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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

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

2. You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?

A) Consume the stream of data in Cloud Dataflow using Kafka I
B) Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
C) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
D) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
E) Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
F) Set a sliding time window of 1 hour every 5 minute
G) If that number falls below 4000, send an alert.
H) Consume the stream of data in Cloud Dataflow using Kafka I
I) If that number falls below 4000, send an alert.
J) Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
K) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
L) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
M) Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour

3. You architect a system to analyze seismic dat
a. Your extract, transform, and load (ETL) process runs as a series of MapReduce jobs on an Apache Hadoop cluster. The ETL process takes days to process a data set because some steps are computationally expensive. Then you discover that a sensor calibration step has been omitted. How should you change your ETL process to carry out sensor calibration systematically in the future?

A) Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.
B) Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.
C) Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.
D) Develop an algorithm through simulation to predict variance of data output from the last MapReduce job based on calibration factors, and apply the correction to all data.

4. You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

A) Use the WHERE_PARTITIONTIME pseudo column
B) Use the TABLE_DATE_RANGE function
C) Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD
D) Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD

5. Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

A) The with Allowed Lateness method
B) An event time trigger
C) A processing time trigger
D) An hourly watermark

Solutions: