Snowflake DEA-C01 Dumps

This option is the best way to configure the compute resources to support this dashboard. By assigning all queries to a multi-cluster virtual warehouse set to maximized mode, the Data Engineer can ensure that there is enough compute capacity to handle thousands of concurrent queries from different analysts. A multi-cluster virtual warehouse can scale up or down by adding or removing clusters based on the load. A maximized scaling policy ensures that there is always at least one cluster running and that new clusters are added as soon as possible whenneeded. By monitoring the utilization and performance of the virtual warehouse, the Data Engineer can determine the smallest suitable number of clusters that can meet the responsiveness requirement and minimize costs.

The isolation level of Snowflake streams is repeatable read, which means that each transaction sees a consistent snapshot of data that does not change during its execution. Streams use time travel internally to provide this isolation level and ensure that queries on streams return consistent results regardless of concurrent transactions on their source tables.

The Snowflake objects that are created automatically when the Kafka connector starts are tables, pipes, and internal stages. The Kafka connector will create one table, one pipe, and oneinternal stage for each Kafka topic that is configured in the connector properties. The table will store the data from the Kafka topic, the pipe will load the data from the stage to the table using COPY statements, and the internal stage will store the files that are produced by the Kafka connector using PUT commands. The other options are not Snowflake objects that are created automatically when the Kafka connector starts. Option B, tasks, are objects that can execute SQL statements on a schedule without requiring a warehouse. Option E, external stages, are objects that can reference locations outside of Snowflake, such as cloud storage services. Option F, materialized views, are objects that can store the precomputed results of a query and refresh them periodically.