Denormalization, an essential tool in the optimization of database performance, refers to the process of joining two or more related tables within one table. This is counter to the normalization process that seeks to reduce redundancy within data. Denormalization aims to improve read performance by reducing the number of joins and simplifying queries, thereby improving throughput and response times. If denormalization is a technique you aim to employ in your Azure Cosmos DB native application design, you may want to consider using a change feed to implement this.
Azure Cosmos DB is a multi-model globally distributed database service that is optimal for managing large amounts of data quickly and flexibly. The Azure Cosmos DB change feed is a persistent log of documents that are sorted by time and ordered by the logical sequence of operations. It enables you to listen to any changes to your data. Being able to respond to changes in real time allows event sourcing architectures to react and trigger actions, like denormalization.
Implementing Denormalization using Change Feed
To implement denormalization using a change feed, we must first establish an Azure Cosmos DB instance with a change feed.
1. Setting up the Azure Cosmos DB Change Feed
Setting up the Azure Cosmos DB change feed involves enabling the change feed policy at the level of the Azure Cosmos DB account.
{
"id": "myContainerId",
"partitionKey": {
"paths": ["/myPath"],
"kind": "Hash"
},
"changeFeedPolicy": {
"fullFidelityTtl": 120
}
}
In the above JSON definition, the changeFeedPolicy property is set to 120 minutes which means the change feed retains the change log for 120 minutes.
2. Consuming the Change Feed with Azure Functions
Azure Functions is a serverless compute service that lets you run event-triggered code without having to explicitly provision or manage infrastructure. In this scenario, Azure Functions can be used to trigger code that consumes the change feed.
To set up an Azure Function that’s triggered by a change feed, you must define a new function that’s bound to the Cosmos DB change feed. Here is a simple example function:
[FunctionName("ChangeFeedFunction")]
public static async Task Run([CosmosDBTrigger(
databaseName: "ToDoList",
collectionName: "Items",
ConnectionStringSetting = "CosmosDBConnection",
LeaseCollectionName = "leases")]IReadOnlyList
documents, ILogger log)
{
if (documents != null && documents.Count > 0)
{
log.LogInformation("Documents modified " + documents.Count);
log.LogInformation("First document Id " + documents[0].Id);
}
}
The above function logs the number of documents modified and the first document ID every time there is a change in the “Items” collection within the ToDoList database.
3. Implementing Denormalization
You then modify the Azure Function to apply denormalization changes based on the data that has been monitored and captured by the change feed. With the captured changes, you can decide how to denormalize your data. You may want to combine related information and create a new view that simplifies your app’s queries, effectively speeding up read speeds and overall database performance.
Benefits and Drawbacks of Denormalization
Implementing denormalization using a change feed in Azure Cosmos DB comes with both benefits and potential drawbacks to consider when designing your native Azure Cosmos DB Application.
| Advantages | Disadvantages | |
|---|---|---|
| Denormalization |
|
|
Bear in mind, while denormalization can reduce the complexity of queries and improve read performance, it may increase the complexity of updates and will definitely increase storage costs. As such, you need to be mindful of the right balance suitable for your application needs.
Implementing denormalization can tune your Azure Cosmos DB application for maximum performance. While there are certain trade-offs to be considered, the Azure Cosmos DB change feed enables you to react to changes to your data immediately, allowing you to simplify queries and improve throughput and latency, for a more optimized application experience.
Practice Test
True or False: Denormalization is the process of combining two or more tables into one.
- True
- False
Answer: True.
Explanation: Denormalization is the process of merging two or more tables into a single table in a database to optimize database performance.
What is a change feed in Azure Cosmos DB?
- a) A mechanism to capture changes in data over a specified period of time.
- b) A feed to monitor data usage.
- c) A feed to capture changes only in the schema of the database.
- d) A log to track changes made by database users.
Answer: A.
Explanation: A change feed in Azure Cosmos DB is a mechanism to capture changes in data over a specified period of time.
True or False: Denormalization can have a negative impact on write performance.
- True
- False
Answer: True.
Explanation: While denormalization can improve read performance, it can often slow down writes as data must be updated in multiple places.
How is denormalization used with a change feed in Azure Cosmos DB?
- a) It triggers an update in the denormalized data whenever a change is detected.
- b) Denormalization is not applied to a change feed.
- c) Denormalization only processes the information as changes are detected in the change feed.
- d) It uses the information in the change feed to identify which tables to combine.
Answer: A.
Explanation: By using a change feed, denormalization can be applied where needed, and an update process can be triggered each time the original data changes.
True or False: Azure Cosmos DB doesn’t support change feed.
- True
- False
Answer: False.
Explanation: Azure Cosmos DB supports change feed. It is a mechanism that provides a sorted list of documents within an Azure Cosmos container in the order in which they were modified.
Multiple Select: Which of the following are advantages of denormalization?
- a) Improved read performance.
- b) Less write operation on a database.
- c) Simplified queries.
- d) Reduced data redundancy.
Answer: A and C.
Explanation: The main benefits of denormalization include improved read performance and simplified queries. However, denormalization often leads to more complex write operations and increased data redundancy.
True or False: Denormalization increases data redundancy.
- True
- False
Answer: True.
Explanation: While denormalization can improve read performance, it often comes with the drawback of increasing data redundancy as the same piece of data is replicated in multiple places.
What are change feeds primarily used for in Azure Cosmos DB?
- a) For archiving the database.
- b) For setting permissions.
- c) To handle real-time processing.
- d) For monitoring user usage.
Answer: C.
Explanation: Change feeds in Azure Cosmos DB are mainly used to handle event sourcing, real-time processing, and other similar scenarios where it is necessary to reflect changes in the database immediately.
True or False: Denormalization simplified data writing operations.
- True
- False
Answer: False.
Explanation: Denormalization often complicates write operations, as changing a single piece of data could imply updating all places where it has been replicated.
Is denormalization applicable in every type of database?
- Yes
- No
Answer: No.
Explanation: Denormalization is typically used in SQL databases. In NoSQL databases like Azure Cosmos DB, data is typically denormalized as a normal practice.
Interview Questions
What is denormalization in the context of Azure Cosmos DB?
Denormalization in Azure Cosmos DB is a technique used to combine data from multiple sources into a single, simplified form within a document in order to accelerate read operations.
What role does the Change Feed feature play in the implementation of denormalization in Azure Cosmos DB?
The Change Feed feature supports denormalization by enabling you to handle events such as additions, modifications, and deletions of data in Azure Cosmos containers. It provides sorted, sequenced, and time-stamped data modifications that can be read and processed in real-time or asynchronously.
How can you enable the Change Feed in Azure Cosmos DB?
The Change Feed in Azure Cosmos DB is enabled by default and does not need any specific activation. Users can consume the feed at any time without impacting performance or incurring extra costs.
How does Azure Cosmos DB maintain consistency across normalized and denormalized data?
Azure Cosmos DB utilizes a change feed feature that listens for changes in the main data container. When changes occur, the change feed triggers an Azure function that performs necessary updates to keep the denormalized data consistent.
What advantages does using denormalization provide in Azure Cosmos DB?
Denormalization in Azure Cosmos DB enables faster read operations as it eliminates the need to query multiple containers for data. It also reduces the complexity of queries and allows for easy data scaling.
Which Azure service is typically used along with Azure Cosmos DB Change Feed for denormalization implementation?
Azure Functions is commonly used with Change Feed to implement denormalization, creating a serverless architecture that responds to changes in the container.
Does the use of Change Feed in Azure Cosmos DB require a separate data store?
No, Change Feed works within Azure Cosmos DB itself and doesn’t require a separate data store.
In the process of denormalization, what happens when data changes in Azure Cosmos DB?
When data changes in Azure Cosmos DB, the Change Feed feature captures these changes and triggers an Azure Function(s) that updates the denormalized data accordingly.
Can you monitor the changes in Azure Cosmos DB Change Feed?
Yes, the changes in Azure Cosmos DB Change Feed can be monitored using Azure Monitor, which provides real-time telemetry and operational insight into your Azure resources.
Is there any cost associated with consuming the Change Feed in Azure Cosmos DB?
Yes, reading the Change Feed does consume request units(RUs), so it will incur some cost based on the volume of changes and frequency of reading.
How can you pause processing of a change feed in Azure Cosmos DB?
You can control the checkpointing process by manually checkpointing to pause processing. In the event of a failure, processing can be resumed from the last checkpoint.
Are the changes in Azure Cosmos DB Change Feed persistent?
Yes, the data in Azure Cosmos DB Change Feed is persistent and remains available until it is classified as obsolete according to the container’s data retention policy.
Can you use Change Feed with all Azure Cosmos DB APIs?
Currently, Change Feed is supported with SQL (Core) API and MongoDB API in Azure Cosmos DB.
How is the order of the changes preserved in Azure Cosmos DB Change Feed?
Each change record in the Change Feed comes with a system attribute “_lsn”, which denotes the logical sequence number. The changes are sorted by this “_lsn” in ascending order, thereby preserving the order of changes.
What type of data consistency does Azure Cosmos DB Change Feed guarantee?
Azure Cosmos DB Change Feed guarantees eventual consistency. This means that if no new changes are made to the data, eventually all replicas will be consistent.
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