Microsoft DP-300 Practice Test - Questions Answers, Page 17

Step 1: Attach the SSISDB database

Step 2: Turn on the TRUSTWORTHY property and the CLR property

If you are restoring the SSISDB database to an SQL Server instance where the SSISDB catalog was never created, enable common language runtime (clr)

Step 3: Open the master key for the SSISDB database

Restore the master key by this method if you have the original password that was used to create SSISDB.

open master key decryption by password = 'LS1Setup!' --'Password used when creating SSISDB'

Alter Master Key Add encryption by Service Master Key

Step 4: Encrypt a copy of the mater key by using the service master key

Reference:

https://docs.microsoft.com/en-us/sql/integration-services/backup-restore-and-move-the-ssis-catalog

The partition count for an event hub in a dedicated Event Hubs cluster can be increased after the event hub has been created. Incorrect Answers:

A: For Azure Event standard hubs, the partition count isn't changeable, so you should consider long-term scale when setting partition count.

Reference:

https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-features#partitions

Serverless SQL pool can automatically synchronize metadata from Apache Spark. A serverless SQL pool database will be created for each database existing in serverless Apache Spark pools. Serverless SQL pool enables you to query data in your data lake. It offers a T-SQL query surface area that accommodates semi-structured and unstructured data queries.

To support a smooth experience for in place querying of data that's located in Azure Storage files, serverless SQL pool uses the OPENROWSET function with additional capabilities.

The easiest way to see to the content of your JSON file is to provide the file URL to the OPENROWSET function, specify csv FORMAT.

Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/query-json-files

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/query-data-storage

A replicated table has a full copy of the table available on every Compute node. Queries run fast on replicated tables since joins on replicated tables don't require data movement. Replication requires extra storage, though, and isn't practical for large tables.

Incorrect Answers:

C: A round-robin distributed table distributes table rows evenly across all distributions. The assignment of rows to distributions is random. Unlike hash-distributed tables, rows with equal values are not guaranteed to be assigned to the same distribution.

As a result, the system sometimes needs to invoke a data movement operation to better organize your data before it can resolve a query.

Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-distribute

Serverless SQL pool can automatically synchronize metadata from Apache Spark. A serverless SQL pool database will be created for each database existing in serverless Apache Spark pools. For each Spark external table based on Parquet and located in Azure Storage, an external table is created in a serverless SQL pool database. As such, you can shut down your Spark pools and still query Spark external tables from serverless SQL pool.

Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-storage-files-spark-tables

Anomalies can be identified by routing data via IoT Hub to a built-in ML model in Azure Stream Analytics

Reference:

https://docs.microsoft.com/en-us/learn/modules/data-anomaly-detection-using-azure-iot-hub/ https://docs.microsoft.com/en-us/azure/stream-analytics/azure-synapse-analytics-output

You can override the default language by specifying the language magic command %<language> at the beginning of a cell. The supported magic commands are: %python, %r, %scala, and %sql.

Reference:

https://docs.microsoft.com/en-us/azure/databricks/notebooks/notebooks-use

Complete mode: You can use Structured Streaming to replace the entire table with every batch.

Incorrect Answers:

B: By default, streams run in append mode, which adds new records to the table.

Reference:

https://docs.databricks.com/delta/delta-streaming.html