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Google Data Engineer Sample Questions:

1. You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?

A) Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
B) Store the data in a file in a regional Google Cloud Storage bucke
C) Load the data every 30 minutes into a new partitioned table in BigQuery.
D) Store the data in Google Cloud Datastor
E) Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
F) Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.

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

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

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

A) 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".
B) Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".
C) 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.
D) Create a partitioned table and stream new records to it every day.

5. You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?

A) Cloud Dataflow
B) Cloud Composer
C) Cloud Scheduler
D) Cloud Functions

Solutions: