GCP-ADP Hard Questions — 25 Difficult Questions

Question 1

You are building a Looker model and want to create a measure that calculates the count of distinct customers. Which type of measure should you use?

Accepted Answer

type: count_distinct. The `count_distinct` type is specifically designed for calculating unique occurrences in LookML.

Answer

type: count

Answer

type: average_distinct

Answer

type: sum_distinct

Question 2

Which THREE of the following are common administrative tasks when managing a Dataplex Lake? (Choose three)

Accepted Answer

Adding and removing data assets. Admins handle access, assets, and task scheduling.

Answer

Manually editing individual data files

Answer

Rebuilding the physical database indexes

Question 3

You are using Dataflow to read from Pub/Sub. The pipeline is failing due to malformed messages. How can you handle these without crashing?

Accepted Answer

Use a Dead Letter Queue (DLQ). Using a Dead Letter Queue (DLQ) pattern allows you to route unprocessable messages to a separate destination for inspection.

Answer

Ignore errors

Answer

Increase memory

Answer

Restart the pipeline

Question 4

A user is running a query on a BigQuery table with nested data (JSON). How do you access a field named 'city' inside a record field named 'address'?

Accepted Answer

address.city. Standard SQL uses the dot notation (dot-walk) to access fields within a STRUCT.

Answer

address->city

Answer

address[city]

Answer

JSON_EXTRACT(address, '$.city')

Question 5

When setting up a Dataplex Lake, you chose the 'Multi-region' location type. What is the implication of this choice?

Accepted Answer

It improves data availability and durability. Multi-region deployment increases availability and ensures data is replicated across multiple regions within the same geography.

Answer

It restricts access to users in a single region

Answer

It prevents the use of BigQuery datasets

Answer

It reduces the cost of storing data

Question 6

You are configuring a Dataplex Data Quality task. You want to validate that a 'user_id' column has no NULL values. Where do you define this rule?

Accepted Answer

In a YAML configuration file. Data quality rules are defined in a YAML configuration file that Dataplex uses to run the quality check task.

Answer

In the Cloud Storage metadata

Answer

In the BigQuery table schema

Answer

In the Dataplex Asset definition

Question 7

You are creating a Looker report with a 'measure' that calculates the total revenue. You notice it is summing correctly but the format is wrong. Where do you change the format?

Accepted Answer

In the LookML view file using 'value_format_name'.. The 'value_format_name' or 'value_format' parameter in the LookML view definition is where you control display formatting.

Answer

In the dashboard filter settings.

Answer

By editing the underlying SQL.

Answer

In the 'User' settings.

Question 8

You have noticed that your data quality tasks are failing. Which THREE of the following are potential causes for failure? (Choose three)

Accepted Answer

The YAML rule configuration is malformed. Common failures include permission issues, invalid rule configurations, or missing execution environments.

Answer

The user has a slow internet connection

Answer

The data files were moved to another lake

Question 9

In LookML, which parameter is used to define how a table should join to another?

Accepted Answer

relationship. The 'relationship' parameter is essential for Looker to join tables correctly without errors.

Answer

join_type

Answer

dimension_group

Answer

foreign_key

Question 10

A Cloud Composer DAG is failing because the Airflow database is locking up during high-concurrency periods. What is the most effective way to address this?

Accepted Answer

Scale up the Cloud Composer environment size to increase database resources.. Scaling the Composer environment or adjusting the database performance settings (or Airflow configuration) is the recommended path to resolve lock contention.

Answer

Delete all past DAG run logs.

Answer

Increase the number of DAGs in the repository.

Answer

Set the 'parallelism' parameter to a very high value.

Question 11

You need to ingest data from an external API that requires an OAuth token. Which tool is best for executing this periodically?

Accepted Answer

Cloud Functions. Cloud Functions triggered by Cloud Scheduler can handle API requests with custom authentication logic.

Answer

Pub/Sub

Answer

BigQuery Data Transfer Service

Answer

Storage Transfer Service

Question 12

You are troubleshooting a Dataflow job that is running slower than expected when writing data to BigQuery. You suspect the issue is related to hot keys. What is the recommended strategy to mitigate this?

Accepted Answer

Add a random salt to the key before the shuffle operation. Keyed distribution issues can be solved by adding a random salt to keys to ensure better distribution across workers.

Answer

Change the Dataflow runner to a different region

Answer

Increase the number of worker machines

Answer

Use Cloud Storage as an intermediate sink

Question 13

Which TWO actions can help reduce the time it takes to build a Jupyter notebook in Vertex AI Workbench?

Accepted Answer

Scaling up the machine type for the instance. Optimizing compute and pre-installing environments can speed up development.

Answer

Change the project name

Answer

Disable the persistent disk

Answer

Using a single-core machine

Question 14

Which THREE of these are valid ways to monitor or analyze BigQuery performance?

Accepted Answer

Query Plan explanation. Performance analysis is done via metadata views, query plans, and monitoring dashboards.

Answer

Editing the table schema

Answer

Changing the project billing currency

Question 15

You want to perform data quality checks on a BigQuery table that is updated daily. How should you schedule the Dataplex task?

Accepted Answer

Configure a CRON schedule on the task. Dataplex tasks can be triggered on a schedule using cron syntax, allowing for daily alignment with data updates.

Answer

Manually trigger via the UI

Answer

Wait for discovery to trigger it

Answer

Use Cloud Run to trigger the task

Question 16

You notice your Looker dashboard is showing duplicate data. What is the most likely cause?

Accepted Answer

Fan-out due to a join without correctly defined primary keys.. Fan-outs occur when joining a one-to-many relationship without correctly defining the primary key or using the correct aggregate type.

Answer

The data is cached in the browser.

Answer

The user is logged in twice.

Answer

The BigQuery table is corrupted.

Question 17

In a Cloud Composer DAG, you need to trigger a BigQuery job that runs as a service account other than the one assigned to the GKE nodes. How should you implement this?

Accepted Answer

Use the 'impersonation_chain' parameter in the BigQueryInsertJobOperator.. Using the 'impersonation_chain' parameter in the BigQueryInsertJobOperator allows the service account running the task to impersonate a different service account.

Answer

Hardcode the credentials in a JSON file inside the DAG folder.

Answer

Change the worker node's identity in the Cloud Console.

Answer

Configure a connection with the 'Service Account Key' type in Airflow UI.

Question 18

You need to run a Workflows execution based on a schedule. Which Google Cloud service is designed to manage this triggering?

Accepted Answer

Cloud Scheduler. Cloud Scheduler is the fully managed service for scheduling jobs, including triggers for Workflows.

Answer

Eventarc

Answer

Cloud Tasks

Answer

Pub/Sub

Question 19

You are using Dataflow with autoscaling. What metric determines whether the worker pool scales up or down?

Accepted Answer

Work backlog and throughput. Dataflow autoscaling is based on the backlog of work and CPU usage of current workers.

Answer

Network latency

Answer

Memory usage

Answer

User-defined triggers

Question 20

A task in your Airflow DAG involves a long-running process that might exceed the default Airflow worker pod timeout. How should you handle this?

Accepted Answer

Set the 'execution_timeout' parameter on the task instance.. Adjust the 'execution_timeout' parameter for the specific task in the Airflow DAG definition to allow longer processing times.

Answer

Move the task to a custom node pool in GKE.

Answer

Increase the 'default_dag_run_timeout'.

Answer

Decrease the number of parallel tasks.