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Microsoft DP-420 Exam Syllabus Topics:

Section	Weight	Objectives
Optimize an Azure Cosmos DB solution	15-20%	- Define and implement indexing strategy 1. Optimize index performance 2. Choose appropriate index types 3. Choose read-heavy or write-heavy indexing 4. Configure custom indexing policies 5. Implement composite indexes - Optimize query performance 1. Retrieve request unit cost 2. Calculate query cost 3. Adjust indexing policies 4. Implement integrated cache - Design and implement change feeds 1. Consume change feeds using SDK 2. Implement aggregation persistence 3. Manage change feed instances 4. Develop Azure Functions triggers
Design and implement data distribution	5-10%	- Design and implement replication strategy 1. Evaluate consistency model impacts 2. Choose a consistency model 3. Perform manual failovers 4. Choose when to distribute data 5. Define automatic failover policies - Design and implement multi-region writes 1. Choose when to use multi-region writes 2. Implement conflict resolution policies 3. Implement multi-region writes
Maintain an Azure Cosmos DB solution	25-30%	- Monitor and troubleshoot Azure Cosmos DB solutions 1. Implement backup and recovery strategies 2. Monitor metrics and logs 3. Monitor performance and availability 4. Troubleshoot throughput issues
Design and implement data models	35-40%	- Implement client connectivity options 1. Configure client-side threading and logging 2. Implement singleton client 3. Create database connections 4. Handle connection errors 5. Choose gateway or direct connectivity mode 6. Use Azure Cosmos DB emulator - Implement data access 1. Implement patch operations 2. Manage transactional batch operations 3. Use consistency and query request options 4. Implement optimistic concurrency control 5. Use SDKs for CRUD operations 6. Implement SQL queries with arrays and aggregation - Design a data partitioning strategy 1. Choose a partition key 2. Evaluate throughput and data distribution 3. Evaluate cross-partition query cost 4. Plan for transactions with partition keys 5. Choose a partitioning strategy 6. Implement synthetic partition keys - Design and implement a non-relational data model for Azure Cosmos DB for NoSQL 1. Identify data and associated access patterns 2. Identify partition key, id, and unique keys 3. Store multiple related entities in the same document 4. Store multiple entity types in the same container 5. Denormalize data across documents 6. Reference between documents - Plan and implement sizing and scaling 1. Design resource governance and scaling 2. Evaluate global distribution costs 3. Choose between serverless, provisioned, and free tier 4. Evaluate throughput and storage requirements 5. Configure throughput - Implement server-side programming 1. Implement triggers 2. Implement user-defined functions 3. Write and deploy stored procedures
Integrate an Azure Cosmos DB solution	5-10%	- Enable analytical workloads 1. Enable analytical store 2. Configure Azure Cosmos DB Mirroring 3. Write data back from Spark 4. Query analytical store from Synapse - Implement solutions across services 1. Aggregate and archive data 2. Use Change Feed for denormalization 3. Integrate Azure Functions and Event Hubs 4. Enforce referential integrity 5. Implement Azure AI Search integration

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q100-Q105):

NEW QUESTION # 100
You plan to create an Azure Cosmos DB container named account that will contain items in the following format.

You need to define a query that will return the ids of all accounts that have ever recorded a negative value for balance.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 101
You have an Azure Cosmos DB for NoSQL account.
You run the following query against a container in the account.

What is the output of the query?

A. [{"A": true, "B": false, "C": true}]
B. [{"A": true, "B": true, "C": true}]
C. [{"A": true, "B": true, "C": false}]
D. [{"A": false, "B": true, "C": false}]

Answer: D

Explanation:
IS_NUMBER returns a Boolean value indicating if the type of the specified expression is a number.
"1234" is a string, not a number.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/sql-query-is-number

NEW QUESTION # 102
You have an Apache Spark pool in Azure Synapse Analytics that runs the following Python code in a notebook.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation
New and updated orders will be added to contoso-erp.orders: Yes
The code performs bulk data ingestion from contoso-app: No
Both contoso-app and contoso-erp have Analytics store enabled: Yes
The code uses the spark.readStream method to read data from a container named orders in a database named contoso-app. The data is then filtered by a condition and written to another container named orders in a database named contoso-erp using the spark.writeStream method. The write mode is set to "append", which means that new and updated orders will be added to the destination container1.
The code does not perform bulk data ingestion from contoso-app, but rather stream processing. Bulk data ingestion is a process of loading large amounts of data into a data store in batches. Stream processing is a process of continuously processing data as it arrives in real-time2.
Both contoso-app and contoso-erp have Analytics store enabled, because they are both accessed by Spark pools using the spark.cosmos.oltp method. This method requires that the containers have Analytics store enabled, which is a feature that allows Spark pools to query data stored in Azure Cosmos DB containers using SQL APIs3.

NEW QUESTION # 103
You have the Azure Cosmos DB for NoSQL containers shown in the following table.

You have the items shown in the following table.

When will each item expire? To answer, select the appropriate options in the answer are a.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 104
You have an Azure Cosmos DB for NoSQL account that uses the default consistency level. How can the consistency level be modified as part of a query request?

A. stronger consistency for read operations
B. weaker consistency for write operations
C. weaker consistency for read operations
D. stronger consistency for write operations

Answer: C

NEW QUESTION # 105
......

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