM limit of credits that Warehouse 2 can consume?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
Explanation:
In the provided exhibit, Warehouse 2 is under Resource Monitor 2, which has a credit quota of 1000 credits. However, it's important to note that warehouses can also draw from the account-level resource monitor if they consume their dedicated monitor's quota. In this exhibit, Resource Monitor 1 is set for the account with a credit quota of 500 credits.
The exhibit does not clearly show whether Warehouse 2 is also subject to the account-level Resource Monitor 1, but if we assume the typical case where all warehouses can draw from the account-level monitor, the maximum limit of credits Warehouse 2 can consume would be the sum of its dedicated resource monitor (Resource Monitor 2) and the account-level resource monitor (Resource Monitor 1).
Thus, Warehouse 2 can consume:
1000 credits from Resource Monitor 2
500 credits from Resource Monitor 1 (if applicable)
This gives a total of 1500 credits. Therefore, the maximum credit limit that Warehouse 2 can consume, taking into account the possibility of the account-level monitor's contribution, would be 1500 credits.
However, without explicit confirmation that Warehouse 2 can use credits from Resource Monitor 1, one would default to the specific resource monitor assigned to the warehouse, which is 1000 credits. Given the available options, the closest and most accurate answer is B. 1500, as it represents the sum of credits from both monitors that potentially apply to Warehouse 2.
References:
Snowflake Documentation on Resource Monitors: Managing Resource Monitors
NEW QUESTION # 264
A user has semi-structured data to load into Snowflake but is not sure what types of operations will need to be performed on the dat a. Based on this situation, what type of column does Snowflake recommend be used?
- A. ARRAY
- B. OBJECT
- C. VARIANT
- D. TEXT
Answer: C
Explanation:
When dealing with semi-structured data in Snowflake, and the specific types of operations to be performed on the data are not yet determined, Snowflake recommends using the VARIANT data type. The VARIANT type is highly flexible and capable of storing data in multiple formats, including JSON, AVRO, BSON, and more, within a single column. This flexibility allows users to perform various operations on the data, including querying and manipulation of nested data structures without predefined schemas.
References:
Snowflake Documentation: Semi-structured Data Types
NEW QUESTION # 265
Which data sharing option allows a Snowflake user to set up and manage a group of accounts and offer a share to that group?
- A. Direct share
- B. Data Exchange
- C. Free listing
- D. Paid listing
Answer: A
Explanation:
Snowsight, the Snowflake user interface, supports a variety of chart types for data visualization, including line charts and pie charts. These chart types help users analyze and interpret data more effectively.
Line Charts: Useful for showing trends over time or comparing different data sets.
Pie Charts: Ideal for displaying proportions and percentages within a dataset.
References:
Snowflake Documentation: Visualizing Data with Snowsight
Snowflake Documentation: Chart Types
NEW QUESTION # 266
The bulk data load history that is available upon completion of the COPY statement is stored where and for how long?
- A. In the metadata of the target table for 64 days
- B. In the metadata of the pipe for 64 days
- C. In the metadata of the target table for 14 days
- D. In the metadata of the pipe for 14 days
Answer: B
Explanation:
The bulk data load history available after a COPY statement is stored in the metadata of the pipe and is retained for 64 days1.
NEW QUESTION # 267
A developer is granted ownership of a table that has a masking policy. The developer's role is not able to see the masked dat a. Will the developer be able to modify the table to read the masked data?
- A. Yes, because masking policies only apply to cloned tables.
- B. No, because masking policies must always reference specific access roles.
- C. Yes, because a table owner has full control and can unset masking policies.
- D. No, because ownership of a table does not include the ability to change masking policies
Answer: D
Explanation:
Even if a developer is granted ownership of a table with a masking policy, they will not be able to modify the table to read the masked data if their role does not have the necessary permissions. Ownership of a table does not automatically confer the ability to alter masking policies, which are designed to protect sensitive data.Masking policies are applied at the schema level and require specific privileges to modify12.
References:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Masking Policies
NEW QUESTION # 268
What Snowflake objects can contain custom application logic written in JavaScript? (Select TWO)
- A. User-Defined Functions (UDFs)
- B. Stages
- C. Tasks
- D. Views
- E. Stored procedures
Answer: A,E
Explanation:
Snowflake allows users to write custom application logic in JavaScript for two types of objects: Stored Procedures and User-Defined Functions (UDFs).
Stored Procedures: Snowflake stored procedures can be written in JavaScript to encapsulate complex business logic and procedural operations.
CREATE OR REPLACE PROCEDURE my_procedure()
RETURNS STRING
LANGUAGE JAVASCRIPT
EXECUTE AS CALLER
AS
$$
// JavaScript logic here
$$;
User-Defined Functions (UDFs): Snowflake UDFs can be written in JavaScript to perform custom calculations or operations on data.
CREATE OR REPLACE FUNCTION my_function(x FLOAT)
RETURNS FLOAT
LANGUAGE JAVASCRIPT
AS
$$
return x * 2;
$$;
References:
Snowflake Documentation: Stored Procedures
Snowflake Documentation: User-Defined Functions (UDFs)
NEW QUESTION # 269
What information is stored in the ACCESS_HlSTORY view?
- A. Query details such as the objects included and the user who executed the query
- B. Names and owners of the roles that are currently enabled in the session
- C. Details around the privileges that have been granted for all objects in an account
- D. History of the files that have been loaded into Snowflake
Answer: C
Explanation:
Details around the privileges that have been granted for all objects in an account. The ACCESS_HISTORY view in Snowflake provides a comprehensive log of access control changes, including grants and revocations of privileges on all securable objects within the account. This information is crucial for auditing and monitoring the security posture of your Snowflake environment.
Here's how to understand and use the ACCESS_HISTORY view:
Purpose of ACCESS_HISTORY View: It is designed to track changes in access controls, such as when a user or role is granted or revoked privileges on various Snowflake objects. This includes tables, schemas, databases, and more.
Querying ACCESS_HISTORY: To access this view, you can use the following SQL query pattern:
SELECT * FROM SNOWFLAKE.ACCOUNT_USAGE.ACCESS_HISTORY WHERE EVENT_TYPE = 'GRANT' OR EVENT_TYPE = 'REVOKE'; Interpreting the Results: The results from the ACCESS_HISTORY view include the object type, the specific privilege granted or revoked, the grantee (who received or lost the privilege), and the timestamp of the event. This data is invaluable for audits and compliance checks.
NEW QUESTION # 270
What happens to the underlying table data when a CLUSTER BY clause is added to a Snowflake table?
- A. Smaller micro-partitions are created for common data values to allow for more parallelism
- B. Larger micro-partitions are created for common data values to reduce the number of partitions that must be scanned
- C. Data may be colocated by the cluster key within the micro-partitions to improve pruning performance
- D. Data is hashed by the cluster key to facilitate fast searches for common data values
Answer: C
Explanation:
When a CLUSTER BY clause is added to a Snowflake table, it specifies one or more columns to organize the data within the table's micro-partitions. This clustering aims to colocate data with similar values in the same or adjacent micro-partitions. By doing so, it enhances the efficiency of query pruning, where the Snowflake query optimizer can skip over irrelevant micro-partitions that do not contain the data relevant to the query, thereby improving performance.
References:
Snowflake Documentation on Clustering Keys & Clustered Tables1.
Community discussions on how source data's ordering affects a table with a cluster key
NEW QUESTION # 271
How should a Snowflake use' configure a virtual warehouse to be in Maximized mode''
- A. Set the same value for both MIN_CLUSTER_COUNT and MAX_CLUSTER_COUNT.
- B. Set the WAREHOUSES_SIZE to 6XL.
- C. Set the MAX_CONCURRENCY_LEVEL to a value of 12 or large.
- D. Set the STATEMENT_TIMEOUT_1M_SECOMES to 0.
Answer: A
Explanation:
In Snowflake, configuring a virtual warehouse to be in a "Maximized" mode implies maximizing the resources allocated to the warehouse for its duration. This is done to ensure that the warehouse has a consistent amount of compute resources available, enhancing performance for workloads that require a high level of parallel processing or for handling high query volumes.
To configure a virtual warehouse in maximized mode, you should set the same value for both MIN_CLUSTER_COUNT and MAX_CLUSTER_COUNT. This configuration ensures that the warehouse operates with a fixed number of clusters, thereby providing a stable and maximized level of compute resources.
Reference to Snowflake documentation on warehouse sizing and scaling:
Warehouse Sizing and Scaling
Understanding Warehouses
NEW QUESTION # 272
Which security models are used in Snowflake to manage access control? (Select TWO).
- A. Role-Based Access Control (RBAC)
- B. Mandatory Access Control (MAC)
- C. Security Assertion Markup Language (SAML)
- D. Discretionary Access Control (DAC)
- E. Identity Access Management (1AM)
Answer: A,D
Explanation:
Snowflake uses both Discretionary Access Control (DAC) and Role-Based Access Control (RBAC) to manage access control. DAC allows object owners to grant access privileges to other users. RBAC assigns permissions to roles, and roles are then granted to users, making it easier to manage permissions based on user roles within the organization.
References:
Snowflake Documentation: Access Control in Snowflake
NEW QUESTION # 273
When unloading data, which file format preserves the data values for floating-point number columns?
- A. CSV
- B. Parquet
- C. JSON
- D. Avro
Answer: B
Explanation:
When unloading data, the Parquet file format is known for its efficiency in preserving the data values for floating-point number columns. Parquet is a columnar storage file format that offers high compression ratios and efficient data encoding schemes. It is especially effective for floating-point data, as it maintains high precision and supports efficient querying and analysis.
References:
Snowflake Documentation: Using the Parquet File Format for Unloading Data
NEW QUESTION # 274
What will happen if a Snowflake user increases the size of a suspended virtual warehouse?
- A. The warehouse will resume immediately and start to share the compute load with other running virtual warehouses.
- B. The provisioning of new compute resources for the warehouse will begin immediately.
- C. The warehouse will remain suspended but new resources will be added to the query acceleration service.
- D. The provisioning of additional compute resources will be in effect when the warehouse is next resumed.
Answer: D
Explanation:
When a Snowflake user increases the size of a suspended virtual warehouse, the changes to compute resources are queued but do not take immediate effect. The provisioning of additional compute resources occurs only when the warehouse is resumed. This ensures that resources are allocated efficiently, aligning with Snowflake's commitment to cost-effective and on-demand scalability.
References:
Snowflake Documentation: Virtual Warehouses
NEW QUESTION # 275
What are supported file formats for unloading data from Snowflake? (Choose three.)
- A. ORC
- B. AVRO
- C. JSON
- D. XML
- E. CSV
- F. Parquet
Answer: C,E,F
Explanation:
The supported file formats for unloading data from Snowflake include JSON, Parquet, and CSV.These formats are commonly used for their flexibility and compatibility with various data processing tools
NEW QUESTION # 276
Which Snowflake object does not consume any storage costs?
- A. Transient table
- B. Materialized view
- C. Secure view
- D. Temporary table
Answer: D
Explanation:
Temporary tables do not consume any storage costs in Snowflake because they only exist for the duration of the session that created them and are automatically dropped when the session ends, thus incurring no long-term storage charges4. References: [COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 277
What do the terms scale up and scale out refer to in Snowflake? (Choose two.)
- A. Scaling out adds additional database servers to an existing running cluster to handle more concurrent queries.
- B. Scaling up adds additional database servers to an existing running cluster to handle larger workloads.
- C. Scaling out adds clusters of the same size to a virtual warehouse to handle more concurrent queries.
- D. Scaling up resizes a virtual warehouse so it can handle more complex workloads.
- E. Scaling out adds clusters of varying sizes to a virtual warehouse.
- F. Snowflake recommends using both scaling up and scaling out to handle more concurrent queries.
Answer: C,D
Explanation:
Scaling out in Snowflake involves adding clusters of the same size to a virtual warehouse, which allows for handling more concurrent queries without affecting the performance of individual queries. Scaling up refers to resizing a virtual warehouse to increase its compute resources, enabling it to handle more complex workloads and larger queries more efficiently.
NEW QUESTION # 278
Which default warehouse configuration has the highest precedence whenever a new session is created by a user?
- A. Default warehouse specified on a CLI or in drivers/connectors parameters
- B. Default warehouse in the configuration file of the client utilities
- C. Default warehouse of the role assigned to the user
- D. Default warehouse tor the user
Answer: C
NEW QUESTION # 279
The following settings are configured:
THE MIN_DATA_RETENTION_TIME_IN_DAYS is set to 5 at the account level.THE DATA_RETENTION_TIME_IN_DAYS is set to 2 at the object level.
For how many days will the data be retained at the object level?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: A
Explanation:
The settings shown in the image indicate that the data retention time in days is configured at two different levels: the account level and the object level. At the account level, the MIN_DATA_RETENTION_TIME_IN_DAYS is set to 5 days, and at the object level, the DATA_RETENTION_TIME_IN_DAYS is set to 2 days. Since the object level setting has a lower value, it takes precedence over the account level setting for the specific object. Therefore, the data will be retained for 2 days at the object level.References: Snowflake Documentation on Data Retention Policies
NEW QUESTION # 280
Which of the following can be used when unloading data from Snowflake? (Choose two.)
- A. When unloading semi-structured data, it is recommended that the STRIP_OUTER_ARRAY option be used.
- B. By using the SINGLE = TRUE parameter, a single file up to 5 GB in size can be exported to the storage layer.
- C. Use the PARSE_JSON function to ensure structured data will be unloaded into the VARIANT data type.
- D. Use the ENCODING file format option to change the encoding from the default UTF-8.
- E. The OBJECT_CONSTRUCT function can be used to convert relational data to semi-structured data.
Answer: B,E
Explanation:
The OBJECT_CONSTRUCT function is used in Snowflake to create a JSON object from relational data, which is useful when unloading semi-structured data. The SINGLE = TRUE parameter is used when unloading data to ensure that the data is exported as a single file, which can be up to 5 GB in size. References: [COF-C02] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 281
Which data type can be used for floating-point numbers without losing precision?
- A. INTEGER
- B. BINARY
- C. DOUBLE
- D. VARIANT
Answer: C
Explanation:
In Snowflake, the DOUBLE data type is used for floating-point numbers and can represent a wide range of values without losing precision. This data type is ideal for storing numerical values that require decimal precision.
Define the Column: When creating a table, specify the column with the DOUBLE data type to store floating-point numbers.
CREATE TABLE example_table (
id INTEGER,
value DOUBLE
);
Insert Data: Insert floating-point numbers into the DOUBLE column.
INSERT INTO example_table (id, value) VALUES (1, 123.456);
References:
Snowflake Documentation: Data Types
Snowflake Documentation: Numeric Data Types
NEW QUESTION # 282
The property mins_to_bypass_network_policy is set at which level?
- A. User
- B. Account
- C. Organization
- D. Role
Answer: B
Explanation:
The property mins_to_bypass_network_policy is set at the account level in Snowflake. This setting allows administrators to specify a time frame during which users can bypass network policies that have been set on their account. It is particularly useful in scenarios where temporary access needs to be granted from IPs not covered by the existing network policies. By adjusting this property at the account level, Snowflake administrators can manage and enforce network access controls efficiently across the entire account.
References:
Snowflake Documentation on Network Policies: Network Policies
NEW QUESTION # 283
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