Free Microsoft DP-900 Practice Exam with Questions & Answers | Set: 5

YES, NO, YES Normalizing decreases throughput for reading (need to make joins), but increases for writing (Less to write, since there are no duplicates)

Box 1: SELECT

Box 2: GROUP BY

Example:

When used with a GROUP BY clause, each aggregate function produces a single value covering each group, instead of a single value covering the whole table. The following example produces summary values for each sales territory in the AdventureWorks2012 database. The summary lists the average bonus received by the sales people in each territory, and the sum of year-to-date sales for each territory.

SELECT TerritoryID, AVG(Bonus)as 'Average bonus', SUM(SalesYTD) as 'YTD sales'

FROM Sales.SalesPerson

GROUP BY TerritoryID;

Box 1: Yes

Azure Databricks can consume data from SQL Databases using JDBC and from SQL Databases using the Apache Spark connector.

The Apache Spark connector for Azure SQL Database and SQL Server enables these databases to act as input data sources and output data sinks for Apache Spark jobs.

Box 2: Yes

You can stream data into Azure Databricks using Event Hubs.

Box 3: Yes

You can run Spark jobs with data stored in Azure Cosmos DB using the Cosmos DB Spark connector. Cosmos can be used for batch and stream processing, and as a serving layer for low latency access.

You can use the connector with Azure Databricks or Azure HDInsight, which provide managed Spark clusters on Azure.

Data Manipulation Language (DML) statements:

DELETE

INSERT

UPDATE

Time series data is a set of values organized by time. Time series databases typically collect large amounts of data in real time from a large number of sources. Updates are rare, and deletes are often done as bulk operations. Although the records written to a time-series database are generally small, there are often a large number of records, and total data size can grow rapidly.