πŸ”

PDE β€” questions

Page 8 of 18 Β· 341 total questions.

Topic 1 Β· Question 141

Data Analysts in your company have the Cloud IAM Owner role assigned to them in their projects to allow them to work with multiple GCP products in their projects. Your organization requires that all BigQuery data access logs be retained for 6 months. You need to ensure that only audit personnel in your company can access the data access logs for all projects. What should you do?

  • AEnable data access logs in each Data Analyst's project. Restrict access to Stackdriver Logging via Cloud IAM roles.
  • BExport the data access logs via a project-level export sink to a Cloud Storage bucket in the Data Analysts' projects. Restrict access to the Cloud Storage bucket.
  • CExport the data access logs via a project-level export sink to a Cloud Storage bucket in a newly created projects for audit logs. Restrict access to the project with the exported logs.
  • DExport the data access logs via an aggregated export sink to a Cloud Storage bucket in a newly created project for audit logs. Restrict access to the project that contains the exported logs. (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Export the data access logs via an aggregated export sink to a Cloud Storage bucket in a newly created project for audit logs. Restrict access to the project that contains the exported logs.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed.

Topic 1 Β· Question 142

Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

  • ACreate a Cloud Monitoring dashboard based on the BigQuery metric query/scanned_bytes
  • BCreate a Cloud Monitoring dashboard based on the BigQuery metric slots/allocated_for_project (correct answer)
  • CCreate a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Cloud Monitoring dashboard based on the custom metric
  • DCreate an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Cloud Monitoring dashboard based on the custom metric
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Create a Cloud Monitoring dashboard based on the BigQuery metric slots/allocated_for_project

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Cloud Monitoring collects metrics, dashboards, and alerts to observe system health.

Topic 1 Β· Question 143

You are operating a streaming Cloud Dataflow pipeline. Your engineers have a new version of the pipeline with a different windowing algorithm and triggering strategy. You want to update the running pipeline with the new version. You want to ensure that no data is lost during the update. What should you do?

  • AUpdate the Cloud Dataflow pipeline inflight by passing the --update option with the --jobName set to the existing job name
  • BUpdate the Cloud Dataflow pipeline inflight by passing the --update option with the --jobName set to a new unique job name
  • CStop the Cloud Dataflow pipeline with the Cancel option. Create a new Cloud Dataflow job with the updated code
  • DStop the Cloud Dataflow pipeline with the Drain option. Create a new Cloud Dataflow job with the updated code (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Stop the Cloud Dataflow pipeline with the Drain option. Create a new Cloud Dataflow job with the updated code

Explanation

Dataflow runs serverless Apache Beam pipelines for stream and batch data processing with autoscaling. This option meets the real-time / low-latency performance requirement.

Topic 1 Β· Question 144

You need to move 2 PB of historical data from an on-premises storage appliance to Cloud Storage within six months, and your outbound network capacity is constrained to 20 Mb/sec. How should you migrate this data to Cloud Storage?

  • AUse Transfer Appliance to copy the data to Cloud Storage (correct answer)
  • BUse gsutil cp ""J to compress the content being uploaded to Cloud Storage
  • CCreate a private URL for the historical data, and then use Storage Transfer Service to copy the data to Cloud Storage
  • DUse trickle or ionice along with gsutil cp to limit the amount of bandwidth gsutil utilizes to less than 20 Mb/sec so it does not interfere with the production traffic
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use Transfer Appliance to copy the data to Cloud Storage

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed. Transfer Appliance physically ships large datasets to Google Cloud when bandwidth is limited.

Topic 1 Β· Question 145

You receive data files in CSV format monthly from a third party. You need to cleanse this data, but every third month the schema of the files changes. Your requirements for implementing these transformations include: β€’ Executing the transformations on a schedule β€’ Enabling non-developer analysts to modify transformations β€’ Providing a graphical tool for designing transformations What should you do?

  • AUse Dataprep by Trifacta to build and maintain the transformation recipes, and execute them on a scheduled basis (correct answer)
  • BLoad each month's CSV data into BigQuery, and write a SQL query to transform the data to a standard schema. Merge the transformed tables together with a SQL query
  • CHelp the analysts write a Dataflow pipeline in Python to perform the transformation. The Python code should be stored in a revision control system and modified as the incoming data's schema changes
  • DUse Apache Spark on Dataproc to infer the schema of the CSV file before creating a Dataframe. Then implement the transformations in Spark SQL before writing the data out to Cloud Storage and loading into BigQuery
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Use Dataprep by Trifacta to build and maintain the transformation recipes, and execute them on a scheduled basis

Explanation

Dataprep visually explores, cleans, and prepares data for analysis with no code.

Topic 1 Β· Question 146 Β· Select all that apply

You want to migrate an on-premises Hadoop system to Cloud Dataproc. Hive is the primary tool in use, and the data format is Optimized Row Columnar (ORC). All ORC files have been successfully copied to a Cloud Storage bucket. You need to replicate some data to the cluster's local Hadoop Distributed File System (HDFS) to maximize performance. What are two ways to start using Hive in Cloud Dataproc? (Choose two.)

  • ARun the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDFS. Mount the Hive tables locally. (correct answer)
  • BRun the gsutil utility to transfer all ORC files from the Cloud Storage bucket to any node of the Dataproc cluster. Mount the Hive tables locally.
  • CRun the gsutil utility to transfer all ORC files from the Cloud Storage bucket to the master node of the Dataproc cluster. Then run the Hadoop utility to copy them do HDFS. Mount the Hive tables from HDFS.
  • DLeverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive tables. Replicate external Hive tables to the native ones. (correct answer)
  • ELoad the ORC files into BigQuery. Leverage BigQuery connector for Hadoop to mount the BigQuery tables as external Hive tables. Replicate external Hive tables to the native ones.
Reveal answer & explanation
Correct answer: A, D

The correct answer is A, D. Option A: Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDFS. Mount the Hive tables locally. Option D: Leverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive tables. Replicate external Hive tables to the native ones.

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed.

Topic 1 Β· Question 147

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?

  • ACloud Scheduler
  • BCloud Dataflow
  • CCloud Functions
  • DCloud Composer (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Cloud Composer

Explanation

Cloud Composer is managed Apache Airflow for orchestrating multi-step data workflows.

Topic 1 Β· Question 148

You work for a shipping company that has distribution centers where packages move on delivery lines to route them properly. The company wants to add cameras to the delivery lines to detect and track any visual damage to the packages in transit. You need to create a way to automate the detection of damaged packages and flag them for human review in real time while the packages are in transit. Which solution should you choose?

  • AUse BigQuery machine learning to be able to train the model at scale, so you can analyze the packages in batches.
  • BTrain an AutoML model on your corpus of images, and build an API around that model to integrate with the package tracking applications. (correct answer)
  • CUse the Cloud Vision API to detect for damage, and raise an alert through Cloud Functions. Integrate the package tracking applications with this function.
  • DUse TensorFlow to create a model that is trained on your corpus of images. Create a Python notebook in Cloud Datalab that uses this model so you can analyze for damaged packages.
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Train an AutoML model on your corpus of images, and build an API around that model to integrate with the package tracking applications.

Explanation

AutoML trains high-quality custom models from your data with minimal ML expertise. This option meets the real-time / low-latency performance requirement.

Topic 1 Β· Question 149

You are migrating your data warehouse to BigQuery. You have migrated all of your data into tables in a dataset. Multiple users from your organization will be using the data. They should only see certain tables based on their team membership. How should you set user permissions?

  • AAssign the users/groups data viewer access at the table level for each table
  • BCreate SQL views for each team in the same dataset in which the data resides, and assign the users/groups data viewer access to the SQL views
  • CCreate authorized views for each team in the same dataset in which the data resides, and assign the users/groups data viewer access to the authorized views
  • DCreate authorized views for each team in datasets created for each team. Assign the authorized views data viewer access to the dataset in which the data resides. Assign the users/groups data viewer access to the datasets in which the authorized views reside (correct answer)
Reveal answer & explanation
Correct answer: D

The correct answer is D. Option D: Create authorized views for each team in datasets created for each team. Assign the authorized views data viewer access to the dataset in which the data resides. Assign the users/groups data viewer access to the datas...

Topic 1 Β· Question 150

You want to build a managed Hadoop system as your data lake. The data transformation process is composed of a series of Hadoop jobs executed in sequence. To accomplish the design of separating storage from compute, you decided to use the Cloud Storage connector to store all input data, output data, and intermediary data. However, you noticed that one Hadoop job runs very slowly with Cloud Dataproc, when compared with the on-premises bare-metal Hadoop environment (8-core nodes with 100-GB RAM). Analysis shows that this particular Hadoop job is disk I/O intensive. You want to resolve the issue. What should you do?

  • AAllocate sufficient memory to the Hadoop cluster, so that the intermediary data of that particular Hadoop job can be held in memory
  • BAllocate sufficient persistent disk space to the Hadoop cluster, and store the intermediate data of that particular Hadoop job on native HDFS (correct answer)
  • CAllocate more CPU cores of the virtual machine instances of the Hadoop cluster so that the networking bandwidth for each instance can scale up
  • DAllocate additional network interface card (NIC), and configure link aggregation in the operating system to use the combined throughput when working with Cloud Storage
Reveal answer & explanation
Correct answer: B

The correct answer is B. Option B: Allocate sufficient persistent disk space to the Hadoop cluster, and store the intermediate data of that particular Hadoop job on native HDFS

Explanation

Persistent Disk provides durable block storage attached to Compute Engine VMs.

Topic 1 Β· Question 151

You work for an advertising company, and you've developed a Spark ML model to predict click-through rates at advertisement blocks. You've been developing everything at your on-premises data center, and now your company is migrating to Google Cloud. Your data center will be closing soon, so a rapid lift-and-shift migration is necessary. However, the data you've been using will be migrated to migrated to BigQuery. You periodically retrain your Spark ML models, so you need to migrate existing training pipelines to Google Cloud. What should you do?

  • AUse Vertex AI for training existing Spark ML models
  • BRewrite your models on TensorFlow, and start using Vertex AI
  • CUse Dataproc for training existing Spark ML models, but start reading data directly from BigQuery (correct answer)
  • DSpin up a Spark cluster on Compute Engine, and train Spark ML models on the data exported from BigQuery
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Use Dataproc for training existing Spark ML models, but start reading data directly from BigQuery

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Dataproc runs managed Spark and Hadoop clusters for big-data processing.

Topic 1 Β· Question 152

You work for a global shipping company. You want to train a model on 40 TB of data to predict which ships in each geographic region are likely to cause delivery delays on any given day. The model will be based on multiple attributes collected from multiple sources. Telemetry data, including location in GeoJSON format, will be pulled from each ship and loaded every hour. You want to have a dashboard that shows how many and which ships are likely to cause delays within a region. You want to use a storage solution that has native functionality for prediction and geospatial processing. Which storage solution should you use?

  • ABigQuery (correct answer)
  • BCloud Bigtable
  • CCloud Datastore
  • DCloud SQL for PostgreSQL
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: BigQuery

Explanation

BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage.

Topic 1 Β· Question 153

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?

  • AConsume the stream of data in Dataflow using Kafka IO. Set a sliding time window of 1 hour every 5 minutes. Compute the average when the window closes, and send an alert if the average is less than 4000 messages. (correct answer)
  • BConsume the stream of data in Dataflow using Kafka IO. 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.
  • CUse Kafka Connect to link your Kafka message queue to Pub/Sub. Use a Dataflow template to write your messages from Pub/Sub to Bigtable. Use Cloud Scheduler to run a script every hour that counts the number of rows created in Bigtable in the last hour. If that number falls below 4000, send an alert.
  • DUse Kafka Connect to link your Kafka message queue to Pub/Sub. Use a Dataflow template to write your messages from Pub/Sub to BigQuery. Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour. If that number falls below 4000, send an alert.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Consume the stream of data in Dataflow using Kafka IO. Set a sliding time window of 1 hour every 5 minutes. Compute the average when the window closes, and send an alert if the average is less than 4000 messages.

Explanation

Dataflow runs serverless Apache Beam pipelines for stream and batch data processing with autoscaling.

Topic 1 Β· Question 154

You plan to deploy Cloud SQL using MySQL. You need to ensure high availability in the event of a zone failure. What should you do?

  • ACreate a Cloud SQL instance in one zone, and create a failover replica in another zone within the same region. (correct answer)
  • BCreate a Cloud SQL instance in one zone, and create a read replica in another zone within the same region.
  • CCreate a Cloud SQL instance in one zone, and configure an external read replica in a zone in a different region.
  • DCreate a Cloud SQL instance in a region, and configure automatic backup to a Cloud Storage bucket in the same region.
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Create a Cloud SQL instance in one zone, and create a failover replica in another zone within the same region.

Explanation

Cloud SQL is a managed relational database (MySQL/PostgreSQL/SQL Server) that handles patching, backups, and failover.

Topic 1 Β· Question 155

Your company is selecting a system to centralize data ingestion and delivery. You are considering messaging and data integration systems to address the requirements. The key requirements are: β€’ The ability to seek to a particular offset in a topic, possibly back to the start of all data ever captured β€’ Support for publish/subscribe semantics on hundreds of topics Retain per-key ordering - Which system should you choose?

  • AApache Kafka (correct answer)
  • BCloud Storage
  • CDataflow
  • DFirebase Cloud Messaging
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Apache Kafka.

Topic 1 Β· Question 156

You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?

  • ADeploy a Dataproc cluster. Use a standard persistent disk and 50% preemptible workers. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs:// (correct answer)
  • BDeploy a Dataproc cluster. Use an SSD persistent disk and 50% preemptible workers. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
  • CInstall Hadoop and Spark on a 10-node Compute Engine instance group with standard instances. Install the Cloud Storage connector, and store the data in Cloud Storage. Change references in scripts from hdfs:// to gs://
  • DInstall Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances. Store data in HDFS. Change references in scripts from hdfs:// to gs://
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Deploy a Dataproc cluster. Use a standard persistent disk and 50% preemptible workers. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://

Explanation

Preemptible/Spot VMs use spare capacity at a large discount for fault-tolerant, interruptible work. Cloud Storage provides durable, scalable object storage that is fully managed. Persistent Disk provides durable block storage attached to Compute Engine VMs. This option delivers the requirement at the lowest cost.

Topic 1 Β· Question 157

Your team is working on a binary classification problem. You have trained a support vector machine (SVM) classifier with default parameters, and received an area under the Curve (AUC) of 0.87 on the validation set. You want to increase the AUC of the model. What should you do?

  • APerform hyperparameter tuning (correct answer)
  • BTrain a classifier with deep neural networks, because neural networks would always beat SVMs
  • CDeploy the model and measure the real-world AUC; it's always higher because of generalization
  • DScale predictions you get out of the model (tune a scaling factor as a hyperparameter) in order to get the highest AUC
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Perform hyperparameter tuning.

Topic 1 Β· Question 158

You need to deploy additional dependencies to all nodes of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

  • ADeploy the Cloud SQL Proxy on the Cloud Dataproc master
  • BUse an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
  • CCopy all dependencies to a Cloud Storage bucket within your VPC security perimeter (correct answer)
  • DUse Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter

Explanation

Cloud Storage provides durable, scalable object storage that is fully managed. A VPC provides a global, software-defined private network for your Google Cloud resources.

Topic 1 Β· Question 159

You need to choose a database for a new project that has the following requirements: β€’ Fully managed β€’ Able to automatically scale up β€’ Transactionally consistent β€’ Able to scale up to 6 TB β€’ Able to be queried using SQL Which database do you choose?

  • ACloud SQL
  • BCloud Bigtable
  • CCloud Spanner (correct answer)
  • DCloud Datastore
Reveal answer & explanation
Correct answer: C

The correct answer is C. Option C: Cloud Spanner

Explanation

Cloud Spanner is a horizontally scalable, strongly consistent relational database with global reach.

Topic 1 Β· Question 160

You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?

  • ACloud SQL (correct answer)
  • BCloud Bigtable
  • CCloud Spanner
  • DCloud Datastore
Reveal answer & explanation
Correct answer: A

The correct answer is A. Option A: Cloud SQL

Explanation

Cloud SQL is a managed relational database (MySQL/PostgreSQL/SQL Server) that handles patching, backups, and failover.

Showing questions 141–160 of 341 Β· Page 8 of 18