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

This command will fail because while the user has USAGE permission ondb2andschema2through Role B, and can create a view inschema2, they do not have SELECT permission ondb1.schemal.table1with Role B. Since Role A, which has SELECT permission ondb1.schemal.table1, is not the currently active role when the viewv2is being created indb2.schema2, the user does not have the necessary permissions to read fromdb1.schemal.table1to create the view. Snowflake’s security model requires that the active role have all necessary permissions to execute the command.

 Option C is the correct answer because schema-on-read is a technique that allows Snowflake to ingest and consume semi-structured data without requiring a predefined schema. Snowflake supports various semi-structured data formats such as JSON, Avro, ORC, Parquet, and XML, and provides native data types (ARRAY, OBJECT, and VARIANT) for storing them. Snowflake also provides native support for querying semi-structured data using SQL and dot notation. Schema-on-read enables Snowflake to query semi-structured data at the same speed as performing relational queries while preserving the flexibility of schema-on-read. Snowflake’s near-instant elasticity rightsizes compute resources, and consumption-based pricing ensures you only pay for what you use.

Option A is incorrect because IDEF1X is a data modeling technique that defines the structure and constraints of relational data using diagrams and notations. IDEF1X is not suitable for ingesting and consuming semi-structured data, which does not have a fixed schema or structure.

Option B is incorrect because schema-on-write is a technique that requires defining a schema before loading and processing data. Schema-on-write is not efficient for ingesting and consuming semi-structured data, which may have varying or complex structures that are difficult to fit into a predefined schema. Schema-on-write also introduces additional overhead and complexity for data transformation and validation.

Option D is incorrect because information schema is a set of metadata views that provide information about the objects and privileges in a Snowflake database. Information schema is not a technique for ingesting and consuming semi-structured data, but rather a way of accessing metadata about the data.

A pipe is a Snowflake object that continuously loads data from files in a stage (internal or external) into a table. A pipe can be configured to use auto-ingest, which means that Snowflake automatically detects new or modified files in the stage and loads them into the table without any manual intervention1.

A pipe is the most cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it minimizes the number of COPY commands executed and the number of micro-partitions created. A pipe can use file aggregation, which means that it can combine multiple small files into a single larger file before loading them into the table. This reduces the load time and the storage cost of the data2.

An external table is a Snowflake object that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table does not store the data in Snowflake, but only provides a view of the data for querying. An external table is not a cost-effective way to bring data into a Snowflake table, because it does not support file aggregation, and it requires additional network bandwidth and compute resources to query the external data3.

A stream is a Snowflake object that records the history of changes (inserts, updates, and deletes) made to a table. A stream can be used to consume the changes from a table and apply them to another table or a task. A stream is not a way to bring data into a Snowflake table, but a way to process the data after it is loaded into a table4.

A copy command is a Snowflake command that loads data from files in a stage into a table. A copy command can be executed manually or scheduled using a task. A copy command is not a cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it does not support file aggregation, and it may create many micro-partitions that increase the storage cost of the data5.

 Pipes : Loading Data Using Snowpipe : External Tables : Streams : COPY INTO

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