As you prepare for the DP-420 Designing and Implementing Native Applications Using Microsoft Azure Cosmos DB exam, one critical decision you’ll need to make is choosing between Azure Synapse Link and Spark Connector for data analysis purpose. Depending on the requirements of your project, one may be a better fit than the other. Let’s compare both options to help make this decision clearer.
Understanding Azure Synapse Link
Azure Synapse Link for Azure Cosmos DB is a cloud-based hybrid transactional analytical processing (HTAP) capability that enables you to analyze your operational data in near real-time.
The key advantage of Azure Synapse Link is its capability to run large-scale analytics without the operational overhead and it doesn’t affect your workload running on Cosmos DB. It seamlessly applies schema on read capabilities and does the data extraction without impacting the transactional workloads.
// Here is a simple example of a query with Azure Synapse Link
SELECT c.name, c.address.city
FROM c
WHERE c.address.state = 'WA'
Understanding Spark Connector
On the other hand, Azure Cosmos DB’s Apache Spark connector seamlessly connects Azure Cosmos DB and Apache Spark to facilitate real-time data analytics, machine learning, and much more. It offers bi-directional communication capabilities between Cosmos DB and Spark, allowing you to read and write data from and to your database.
Compared to Azure Synapse Link, Spark Connector needs a Spark Cluster to be set up for its operations and it has its own provisioned throughput. Hence, it may impact the transactional workload on Cosmos DB, if it isn’t designed properly.
# Here is a simple example of a read operation from Cosmos DB with Spark Connector
df = spark.read.format("com.microsoft.azure.cosmosdb.spark").load()
df.select("address.state").show()
Key Differences
The following are the key differences between Azure Synapse Link and Spark Connector:
| Azure Synapse Link | Spark Connector | |
|---|---|---|
| Impact on Workload | No impact on transactional workload | Can impact transactional workload if not properly designed |
| Operational Overhead | Minimal, as it runs large scale analytics | Higher, as requires set-up of spark cluster |
| Data Read/Write Capabilities | Read only data for analytics | Allows both read and write operations |
| Dependencies | No dependencies | Requires an operational Spark cluster |
When to Choose What?
It is critical to understand your project requirements to make the right choice between Azure Synapse Link and Spark Connector.
- 1. Choose Azure Synapse Link if your project primarily involves large-scale analytics and you want a solution with minimal setup, operational overhead and zero impact on your operational workloads.
- 2. On the other hand, if your project is geared towards machine learning, requires both read and write operations, and you have means to manage an operational Spark cluster, Spark Connector would be a better choice.
In conclusion, while both Azure Synapse Link and Spark Connector serve critical roles within the Cosmos DB ecosystem, understanding their features, strengths, and potential impacts on projects is essential for DP-420 exam and informing the best possible decisions for real-world implementations.
Practice Test
True/False: Azure Synapse Link for Azure Cosmos DB is a cloud-native hybrid transactional and analytical processing (HTAP) capability.
- True
Answer: True
Explanation: Azure Synapse Link for Azure Cosmos DB is indeed a cloud-native hybrid transactional and analytical processing (HTAP) capability that enables you to run near real-time analytics over operational data.
Which of the following provides automatic Azure Cosmos DB analytical store updates?
- a. Azure Synapse Link
- b. Spark Connector
Answer: a. Azure Synapse Link
Explanation: Azure Synapse Link automatically synchronizes Azure Cosmos DB containers with an analytical store enabling no-ETL (Extract-Transform-Load) Azure Synapse analytics.
True/False: Both Azure Synapse Link and Spark Connector allow running analytical workloads without affecting the transactional workloads.
- False
Answer: False
Explanation: Only Azure Synapse Link allows you to run large-scale analytics directly on operational data without affecting transactional workloads. This is not possible with the Spark Connector.
True/False: Azure Synapse Link integrates Azure Cosmos DB with Azure Synapse Analytics and Azure Databricks.
- False
Answer: False
Explanation: Azure Synapse Link integrates Azure Cosmos DB with Azure Synapse Analytics, but not with Azure Databricks. For integration with Azure Databricks, Spark Connector is the recommended choice.
Multiple select: Which of the following supports serverless and on-demand models for running analytics workloads?
- a. Azure Synapse Link
- b. Spark Connector
Answer: a. Azure Synapse Link
Explanation: Azure Synapse Link supports serverless and on-demand models for running analytics workloads, enabling cost-effective analytics processing.
True/False: Spark Connector supports consumption of change feed.
- True
Answer: True
Explanation: Spark Connector for Cosmos DB supports change feed, which provides a sorted, chronological list of changes that have been made to items within a container.
Single select: For near real-time analytics on operational data, which is more preferable?
- a. Azure Synapse Link
- b. Spark Connector
Answer: a. Azure Synapse Link
Explanation: Azure Synapse Link enables near real-time analytics on operational data due to its automatic synchronization feature with the Azure Cosmos DB analytical store.
True/False: Spark Connector requires ETL operations to prepare data for analytical workloads.
- True
Answer: True
Explanation: Unlike Azure Synapse Link with a no-ETL capability, Spark Connector does require ETL operations to transform and load data for analytical workloads.
Multiple select: Which of the following offers seamless management and monitoring capabilities through Azure Synapse Studio?
- a. Azure Synapse Link
- b. Spark Connector
Answer: a. Azure Synapse Link
Explanation: Azure Synapse Link offers seamless management and monitoring capabilities through Azure Synapse Studio. Spark Connector doesn’t provide this feature.
True/False: Both Azure Synapse Link and Spark Connector require setting up separate compute resources for analytical workloads.
- False
Answer: False
Explanation: Setting up separate compute resources for analytical workloads is required with the Spark Connector but not with Azure Synapse Link.
Interview Questions
What is Azure Synapse Link?
Azure Synapse Link for Azure Cosmos DB is a hybrid transactional and analytical processing (HTAP) capability that enables you to run near real-time analytics over operational data in Azure Cosmos DB.
What is a Spark Connector?
A Spark Connector is a tool that allows Spark to read from and write to other storage systems, such as Azure Cosmos DB, using the Spark scheduler without needing to install new software or manage clusters.
What are the key features of Azure Synapse Link?
Azure Synapse Link features include seamless integration with Azure Synapse Analytics, no-ETL (Extract, Transform, Load) data exploration, and immediate insights from Azure Cosmos DB data through Azure Synapse Analytics.
Which one between Azure Synapse Link and Spark Connector could be used to eliminate ETL pipelines?
Azure Synapse Link could be used to eliminate ETL pipelines because it allows for immediate querying of operational data without the need for data movement.
When would you recommend using Azure Synapse Link over Spark Connector?
Azure Synapse Link would be more suitable when near real-time insights are needed straight from operational data without moving data between data lakes and data warehouses.
Can Spark Connector and Azure Synapse Link be used together?
Yes, Spark Connector can be used to read and write data to Azure Cosmos DB, while Azure Synapse Link can be used to enable analytics over the real-time data.
How are the analytics capabilities different between Azure Synapse Link and Spark Connector?
Azure Synapse Link supports On-demand and serverless exploratory analytics, whereas Spark connector is primarily used for batch-mode analytics tasks with Azure Cosmos DB.
What is the potential advantage of using Azure Synapse Link?
Azure Synapse Link allows for immediate business insights over data in Azure Cosmos DB without affecting its transactional workload.
How does the data latency differ between Azure Synapse Link and Spark Connector?
Azure Synapse Link provides near real-time analytics, reducing data latency. The Spark Connector, on the other hand, may introduce some data latency based on the size of the data and the processing power of the Spark cluster.
Are there any prerequisites for using Azure Synapse Link?
Yes, to use Azure Synapse Link, we need an Azure account, an Azure Cosmos DB SQL API account, and an Azure Synapse Analytics workspace.
Can Spark Connector enable analytic capabilities without affecting transactional workload in Cosmos DB?
No, unlike Azure Synapse Link, Spark Connector may affect the transactional workload while executing heavy analytic tasks.
Which between Azure Synapse Link and Spark Connector allows seamless integration with Azure Synapse Studio?
Azure Synapse Link for Cosmos DB allows seamless integration with Azure Synapse Studio.
Can you use Azure Synapse Link for any Azure Cosmos DB API?
Currently, Azure Synapse Link is only available for Azure Cosmos DB’s SQL and MongoDB APIs.
Which one between Azure Synapse Link and Spark Connector is better when real-time analytics is not a requirement?
If real-time analytics is not a requirement, both Azure Synapse Link and Spark Connector could be used. The choice would then depend upon other factors, such as the need for ETL processes, the desired compute model, and the complexity of analytics tasks.
Which technology provides built-in integration with Power BI, Azure Machine Learning and Azure Synapse Studio?
Azure Synapse Link provides built-in integration with these services.
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