HOTSPOT (Drag and Drop is not supported)You have an Azure Storage account that generates 200,000 new files daily. The file names have a format of {YYYY}/{MM}/{DD}/{HH}/{CustomerID}.csv.You need to design an Azure Data Factory solution that will load new data from the storage account to an Azure Data Lake once hourly. The solution must minimize load times and costs.How should you configure the solution? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.Hot Area:
Answer(s): A
Box 1: Incremental load Box 2: Tumbling windowTumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals. The following diagram illustrates a stream with a series of events and how they are mapped into 10-second tumbling windows.
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-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 sets 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 plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:-A workload for data engineers who will use Python and SQL.-A workload for jobs that will run notebooks that use Python, Scala, and SQL.-A workload that data scientists will use to perform ad hoc analysis in Scala and R.The enterprise architecture team at your company identifies the following standards for Databricks environments:-The data engineers must share a cluster.-The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.-All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.-You need to create the Databricks clusters for the workloads.Solution: You create a Standard cluster for each data scientist, a Standard cluster for the data engineers, and a High Concurrency cluster for the jobs.Does this meet the goal?
Answer(s): B
We need a High Concurrency cluster for the data engineers and the jobs.Note: Standard clusters are recommended for a single user. Standard can run workloads developed in any language: Python, R, Scala, and SQL.A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
https://docs.azuredatabricks.net/clusters/configure.html
You have the following Azure Data Factory pipelines:-Ingest Data from System1 -Ingest Data from System2 -Populate Dimensions -Populate Facts-Ingest Data from System1 and Ingest Data from System2 have no dependencies. -Populate Dimensions must execute after Ingest Data from System1 and Ingest Data from System2. -Populate Facts must execute after Populate Dimensions pipeline. -All the pipelines must execute every eight hours.What should you do to schedule the pipelines for execution?
Answer(s): C
Schedule trigger: A trigger that invokes a pipeline on a wall-clock schedule.
https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipeline-execution-triggers
DRAG DROP (Drag and Drop is not supported)You are responsible for providing access to an Azure Data Lake Storage Gen2 account.Your user account has contributor access to the storage account, and you have the application ID and access key.You plan to use PolyBase to load data into an enterprise data warehouse in Azure Synapse Analytics. You need to configure PolyBase to connect the data warehouse to storage account.Which three components should you create in sequence? To answer, move the appropriate components from the list of components to the answer area and arrange them in the correct order.Select and Place:
Step 1: an asymmetric keyA master key should be created only once in a database. The Database Master Key is a symmetric key used to protect the private keys of certificates and asymmetric keys in the database.Step 2: a database scoped credentialCreate a Database Scoped Credential. A Database Scoped Credential is a record that contains the authentication information required to connect an external resource. The master key needs to be created first before creating the database scoped credential.Step 3: an external data sourceCreate an External Data Source. External data sources are used to establish connectivity for data loading using Polybase.
https://www.sqlservercentral.com/articles/access-external-data-from-azure-synapse-analytics-using-polybase
You are monitoring an Azure Stream Analytics job by using metrics in Azure.You discover that during the last 12 hours, the average watermark delay is consistently greater than the configured late arrival tolerance.What is a possible cause of this behavior?
Answer(s): D
Watermark Delay indicates the delay of the streaming data processing job.There are a number of resource constraints that can cause the streaming pipeline to slow down. The watermark delay metric can rise due to:1. Not enough processing resources in Stream Analytics to handle the volume of input events. To scale up resources, see Understand and adjust Streaming Units.2. Not enough throughput within the input event brokers, so they are throttled. For possible solutions, see Automatically scale up Azure Event Hubs throughput units.3. Output sinks are not provisioned with enough capacity, so they are throttled. The possible solutions vary widely based on the flavor of output service being used.
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling
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