ARA-C01 Exam Dumps : SnowPro Advanced: Architect Certification Exam

Database replication is a feature that allows you to create a copy of a database in another account, region, or cloud platform for disaster recovery or business continuity purposes. However, not all database objects can be replicated. External tables are one of the exceptions, as they reference data files stored in an external stage that is not part of Snowflake. Therefore, to replicate a database that contains external tables, you need to move the external tables to a separate database that is not replicated, and then replicate the primary database that contains the other objects. This way, you can avoid replication errors and ensure consistency between the primary and secondary databases. The other options are incorrect because they either do not address the issue of external tables, or they use an alternative method that is not supported by Snowflake. You cannot create a clone of the primary database and then replicate it, as replication only works on the original database, not on its clones. You also cannot share the primary database with another account, as sharing is a different feature that does not create a copy of the database, but rather grants access to the shared objects. Finally, you do not need to ensure that the replicated database is in the same region as the external tables, as external tables can access data files stored in any region or cloud platform, as long as the stage URL is valid and accessible. References:

[Replication and Failover/Failback] 1

[Introduction to External Tables] 2

[Working with External Tables] 3

[Replication : How to migrate an account from One Cloud Platform or Region to another in Snowflake] 4

 The most efficient solution is to ask the partner to create a share and add the company’s account (Option A). This way, the company can access the live data from the partner without any data movement or manual intervention. Snowflake’s secure data sharing feature allows data providers to share selected objects in a database with other Snowflake accounts. The shared data is read-only and does not incur any storage or compute costs for the data consumers. The data consumers can query the shared data directly or create local copies of the shared objects in their own databases. Option B is not efficient because it involves using the data lake export feature, which is intended for exporting data from Snowflake to an external data lake, not for importing data from another Snowflake account. The data lake export feature also requires the data provider to create an external stage on cloud storage and use the COPY INTO command to export the data into parquet files. The data consumer then needs to create an external table or a file format to load the data from the cloud storage into Snowflake. This process can be complex and costly, especially if the data changes frequently. Option C is not efficient because it does not solve the problem of manual data ingestion and adaptation. Keeping the current structure of daily JSON extracts on an FTP server and requesting the partner to stop changing files, instead only appending new files, does not improve the efficiency or reliability of the data ingestion process. The company still needs to upload the data to Snowflake manually and deal with any schema changes or data quality issues. Option D is not efficient because it requires the partner to set up a Snowflake reader account and use that account to get the data for ingestion. A reader account is a special type of account that can only consume data from the provider account that created it. It is intended for data consumers who are not Snowflake customers and do not have a licensing agreement with Snowflake. A reader account is not suitable for data ingestion from another Snowflake account, as it does not allow uploading, modifying, or unloading data. The company would need to use external tools or interfaces to access the data from the reader account and load it into their own account, which can be slow and expensive. References: The answer can be verified from Snowflake’s official documentation on secure data sharing, data lake export, and reader accounts available on their website. Here are some relevant links:

Introduction to Secure Data Sharing | Snowflake Documentation

Data Lake Export Public Preview Is Now Available on Snowflake | Snowflake Blog

Managing Reader Accounts | Snowflake Documentation

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.

 COPY INTO

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