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[Hardware] DEA-C02考古題介紹 &新版DEA-C02題庫

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【Hardware】 DEA-C02考古題介紹 &新版DEA-C02題庫

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最新的 SnowPro Advanced DEA-C02 免費考試真題 (Q303-Q308):問題 #303
A Snowflake data engineer is troubleshooting a slow-running query that joins two large tables, 'ORDERS' (1 billion rows) and 'CUSTOMER' (10 million rows), using the 'CUSTOMER ID' column. The query execution plan shows a significant amount of data spilling to local disk. The query is as follows:

Which of the following are the MOST likely root causes of the disk spilling and the best corresponding solutions? Select two options that directly address the disk spilling issue.
  • A. The virtual warehouse is undersized for the amount of data being processed. Increase the virtual warehouse size to provide more memory.
  • B. The 'CUSTOMER_ID column is not properly clustered in either the 'ORDERS' or 'CUSTOMER table. Define a clustering key on 'CUSTOMER_ID for both tables.
  • C. The query is performing a full table scan on the 'ORDERS' table. Add an index on the 'CUSTOMER ID column in the 'ORDERS table.
  • D. The join operation is resulting in a large intermediate result set that exceeds the available memory. Apply a filter on the 'ORDERS' table to reduce the data volume before the join.
  • E. The statistics on the tables are outdated. Run 'ANALYZE TABLE ORDERS' and 'ANALYZE TABLE CUSTOMER to update the statistics.
答案：A,D
解題說明：
Options A and D are the most direct solutions for disk spilling. A undersized warehouse directly impacts available memory, leading to disk spilling. Increasing the warehouse size (option A) provides more memory for the operation. When data spill happens increasing the warehouse size is the primary action to take. Option D correctly addresses the root cause of the spill an overly large intermediate result set. Reducing the data volume before the join minimizes the memory required. Option B could improve query performance overall, but doesn't directly address disk spilling. Option C is incorrect, as Snowflake does not support manual indexes. Option E would improve the accuracy of the query optimizer's decisions, which could indirectly improve performance, but is less direct than options A and D.

問題 #304
A financial institution needs to implement both dynamic data masking and column-level security on the 'CUSTOMER DATA table, which contains sensitive information like 'CREDIT CARD NUMBER and 'SSN'. The requirement is: all users except those in the 'DATA ADMIN' role should see masked credit card numbers (last 4 digits unmasked) and masked SSNs. Users in 'DATA ADMIN' should see the original data'. Which of the following combination of policies and grants will achieve this?
  • A. Create two masking policies: one for 'CREDIT CARD NUMBER' and another for 'SSN'. Grant APPLY MASKING POLICY privilege to the 'DATA ADMIN' role and then apply masking policies to the appropriate columns. Grant SELECT privilege on the table to PUBLIC.
  • B. Create two masking policies: one for 'CREDIT CARD NUMBER' and another for 'SSN'. Grant APPLY MASKING POLICY privilege to the 'DATA ADMIN' role. Apply masking policies to the appropriate columns. Grant SELECT privilege on the table to PUBLI
  • C. Create two masking policies: one for 'CREDIT CARD NUMBER' and another for 'SSN'. Grant APPLY MASKING POLICY privilege to the 'DATA ADMIN' role. Do not grant any SELECT privileges on the table.
  • D. Create two masking policies: one for 'CREDIT CARD NUMBER and another for 'SSN' using the 'CASE' statement to apply masking logic based on the current_role(). Apply masking policies to the appropriate columns. Grant SELECT privilege on the table to PUBLIC.
  • E. Create two masking policies: one for 'CREDIT CARD NUMBER and another for 'SSN'. Apply masking policies to the appropriate columns. Create a custom role with the 'APPLY MASKING POLICY privilege, grant this custom role to the 'DATA_ADMIN' role. Grant SELECT privilege on the table to PUBLIC.
答案：D
解題說明：
Option E correctly implements both dynamic data masking and column-level security. The 'CASE statement within the masking policy allows for different masking logic based on the current role. Granting SELECT to PUBLIC allows all users access to the table, while the masking policy controls what they see. Options A, B, C and D fails to implement either correct masking logic within policies or proper grant structure.

問題 #305
Consider a table with columns and 'customer _ region'. You want to implement both a Row Access Policy (RAP) and an Aggregation Policy on this table. The RAP should restrict access to orders based on the user's region, defined in a session variable 'CURRENT REGION'. Users should only see orders from their region. The Aggregation Policy should mask order totals for regions other than the user's region when aggregating data'. In other words if someone attempts to aggregate ALL region's totals, the aggregation will only include their region. Which statements about implementing this scenario are true?
  • A. The Aggregation Policy is evaluated before the RAP, ensuring that even if users try to bypass the RAP by aggregating across all regions, the results will be masked appropriately according to 'CURRENT REGION'.
  • B. The RAP should be applied first to filter the data, and then the Aggregation Policy will apply to the filtered data, only masking aggregated values within the user's region.
  • C. You cannot use session variables directly in Row Access Policies; you must pass the session variable as an argument to a user-defined function (UDF) called by the policy.
  • D. You can use the function within both the RAP and Aggregation Policy to control access based on user roles in addition to region.
  • E. Using external functions in RAPs can introduce performance overhead, especially if the external function is complex or slow to execute.
答案：D,E
解題說明：
Option C is correct. ' IS ROLE IN can be used in both policy types for role-based access control. Option D is correct because using external functions can lead to performance problems. Option A is incorrect because the Aggregation Policy's main purpose here is to mask data, so it isn't for filtering the data, it operates based on the results of the RAP. Option B is incorrect as RAP policy applies before AGGREGATION policy. Option E is partially incorrect; session variables are referenced as CURRENT_REGION, CURRENT_USER and no UDF is needed.

問題 #306
You are developing a Secure UDF in Snowflake to encrypt sensitive customer data'. The UDF should only be accessible by authorized roles. Which of the following steps are essential to properly secure the UDF?
  • A. Setting the 'SECURITY INVOKER clause when creating the UDF to execute the UDF with the privileges of the caller.
  • B. Ensuring that the UDF is owned by a role with appropriate permissions and limiting access to this role.
  • C. Using the 'SECURE keyword when creating the UDF to prevent viewing the UDF definition.
  • D. Using masking policies instead of Secure UDFs is the recommended approach for data security
  • E. Granting the EXECUTE privilege on the UDF only to the roles that require access.
答案：B,C,E
解題說明：
Secure UDFs protect the code definition. Granting EXECUTE privilege controls access to the UDE Ownership control is critical for managing permissions. SECURITY INVOKER, when used inappropriately can lead to security breaches if not properly managed and it executes with the privileges of the caller, potentially bypassing intended access restrictions. Masking policies are useful, but don't cover the core security functionality of secure UDFs, which hide the function's code itself.

問題 #307
You are tasked with optimizing a data pipeline that loads data from an external cloud storage location into Snowflake, transforms it, and then loads it into reporting tables. The pipeline is experiencing intermittent performance issues. You want to proactively identify and address these issues. Which of the following monitoring techniques and Snowflake features would be MOST effective for continuous monitoring and performance optimization?
  • A. Implement custom logging and monitoring using Snowflake Scripting and User-Defined Functions (UDFs) to capture granular performance metrics at each stage of the pipeline and push notifications via external functions to a monitoring service.
  • B. Enable Snowflake's Auto-Suspend and Auto-Resume features on the warehouse. This is the most efficient way to manage resources and optimize costs, indirectly addressing performance concerns.
  • C. Utilize Snowflake's System Functions to periodically query performance views (e.g., 'QUERY_HISTORY, ' and write aggregated metrics to a dedicated monitoring table. Configure a scheduled task to generate alerts based on predefined thresholds.
  • D. Rely solely on Snowflake's default query history and resource monitors. These automatically track performance and usage, providing sufficient insight without additional configuration.
  • E. Focus exclusively on optimizing SQL queries and data transformations. Monitoring is unnecessary since Snowflake automatically handles performance optimization.
答案：A,C
解題說明：
Options B and C provide the most effective methods for continuous monitoring and performance optimization. Option B allows for highly customized and granular monitoring of the entire pipeline, enabling proactive issue identification through external notifications. Option C leverages Snowflake's built-in system functions and task scheduling to create a robust monitoring and alerting system. Option A is insufficient as default monitoring may not provide the granularity needed. Option D is incorrect because monitoring is crucial. Option E primarily focuses on cost optimization, not performance monitoring.

問題 #308
......
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