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Google Data Engineer Sample Questions:

1. You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the dat a. Which two actions should you take? (Choose two.)

A) Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
B) Configure your Cloud Dataflow pipeline to use local execution
C) Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
D) Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
E) Increase the number of nodes in the Cloud Bigtable cluster

2. Which of these is not a supported method of putting data into a partitioned table?

A) Create a partitioned table and stream new records to it every day.
B) Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".
C) Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".
D) If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.

3. 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) Monitor the total execution time for a sampling of job
B) Use the default autoscaling setting for worker instances.
C) Use Cloud Dataflow to run your transformation
D) Use the diagnose command to generate an operational output archiv
E) Locate the bottleneck and adjust cluster resources.
F) Use Cloud Dataproc to run your transformation
G) Monitor the job system lag with Stackdrive
H) Configure the job to use non-default Compute Engine machine types when needed.
I) Use Cloud Dataproc to run your transformation
J) Use Cloud Dataflow to run your transformation
K) Resize the number of worker nodes in your cluster via the command line.
L) Monitor CPU utilization for the cluste

4. If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?

A) Run your test for at least 10 minutes.
B) Do not use a production instance.
C) Use at least 300 GB of data.
D) Before you test, run a heavy pre-test for several minutes.

5. MJTelco is building a custom interface to share dat
a. They have these requirements:
They need to do aggregations over their petabyte-scale datasets.
They need to scan specific time range rows with a very fast response time (milliseconds). Which combination of Google Cloud Platform products should you recommend?

A) BigQuery and Cloud Bigtable
B) BigQuery and Cloud Storage
C) Cloud Bigtable and Cloud SQL
D) Cloud Datastore and Cloud Bigtable

Solutions: