ARA-R01 Exam Dumps : SnowPro Advanced: Architect Recertification Exam

By default, Snowflake does not allow sharing data from a Business Critical edition to a non-Business Critical edition. This is because Business Critical edition provides enhanced security and data protection features that are not available in lower editions. However, this restriction can be overridden by setting the share_restriction parameter on the shared object (database, schema, or table) to false. This parameter allows the data provider to explicitly allow sharing data with lower edition accounts. Note that this parameter can only be set by the data provider, not the data consumer. Also, setting this parameter to false may reduce the level of security and data protection for the shared data.

References:

• Enable Data Share:Business Critical Account to Lower Edition
• Sharing Is Not Allowed From An Account on BUSINESS CRITICAL Edition to an Account On A Lower Edition
• SQL Execution Error: Sharing is Not Allowed from an Account on BUSINESS CRITICAL Edition to an Account on a Lower Edition
• Snowflake Editions | Snowflake Documentation

For the configuration of data unloading in Snowflake, the valid option among the provided choices is "C." This is because Snowflake supports unloading data into Google Cloud Storage using the COPY INTO command with specific configurations. The configurations listed in option C, such as Parquet file format with UTF-8 encoding and gzip compression, are all supported by Snowflake. Notably, Parquet is a columnar storage file format, which is optimal for high-performance data processing tasks in Snowflake. The UTF-8 file encoding and gzip compression are both standard and widely used settings that are compatible with Snowflake’s capabilities for data unloading to cloud storage platforms.References:

• Snowflake Documentation on COPY INTO command
• Snowflake Documentation on Supported File Formats
• Snowflake Documentation on Compression and Encoding Options

According to the Snowflake documentation, the following are some considerations for choosing clustering for a table1:

• Clustering is optimal when either:
• Clustering is most effective when the clustering key is used in the following types of query predicates:
• Clustering is less effective when the clustering key is not used in any of the above query predicates, or when the clustering key is used in a predicate that requires a function or expression to be applied to the key (e.g. DATE_TRUNC, TO_CHAR, etc.).
• For most tables, Snowflake recommends a maximum of 3 or 4 columns (or expressions) per key. Adding more than 3-4 columns tends to increase costs more than benefits.

Based on these considerations, the best option for the clustering key columns is C. C1, C3, C2, because:

• These columns are heavily used in filter and join conditions of SELECT queries, which are the most effective types of predicates for clustering.
• These columns have high cardinality, which means they have many distinct values and can help reduce the clustering skew and improve the compression ratio.
• These columns are likely to be correlated with each other, which means they can help co-locate similar rows in the same micro-partitions and improve the scan efficiency.
• These columns do not require any functions or expressions to be applied to them, which means they can be directly used in the predicates without affecting the clustering.

References: 1: Considerations for Choosing Clustering for a Table | Snowflake Documentation