Snowflake COF-C02 Practice Test - Questions Answers, Page 68

The Query Profile in Snowflake provides detailed insights into the execution of a query. It helps in troubleshooting performance issues by showing the steps of the query execution and the resources consumed. One of the key aspects it reveals is whether the virtual warehouse memory was sufficient for the query.

Access Query Profile: Navigate to the Query History page and select the query you want to analyze.

Examine Query Execution Steps: The Query Profile displays the different stages of the query execution, including the time taken and resources used at each step.

Identify Memory Issues: Look for indicators of memory issues, such as spilling to disk or memory errors, which suggest that the virtual warehouse memory might be too small.

References:

Snowflake Documentation: Query Profile

Snowflake Documentation: Optimizing Queries

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

Snowflake recommends not exposing sequence-generated columns in secure views. Secure views are used to protect sensitive data by ensuring that users can only access data for which they have permissions. Exposing sequence-generated columns can potentially reveal information about the underlying data structure or the number of rows, which might be sensitive.

Create Secure Views: Define secure views using the SECURE keyword to ensure they comply with Snowflake's security policies.

Exclude Sensitive Columns: When creating secure views, exclude columns that might expose sensitive information, such as sequence-generated columns.

CREATE SECURE VIEW secure_view AS

SELECT col1, col2

FROM sensitive_table

WHERE sensitive_column IS NOT NULL;

References:

Snowflake Documentation: Secure Views

Snowflake Documentation: Creating Secure Views

These answers and explanations should provide comprehensive guidance on the specified Snowflake topics.

Snowflake's Data Exchange allows users to create and manage a group of accounts to which they can offer data shares. This platform facilitates secure and governed data sharing within and between organizations.

Data Exchange Setup: Users can set up a Data Exchange and invite other Snowflake accounts to join.

Sharing Data: Within the Data Exchange, users can offer shares to the entire group or to specific accounts.

Governance and Security: Data Exchange provides tools for data governance and security, ensuring that shared data is only accessible to authorized accounts.

References:

Snowflake Documentation: Snowflake Data Exchange

Snowflake Documentation: Managing a Data Exchange

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

To change a Standard virtual warehouse to a Snowpark-optimized virtual warehouse, the warehouse must be in a suspended state. This ensures that no operations are disrupted during the modification process.

Suspend the Warehouse: Ensure that the warehouse is suspended.

ALTER WAREHOUSE my_warehouse SUSPEND;

Alter the Warehouse: Modify the warehouse to be Snowpark-optimized.

ALTER WAREHOUSE my_warehouse SET WAREHOUSE_TYPE = 'SNOWPARK-OPTIMIZED';

Resume the Warehouse: Resume the warehouse to make it operational.

ALTER WAREHOUSE my_warehouse RESUME;

References:

Snowflake Documentation: Creating Snowpark-Optimized Warehouses

Snowflake Documentation: ALTER WAREHOUSE

Snowpipe uses key-based authentication for its REST endpoints. This involves generating and using a key pair (public and private keys) to securely authenticate API requests.

Generate Key Pair: Generate a public and private key pair.

Register Public Key: Register the public key with the Snowflake user that will be making the API requests.

Authenticate Requests: Use the private key to sign API requests sent to Snowpipe REST endpoints.

References:

Snowflake Documentation: Key Pair Authentication & Key Rotation

Snowflake Documentation: Using Snowpipe REST API

In Snowflake streams, the METADATASACTION column indicates the type of data manipulation operation that has occurred. The possible values include INSERT and DELETE.

INSERT: Indicates that a new row has been inserted into the table.

DELETE: Indicates that a row has been deleted from the table.

References:

Snowflake Documentation: Change Data Capture (CDC) with Streams

Snowflake Documentation: Stream Data Capture