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You are monitoring an Azure Stream Analytics job. You discover that the Backlogged Input Events metric is increasing slowly and is consistently non-zero. You need to ensure that the job can handle all the events. What should you do?
Answer: B
You are designing an inventory updates table in an Azure Synapse Analytics dedicated SQL pool. The table will have a clustered columnstore index and will include the following columns:
You identify the following usage patterns: ✑ Analysts will most commonly analyze transactions for a warehouse. ✑ Queries will summarize by product category type, date, and/or inventory event type. You need to recommend a partition strategy for the table to minimize query times. On which column should you partition the table?
Answer: D
It is recommended to have at least 1 million rows per partition and distribution. Since there are 60 distributions, the number of rows for each partition must exceed 60 millions. Answer is correct
Source: Adapted from community discussion — Lio95
You are designing a star schema for a dataset that contains records of online orders. Each record includes an order date, an order due date, and an order ship date. You need to ensure that the design provides the fastest query times of the records when querying for arbitrary date ranges and aggregating by fiscal calendar attributes. Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: CD
Who gives these answers?? It's so obviously C and D. You want a Date Dim with an Integer key and the fact table also with that integer key
Source: Adapted from community discussion — AlCubeHead
A company purchases IoT devices to monitor manufacturing machinery. The company uses an Azure IoT Hub to communicate with the IoT devices. The company must be able to monitor the devices in real-time. You need to design the solution. What should you recommend?
Answer: C
You have a SQL pool in Azure Synapse. A user reports that queries against the pool take longer than expected to complete. You determine that the issue relates to queried columnstore segments. You need to add monitoring to the underlying storage to help diagnose the issue. Which two metrics should you monitor? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: BD
You have an Azure Databricks resource. You need to log actions that relate to changes in compute for the Databricks resource. Which Databricks services should you log?
Answer: A
Answer: A (clusters) Dispite using workspace to enable logging, from there you need to select clusters form the list if you want to satisfy the "changes in compute for the Databricks resource" question, hence the service you sould log is clusters. See link from Amsterliese. Beware of links to databricks.com vs links to microsoft because they are two slightly different products (i.e. Databricks (on AWS) vs Azure Databricks). For the other comment referencing dp200; the answer description only gives the defintions but no explanation.
Source: Adapted from community discussion — KashRaynardMorse
You are designing a highly available Azure Data Lake Storage solution that will include geo-zone-redundant storage (GZRS). You need to monitor for replication delays that can affect the recovery point objective (RPO). What should you include in the monitoring solution?
Answer: D
D. Last Sync Time: Monitoring the Last Sync Time metric will provide you with the information about the timestamp of the last successful synchronization between the primary and secondary regions. By monitoring this metric, you can determine if there are any replication delays impacting the RPO. If the Last Sync Time is significantly behind the current time, it indicates a replication delay and potential RPO impact.
Source: Adapted from community discussion — vctrhugo
You configure monitoring for an Azure Synapse Analytics implementation. The implementation uses PolyBase to load data from comma-separated value (CSV) files stored in Azure Data Lake Storage Gen2 using an external table. Files with an invalid schema cause errors to occur. You need to monitor for an invalid schema error. For which error should you monitor?
Answer: B
To monitor for an invalid schema error when using PolyBase to load data from CSV files in Azure Data Lake Storage Gen2 using an external table in Azure Synapse Analytics, you should monitor the following error: B. Cannot execute the query "Remote Query" against OLE DB provider "SQLNCLI11" for linked server "(null)". Query aborted- the maximum reject threshold (0 rows) was reached while reading from an external source: 1 rows rejected out of total 1 rows processed. This error indicates that a row in the CSV file has been rejected due to an invalid schema. By monitoring for this error, you can identify when data loading fails due to an incompatible or incorrect schema in the CSV files.
Source: Adapted from community discussion — vctrhugo
You have an Azure Synapse Analytics dedicated SQL pool that contains a large fact table. The table contains 50 columns and 5 billion rows and is a heap. Most queries against the table aggregate values from approximately 100 million rows and return only two columns. You discover that the queries against the fact table are very slow. Which type of index should you add to provide the fastest query times?
Answer: B
Correct. The "Nonclustered columnstore" isn't a posibility in synapse, it not exists: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index#index-types Due to number of rows returned (mora than 60 million) clustered index is not a good option: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index#heap-tables Is a Heap table; a table without any index, so clustered columstore index seems to be the correct options. Because non-clustered index is a good option when you have a primary clustered index and usea mutiple columns in where clause, but is a Heap table.
Source: Adapted from community discussion — juanlu46
You have an Azure Synapse Analytics dedicated SQL pool. You run PDW_SHOWSPACEUSED('dbo.FactInternetSales'); and get the results shown in the following table.
Which statement accurately describes the dbo.FactInternetSales table?
Answer: D
correct as few distributions have more data and few have no data at all. The data should be evenly distributed across all the distributions.
Source: Adapted from community discussion — PallaviPatel
Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page
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