Minimize Costs and Infrastructure Management Effort: Hadoop Job Migration Guide

A.

To migrate Hadoop jobs for your company's Data Science team without modifying the underlying infrastructure and minimize costs and infrastructure management effort, you should choose option B: Create a Dataproc cluster using preemptible worker instances.

Dataproc is a fully-managed cloud service that lets you easily run Apache Hadoop and Apache Spark jobs. With Dataproc, you can create a Hadoop cluster quickly and easily, without having to manually deploy and configure the underlying infrastructure. Dataproc provides a number of features that help you optimize the performance and cost of your Hadoop jobs, including auto-scaling, cluster management, and monitoring.

Preemptible worker instances are a cost-effective option for running Hadoop jobs in Dataproc. These instances are the same as regular Compute Engine instances, but with the caveat that Google may reclaim them at any time with a 30-second warning. Because preemptible instances are priced at a significant discount compared to regular instances, they can help you save money on your Hadoop jobs.

Here are some additional reasons why choosing option B is the best choice:

• Option A: Creating a Dataproc cluster using standard worker instances is a viable option, but it would likely be more expensive than using preemptible instances. Standard instances are priced at a premium compared to preemptible instances, which would increase the cost of running your Hadoop jobs.
• Option C: Manually deploying a Hadoop cluster on Compute Engine using standard instances would be a more complex and time-consuming option than using Dataproc. You would need to manually provision and configure the infrastructure, which would require more effort and resources.
• Option D: Manually deploying a Hadoop cluster on Compute Engine using preemptible instances would be less efficient and more time-consuming than using Dataproc. You would need to manually provision and configure the infrastructure, and you would not have access to Dataproc's management and monitoring features.

In summary, creating a Dataproc cluster using preemptible worker instances is the most cost-effective and efficient option for migrating Hadoop jobs for your company's Data Science team.