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You are implementing an Azure Data Factory data flow that will use an Azure Cosmos DB (SQL API) sink to write a dataset. The data flow will use 2,000 Apache Spark partitions.
You need to ensure that the ingestion from each Spark partition is balanced to optimize throughput.
Which sink setting should you configure?
Batch size: An integer that represents how many objects are being written to Cosmos DB collection in each batch. Usually, starting with the default batch size is sufficient. To further tune this value, note:
Cosmos DB limits single request's size to 2MB. The formula is 'Request Size = Single Document Size * Batch Size'. If you hit error saying 'Request size is too large', reduce the batch size value.
The larger the batch size, the better throughput the service can achieve, while make sure you allocate enough RUs to empower your workload.
Incorrect Answers:
A: Throughput: Set an optional value for the number of RUs you'd like to apply to your CosmosDB collection for each execution of this data flow. Minimum is 400.
B: Write throughput budget: An integer that represents the RUs you want to allocate for this Data Flow write operation, out of the total throughput allocated to the collection.
D: Collection action: Determines whether to recreate the destination collection prior to writing.
None: No action will be done to the collection.
Recreate: The collection will get dropped and recreated
You have an Azure Cosmos DB for NoSQL account. The account hosts a container that has the change feed enabled. You are building an app by using the Azure Cosmos DB SDK. The app will read items from the change feed by using a pull model. You need to ensure that multiple threads can read the change feed in parallel. What should you include?
You have a database named db1in an Azure Cosmos DB for NoSQL account named account 1.
You need to write JSON data to db1 by using Azure Stream Analytics. The solution must minimize costs.
Which should you do before you can use db1 as an output of Stream Analytics?
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sett might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a container named conlainer1 in an Azure Cosmos DB for NoSQL account.
You need to make the contents of container1 available as reference data for an Azure Stream Analytics job.
Solution: You create an Azure function to copy data to another Azure Cosmos DB for NoSQL container.
Does this meet the goal?
You have an Azure Cosmos DB Core (SQL) API account that uses a custom conflict resolution policy. The account has a registered merge procedure that throws a runtime exception.
The runtime exception prevents conflicts from being resolved.
You need to use an Azure function to resolve the conflicts.
What should you use?
The Azure Cosmos DB Trigger uses the Azure Cosmos DB Change Feed to listen for inserts and updates across partitions. The change feed publishes inserts and updates, not deletions.
