Dataproc for Spark/Hadoop in GCP - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Google Cloud Dataproc?

Google Cloud Dataproc is a managed service that lets you run Apache Spark and Hadoop clusters quickly and easily without managing the infrastructure yourself.

beginner

How does Dataproc simplify running Spark and Hadoop jobs?

Dataproc automates cluster creation, scaling, and management, so you can focus on your data processing tasks instead of setting up and maintaining servers.

beginner

What is a cluster in Dataproc?

A cluster is a group of virtual machines that work together to run Spark or Hadoop jobs. Dataproc creates and manages these clusters for you.

intermediate

Why is autoscaling useful in Dataproc clusters?

Autoscaling adjusts the number of machines in your cluster automatically based on workload, saving money when demand is low and providing power when demand is high.

beginner

What storage options does Dataproc support for data processing?

Dataproc can use Google Cloud Storage buckets as the main storage for input and output data, which is scalable and easy to manage.

What does Google Cloud Dataproc primarily manage for you?

A Managing user accounts

B Writing Spark code

C Creating databases

D Infrastructure and cluster management

Dataproc automates the setup and management of clusters, so you don't have to manage the infrastructure yourself.

Which of these is NOT a component you run on Dataproc clusters?

A Google BigQuery

B Apache Hadoop

C Apache Spark

D Apache Hive

BigQuery is a separate Google Cloud service for data warehousing, not run on Dataproc clusters.

What is the benefit of autoscaling in Dataproc?

A It creates storage buckets

B It automatically writes Spark code

C It adjusts cluster size based on workload

D It manages user permissions

Autoscaling changes the number of machines in your cluster to match the workload, optimizing cost and performance.

Where does Dataproc typically store input and output data?

A Google Cloud Storage buckets

B On-premises servers

C Local cluster disks only

D Google Drive

Dataproc uses Google Cloud Storage buckets for scalable and reliable data storage.

How quickly can Dataproc create a cluster?

A Several hours

B A few minutes

C Several days

D Instantly without any setup

Dataproc can create clusters in a few minutes, making it fast to start processing data.

Explain how Dataproc helps you run Spark or Hadoop jobs without managing servers.

Think about what tasks Dataproc takes off your hands.

Describe the role of autoscaling in Dataproc clusters and why it matters.

Consider how changing the number of machines helps.