PROFESSIONAL-DATA-ENGINEER Online Practice Questions and Answers

MJTelco is building a custom interface to share data. They have these requirements:

1.

They need to do aggregations over their petabyte-scale datasets.

2.

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. Cloud Datastore and Cloud Bigtable

B. Cloud Bigtable and Cloud SQL

C. BigQuery and Cloud Bigtable

D. BigQuery and Cloud Storage

Your company's customer and order databases are often under heavy load. This makes performing analytics against them difficult without harming operations. The databases are in a MySQL cluster, with nightly backups taken using mysqldump. You want to perform analytics with minimal impact on operations. What should you do?

A. Add a node to the MySQL cluster and build an OLAP cube there.

B. Use an ETL tool to load the data from MySQL into Google BigQuery.

C. Connect an on-premises Apache Hadoop cluster to MySQL and perform ETL.

D. Mount the backups to Google Cloud SQL, and then process the data using Google Cloud Dataproc.

An external customer provides you with a daily dump of data from their database. The data flows into Google Cloud Storage GCS as comma-separated values (CSV) files. You want to analyze this data in Google BigQuery, but the data could have rows that are formatted incorrectly or corrupted. How should you build this pipeline?

A. Use federated data sources, and check data in the SQL query.

B. Enable BigQuery monitoring in Google Stackdriver and create an alert.

C. Import the data into BigQuery using the gcloud CLI and set max_bad_records to 0.

D. Run a Google Cloud Dataflow batch pipeline to import the data into BigQuery, and push errors to another dead-letter table for analysis.

Your startup has a web application that currently serves customers out of a single region in Asia. You are targeting funding that will allow your startup lo serve customers globally. Your current goal is to optimize for cost, and your post-funding goat is to optimize for global presence and performance. You must use a native JDBC driver. What should you do?

A. Use Cloud Spanner to configure a single region instance initially. and then configure multi-region C oud Spanner instances after securing funding.

B. Use a Cloud SQL for PostgreSQL highly available instance first, and 8table with US.Europe, and Asia replication alter securing funding

C. Use a Cloud SQL for PostgreSQL zonal instance first and Bigtable with US. Europe, and Asia after securing funding.

D. Use a Cloud SOL for PostgreSQL zonal instance first, and Cloud SOL for PostgreSQL with highly available configuration after securing funding.

You have a table that contains millions of rows of sales data, partitioned by date Various applications and users query this data many times a minute. The query requires aggregating values by using avg. max. and sum, and does not require joining to other tables. The required aggregations are only computed over the past year of data, though you need to retain full historical data in the base tables You want to ensure that the query results always include the latest data from the tables, while also reducing computation cost, maintenance overhead, and duration. What should you do?

A. Create a materialized view to aggregate the base table data Configure a partition expiration on the base table to retain only the last one year of partitions.

B. Create a materialized view to aggregate the base table data include a filter clause to specify the last one year of partitions.

C. Create a new table that aggregates the base table data include a filter clause to specify the last year of partitions. Set up a scheduled query to recreate the new table every hour.

D. Create a view to aggregate the base table data Include a filter clause to specify the last year of partitions.

Google Cloud Bigtable indexes a single value in each row. This value is called the _______.

A. primary key

B. unique key

C. row key

D. master key

An aerospace company uses a proprietary data format to store its night data. You need to connect this new data source to BigQuery and stream the data into BigQuery. You want to efficiency import the data into BigQuery where consuming

as few resources as possible.

What should you do?

A. Use a standard Dataflow pipeline to store the raw data m BigQuery and then transform the format later when the data is used

B. Write a she script that triggers a Cloud Function that performs periodic ETL batch jobs on the new data source

C. Use Apache Hive to write a Dataproc job that streams the data into BigQuery in CSV format

D. Use an Apache Beam custom connector to write a Dataflow pipeline that streams the data into BigQuery in Avro format

You need to create a near real-time inventory dashboard that reads the main inventory tables in your BigQuery data warehouse. Historical inventory data is stored as inventory balances by item and location. You have several thousand

updates to inventory every hour. You want to maximize performance of the dashboard and ensure that the data is accurate.

What should you do?

A. Leverage BigQuery UPDATE statements to update the inventory balances as they are changing.

B. Partition the inventory balance table by item to reduce the amount of data scanned with each inventory update.

C. Use the BigQuery streaming the stream changes into a daily inventory movement table.Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.

D. Use the BigQuery bulk loader to batch load inventory changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.

You have several Spark jobs that run on a Cloud Dataproc cluster on a schedule. Some of the jobs run in sequence, and some of the jobs run concurrently. You need to automate this process. What should you do?

A. Create a Cloud Dataproc Workflow Template

B. Create an initialization action to execute the jobs

C. Create a Directed Acyclic Graph in Cloud Composer

D. Create a Bash script that uses the Cloud SDK to create a cluster, execute jobs, and then tear down the cluster

You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing data. Which Stackdriver alerts should you create?

A. An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination

B. An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination

C. An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination

D. An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination