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| Section | Weight | Objectives |
|---|---|---|
| Building and operationalizing data processing systems | 24% | - Data processing and transformation
|
| Ensuring solution quality | 28% | - Reliability and performance
|
| Operationalizing machine learning models | 26% | - Model deployment and monitoring
|
| Designing data processing systems | 22% | - Batch and streaming data processing design
|
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NEW QUESTION # 371
Your infrastructure team has set up an interconnect link between Google Cloud and the on- premises network. You are designing a high-throughput streaming pipeline to ingest data in streaming from an Apache Kafka cluster hosted on- premises. You want to store the data in BigQuery, with as minimal latency as possible. What should you do?
Answer: D
NEW QUESTION # 372
When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and ____.
Answer: D
Explanation:
At a minimum, you must specify four values when creating a new cluster with the projects.regions.clusters.create operation:
The project in which the cluster will be created
The region to use
The name of the cluster
The zone in which the cluster will be created
You can specify many more details beyond these minimum requirements. For example, you can
also specify the number of workers, whether preemptible compute should be used, and the network settings.
NEW QUESTION # 373
The Dataflow SDKs have been recently transitioned into which Apache service?
Answer: C
Explanation:
Dataflow SDKs are being transitioned to Apache Beam, as per the latest Google directive
https://cloud.google.com/dataflow/docs/
NEW QUESTION # 374
You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?
Answer: D
NEW QUESTION # 375
You are using BigQuery with a regional dataset that includes a table with the daily sales volumes. This table is updated multiple times per day. You need to protect your sales table in case of regional failures with a recovery point objective (RPO) of less than 24 hours, while keeping costs to a minimum. What should you do?
Answer: B
Explanation:
To apply complex business logic on a JSON response using Python's standard library within a Workflow, invoking a Cloud Function is the most efficient and straightforward approach. Here's why option A is the best choice:
Cloud Functions:
Cloud Functions provide a lightweight, serverless execution environment for running code in response to events. They support Python and can easily integrate with Workflows.
This approach ensures simplicity and speed of execution, as Cloud Functions can be invoked directly from a Workflow and handle the complex logic required.
Flexibility and Simplicity:
Using Cloud Functions allows you to leverage Python's extensive standard library and ecosystem, making it easier to implement and maintain the complex business logic.
Cloud Functions abstract the underlying infrastructure, allowing you to focus on the application logic without worrying about server management.
Performance:
Cloud Functions are optimized for fast execution and can handle the processing of the JSON response efficiently.
They are designed to scale automatically based on demand, ensuring that your workflow remains performant.
Steps to Implement:
Write the Cloud Function:
Develop a Cloud Function in Python that processes the JSON response and applies the necessary business logic.
Deploy the function to Google Cloud.
Invoke Cloud Function from Workflow:
Modify your Workflow to call the Cloud Function using an HTTP request or Google Cloud Function connector.
steps:
- callCloudFunction:
call: http.post
args:
url: https://REGION-PROJECT_ID.cloudfunctions.net/FUNCTION_NAME
body:
key: value
Process Results:
Handle the response from the Cloud Function and proceed with the next steps in the Workflow, such as loading data into BigQuery.
Reference:
Google Cloud Functions Documentation
Using Workflows with Cloud Functions
Workflows Standard Library
NEW QUESTION # 376
......
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