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Google Data Engineer Sample Questions:
1. You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?
A) Use Cloud Dataproc to run your transformation
B) Monitor CPU utilization for the cluste
C) Monitor the total execution time for a sampling of job
D) Monitor the job system lag with Stackdrive
E) Use Cloud Dataproc to run your transformation
F) Use the default autoscaling setting for worker instances.
G) Use Cloud Dataflow to run your transformation
H) Use the diagnose command to generate an operational output archiv
I) Locate the bottleneck and adjust cluster resources.
J) Configure the job to use non-default Compute Engine machine types when needed.
K) Resize the number of worker nodes in your cluster via the command line.
L) Use Cloud Dataflow to run your transformation
2. By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?
A) Single, Global Window
B) Windows at every 1 minute
C) Windows at every 10 minutes
D) Windows at every 100 MB of data
3. The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster .
A) worker node
B) master node
C) application node
D) conditional node
4. Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)
A) Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
B) Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
C) Introduce data compression for each file to increase the rate file of file transfer.
D) Assemble 1,000 files into a tape archive (TAR) fil
E) Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.
F) Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
5. You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?
A) Use Cloud SQL for storag
B) Add secondary indexes to support query patterns.
C) Use Cloud Dataflow to transform data to support query patterns.
D) Use Cloud SQL for storag
E) Use Cloud Spanner for storag
F) Add secondary indexes to support query patterns.
G) Use Cloud Dataflow to transform data to support query patterns.
H) Use Cloud Spanner for storag
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: A,B | Question # 5 Answer: G |



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