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Professional-Data-Engineer Practice Questions

Question # 1

You need to store and analyze social media postings in Google BigQuery at a rate of
10,000 messages per minute in near real-time. Initially, design the application to use
streaming inserts for individual postings. Your application also performs data aggregations
right after the streaming inserts. You discover that the queries after streaming inserts do
not exhibit strong consistency, and reports from the queries might miss in-flight data. How
can you adjust your application design?

A.

Re-write the application to load accumulated data every 2 minutes.

B.

Convert the streaming insert code to batch load for individual messages.

C.

Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.

D.

Estimate the average latency for data availability after streaming inserts, and always run
queries after waiting twice as long.



A.

Re-write the application to load accumulated data every 2 minutes.




Question # 2

Flowlogistic’s management has determined that the current Apache Kafka servers cannot
handle the data volume for their real-time inventory tracking system. You need to build a
new system on Google Cloud Platform (GCP) that will feed the proprietary tracking
software. The system must be able to ingest data from a variety of global sources, process
and query in real-time, and store the data reliably. Which combination of GCP products
should you choose?

A.

Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage

B.

Cloud Pub/Sub, Cloud Dataflow, and Local SSD

C.

Cloud Pub/Sub, Cloud SQL, and Cloud Storage

D.

Cloud Load Balancing, Cloud Dataflow, and Cloud Storage



C.

Cloud Pub/Sub, Cloud SQL, and Cloud Storage




Question # 3

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

A.

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.

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.

Create a partitioned table and stream new records to it every day.

D.

Use ORDER BY to put a table's rows into chronological order and then change the table's type to
"Partitioned".



D.

Use ORDER BY to put a table's rows into chronological order and then change the table's type to
"Partitioned".


Explanation
You cannot change an existing table into a partitioned table. You must create a partitioned table from scratch.
Then you can either stream data into it every day and the data will automatically be put in the right partition,
or you can load data into a specific partition by using "$YYYYMMDD" at the end of the table name.



Question # 4

Which of these sources can you not load data into BigQuery from?

A.

File upload

B.

Google Drive

C.

Google Cloud Storage

D.

Google Cloud SQL



D.

Google Cloud SQL


You can load data into BigQuery from a file upload, Google Cloud Storage, Google Drive, or Google Cloud
Bigtable. It is not possible to load data into BigQuery directly from Google Cloud SQL. One way to get data
from Cloud SQL to BigQuery would be to export data from Cloud SQL to Cloud Storage and then load it from
there.



Question # 5

When you store data in Cloud Bigtable, what is the recommended minimum amount of stored data?

A.

500 TB

B.

1 GB

C.

1 TB
500 GB

D.

500 GB



C.

1 TB
500 GB


Explanation
Cloud Bigtable is not a relational database. It does not support SQL queries, joins, or multi-row transactions. It
is not a good solution for less than 1 TB of data.



Question # 6

You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need
an instant notification to be sent to your monitoring tool when new data is appended to a
certain table using an insert job, but you do not want to receive notifications for other
tables. What should you do?

A.

Make a call to the Stackdriver API to list all logs, and apply an advanced filter.

B.

In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.

C.

In the Stackdriver logging admin interface, enable a log sink export to Google Cloud
Pub/Sub, and subscribe to the topic from your monitoring tool.

D.

Using the Stackdriver API, create a project sink with advanced log filter to export to
Pub/Sub, and subscribe to the topic from your monitoring tool.



B.

In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.




Question # 7

What are two of the characteristics of using online prediction rather than batch prediction?

A.

It is optimized to handle a high volume of data instances in a job and to run more complex models.

B.

Predictions are returned in the response message.

C.

Predictions are written to output files in a Cloud Storage location that you specify.

D.

It is optimized to minimize the latency of serving predictions



B.

Predictions are returned in the response message.


D.

It is optimized to minimize the latency of serving predictions


Explanation
Online prediction
Optimized to minimize the latency of serving predictions.
Predictions returned in the response message.
Batch prediction
Optimized to handle a high volume of instances in a job and to run more complex models.
Predictions written to output files in a Cloud Storage location that you specify.



Question # 8

Which of the following statements is NOT true regarding Bigtable access roles?

A.

Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a
project.

B.

To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.

C.

You can configure access control only at the project level.

D.

To give a user access to only one table in a project, you must configure access through your application



B.

To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.


Explanation
For Cloud Bigtable, you can configure access control at the project level. For example, you can grant the
ability to:
Read from, but not write to, any table within the project.
Read from and write to any table within the project, but not manage instances.
Read from and write to any table within the project, and manage instances



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