最新ARA-C01考證,ARA-C01資訊
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最新的 SnowPro Advanced Certification ARA-C01 免費考試真題 (Q46-Q51):
問題 #46
A company is using a Snowflake account in Azure. The account has SAML SSO set up using ADFS as a SCIM identity provider. To validate Private Link connectivity, an Architect performed the following steps:
* Confirmed Private Link URLs are working by logging in with a username/password account
* Verified DNS resolution by running nslookups against Private Link URLs
* Validated connectivity using SnowCD
* Disabled public access using a network policy set to use the company's IP address range However, the following error message is received when using SSO to log into the company account:
IP XX.XXX.XX.XX is not allowed to access snowflake. Contact your local security administrator.
What steps should the Architect take to resolve this error and ensure that the account is accessed using only Private Link? (Choose two.)
- A. Open a case with Snowflake Support to authorize the Private Link URLs' access to the account.
- B. Add the IP address in the error message to the allowed list in the network policy.
- C. Update the configuration of the Azure AD SSO to use the Private Link URLs.
- D. Generate a new SCIM access token using system$generate_scim_access_token and save it to Azure AD.
- E. Alter the Azure security integration to use the Private Link URLs.
答案:B,C
解題說明:
Explanation
The error message indicates that the IP address in the error message is not allowed to access Snowflake because it is not in the allowed list of the network policy. The network policy is a feature that allows restricting access to Snowflake based on IP addresses or ranges. To resolve this error, the Architect should take the following steps:
* Add the IP address in the error message to the allowed list in the network policy. This will allow the IP address to access Snowflake using the Private Link URLs. Alternatively, the Architect can disable the network policy if it is not required for security reasons.
* Update the configuration of the Azure AD SSO to use the Private Link URLs. This will ensure that the SSO authentication process uses the Private Link URLs instead of the public URLs. The configuration can be updated by following the steps in the Azure documentation1.
These two steps should resolve the error and ensure that the account is accessed using only Private Link. The other options are not necessary or relevant for this scenario. Altering the Azure security integration to use the Private Link URLs is not required because the security integration is used for SCIM provisioning, not for SSO authentication. Generating a new SCIM access token using system$generate_scim_access_token and saving it to Azure AD is not required because the SCIM access token is used for SCIM provisioning, not for SSO authentication. Opening a case with Snowflake Support to authorize the Private Link URLs' access to the account is not required because the authorization can be done by the account administrator using the SYSTEM$AUTHORIZE_PRIVATELINK function2.
問題 #47
An Architect is troubleshooting a query with poor performance using the QUERY function. The Architect observes that the COMPILATION_TIME Is greater than the EXECUTION_TIME.
What is the reason for this?
- A. The query has overly complex logic.
- B. The query is processing a very large dataset.
- C. The query Is reading from remote storage
- D. The query Is queued for execution.
答案:A
解題說明:
The correct answer is B because the compilation time is the time it takes for the optimizer to create an optimal query plan for the efficient execution of the query. The compilation time depends on the complexity of the query, such as the number of tables, columns, joins, filters, aggregations, subqueries, etc. The more complex the query, the longer it takes to compile.
Option A is incorrect because the query processing time is not affected by the size of the dataset, but by the size of the virtual warehouse. Snowflake automatically scales the compute resources to match the data volume and parallelizes the query execution. The size of the dataset may affect the execution time, but not the compilation time.
Option C is incorrect because the query queue time is not part of the compilation time or the execution time. It is a separate metric that indicates how long the query waits for a warehouse slot before it starts running. The query queue time depends on the warehouse load, concurrency, and priority settings.
Option D is incorrect because the query remote IO time is not part of the compilation time or the execution time. It is a separate metric that indicates how long the query spends reading data from remote storage, such as S3 or Azure Blob Storage. The query remote IO time depends on the network latency, bandwidth, and caching efficiency. Reference:
Understanding Why Compilation Time in Snowflake Can Be Higher than Execution Time: This article explains why the total duration (compilation + execution) time is an essential metric to measure query performance in Snowflake. It discusses the reasons for the long compilation time, including query complexity and the number of tables and columns.
Exploring Execution Times: This document explains how to examine the past performance of queries and tasks using Snowsight or by writing queries against views in the ACCOUNT_USAGE schema. It also describes the different metrics and dimensions that affect query performance, such as duration, compilation, execution, queue, and remote IO time.
What is the "compilation time" and how to optimize it?: This community post provides some tips and best practices on how to reduce the compilation time, such as simplifying the query logic, using views or common table expressions, and avoiding unnecessary columns or joins.
問題 #48
An Architect uses COPY INTO with the ON_ERROR=SKIP_FILE option to bulk load CSV files into a table called TABLEA, using its table stage. One file named file5.csv fails to load. The Architect fixes the file and re-loads it to the stage with the exact same file name it had previously.
Which commands should the Architect use to load only file5.csv file from the stage? (Choose two.)
- A. COPY INTO tablea FROM @%tablea MERGE = TRUE;
- B. COPY INTO tablea FROM @%tablea FILES = ('file5.csv');
- C. COPY INTO tablea FROM @%tablea NEW_FILES_ONLY = TRUE;
- D. COPY INTO tablea FROM @%tablea;
- E. COPY INTO tablea FROM @%tablea FORCE = TRUE;
- F. COPY INTO tablea FROM @%tablea RETURN_FAILED_ONLY = TRUE;
答案:B,D
問題 #49
Consider the following COPY command which is loading data with CSV format into a Snowflake table from an internal stage through a data transformation query.
This command results in the following error:
SQL compilation error: invalid parameter 'validation_mode'
Assuming the syntax is correct, what is the cause of this error?
- A. The VALIDATION_MODE parameter does not support COPY statements with CSV file formats.
- B. The value return_all_errors of the option VALIDATION_MODE is causing a compilation error.
- C. The VALIDATION_MODE parameter supports COPY statements that load data from external stages only.
- D. The VALIDATION_MODE parameter does not support COPY statements that transform data during a load.
答案:D
解題說明:
* The VALIDATION_MODE parameter is used to specify the behavior of the COPY statement when loading data into a table. It is used to specify whether the COPY statement should return an error if any of the rows in the file are invalid or if it should continue loading the valid rows. The VALIDATION_MODE parameter is only supported for COPY statements that load data from external stages1.
* The query in the question uses a data transformation query to load data from an internal stage. A data transformation query is a query that transforms the data during the load process, such as parsing JSON or XML data, applying functions, or joining with other tables2.
* According to the documentation, VALIDATION_MODE does not support COPY statements that transform data during a load. If the parameter is specified, the COPY statement returns an error1.
Therefore, option C is the correct answer.
References: : COPY INTO <table> : Transforming Data During a Load
問題 #50
How does a standard virtual warehouse policy work in Snowflake?
- A. It conserves credits by keeping running clusters fully loaded rather than starting additional clusters.
- B. It starts only if the system estimates that there is a query load that will keep the cluster busy for at least 6 minutes.
- C. It prevents or minimizes queuing by starting additional clusters instead of conserving credits.
- D. It starts only f the system estimates that there is a query load that will keep the cluster busy for at least 2 minutes.
答案:C
解題說明:
Explanation
A standard virtual warehouse policy is one of the two scaling policies available for multi-cluster warehouses in Snowflake. The other policy is economic. A standard policy aims to prevent or minimize queuing by starting additional clusters as soon as the current cluster is fully loaded, regardless of the number of queries in the queue. This policy can improve query performance and concurrency, but it may also consume more credits than an economic policy, which tries to conserve credits by keeping the running clusters fully loaded before starting additional clusters. The scaling policy can be set when creating or modifying a warehouse, and it can be changed at any time.
References:
* Snowflake Documentation: Multi-cluster Warehouses
* Snowflake Documentation: Scaling Policy for Multi-cluster Warehouses
問題 #51
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