Home / Google / Professional Data Engineer

Google Professional Data Engineer Practice Test - Questions Answers, Page 27

Question list

List of questions

Question 261

(0)

You've migrated a Hadoop job from an on-premises cluster to Dataproc and Good Storage. Your Spark job is a complex analytical workload fiat consists of many shuffling operations, and initial data ar

Question 262

(0)

Your company currently runs a large on-premises cluster using Spark Hive and Hadoop Distributed File System (HDFS) in a colocation facility. The duster is designed to support peak usage on the syste

Question 263

(0)

You are collecting loT sensor data from millions of devices across the world and storing the data in BigQuery. Your access pattern is based on recent data tittered by location_id and device_version

Question 264

(0)

You want to optimize your queries for cost and performance. How should you structure your data?

Question 265

(0)

A live TV show asks viewers to cast votes using their mobile phones. The event generates a large volume of data during a 3 minute period. You are in charge of the Voting restructure* and must ensure

Question 266

(0)

You are updating the code for a subscriber to a Put/Sub feed. You are concerned that upon deployment the subscriber may erroneously acknowledge messages, leading to message loss. You subscriber is n

Question 267

(0)

Government regulations in the banking industry mandate the protection of client's personally identifiable information (PII). Your company requires PII to be access controlled encrypted and compliant

Question 268

(0)

You are migrating a table to BigQuery and are deeding on the data model. Your table stores information related to purchases made across several store locations and includes information like the time

Question 269

(0)

You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning process. You want to support a logistic regression model. You also need to mon

Question 270

(0)

You have an Oracle database deployed in a VM as part of a Virtual Private Cloud (VPC) network. You want to replicate and continuously synchronize 50 tables to BigQuery. You want to minimize the need

Related questions

What are all of the BigQuery operations that Google charges for?

You are designing a data mesh on Google Cloud by using Dataplex to manage data in BigQuery and Cloud Storage. You want to simplify data asset permissions. You are creating a customer virtual lake with two user groups: * Data engineers, which require lull data lake access * Analytic users, which require access to curated data You need to assign access rights to these two groups. What should you do?

Your infrastructure team has set up an interconnect link between Google Cloud and the on-premises network. You are designing a high-throughput streaming pipeline to ingest data in streaming from an Apache Kafka cluster hosted on-premises. You want to store the data in BigQuery, with as minima! latency as possible. What should you do?

You are designing the architecture to process your data from Cloud Storage to BigQuery by using Dataflow. The network team provided you with the Shared VPC network and subnetwork to be used by your pipelines. You need to enable the deployment of the pipeline on the Shared VPC network. What should you do?

You need to connect multiple applications with dynamic public IP addresses to a Cloud SQL instance. You configured users with strong passwords and enforced the SSL connection to your Cloud SOL instance. You want to use Cloud SQL public IP and ensure that you have secured connections. What should you do?

Your company built a TensorFlow neural-network model with a large number of neurons and layers. The model fits well for the training dat a. However, when tested against new data, it performs poorly. What method can you employ to address this?

You have a BigQuery table that ingests data directly from a Pub/Sub subscription. The ingested data is encrypted with a Google-managed encryption key. You need to meet a new organization policy that requires you to use keys from a centralized Cloud Key Management Service (Cloud KMS) project to encrypt data at rest. What should you do?

You are using BigQuery with a regional dataset that includes a table with the daily sales volumes. This table is updated multiple times per day. You need to protect your sales table in case of regional failures with a recovery point objective (RPO) of less than 24 hours, while keeping costs to a minimum. What should you do?

You are running your BigQuery project in the on-demand billing model and are executing a change data capture (CDC) process that ingests data. The CDC process loads 1 GB of data every 10 minutes into a temporary table, and then performs a merge into a 10 TB target table. This process is very scan intensive and you want to explore options to enable a predictable cost model. You need to create a BigQuery reservation based on utilization information gathered from BigQuery Monitoring and apply the reservation to the CDC process. What should you do?

You work for a large real estate firm and are preparing 6 TB of home sales data lo be used for machine learning You will use SOL to transform the data and use BigQuery ML lo create a machine learning model. You plan to use the model for predictions against a raw dataset that has not been transformed. How should you set up your workflow in order to prevent skew at prediction time?

Question 261

You've migrated a Hadoop job from an on-premises cluster to Dataproc and Good Storage. Your Spark job is a complex analytical workload fiat consists of many shuffling operations, and initial data are parquet toes (on average 200-400 MB size each) You see some degradation in performance after the migration to Dataproc so you'd like to optimize for it. Your organization is very cost-sensitive so you'd Idee to continue using Dataproc on preemptibles (with 2 non-preemptibles workers only) for this workload. What should you do?

Switch from HODs to SSDs override the preemptible VMs configuration to increase the boot disk size

Increase the see of your parquet files to ensure them to be 1 GB minimum

Switch to TFRecords format (appr 200 MB per We) instead of parquet files

Switch from HDDs to SSDs. copy initial data from Cloud Storage to Hadoop Distributed File System (HDFS) run the Spark job and copy results back to Cloud Storage

Show Answer Comment (0)

Question 262

Your company currently runs a large on-premises cluster using Spark Hive and Hadoop Distributed File System (HDFS) in a colocation facility. The duster is designed to support peak usage on the system, however, many jobs are batch n nature, and usage of the cluster fluctuates quite dramatically.

Your company is eager to move to the cloud to reduce the overhead associated with on-premises infrastructure and maintenance and to benefit from the cost savings. They are also hoping to modernize their existing infrastructure to use more servers offerings m order to take advantage of the cloud Because of the tuning of their contract renewal with the colocation facility they have only 2 months for their initial migration How should you recommend they approach thee upcoming migration strategy so they can maximize their cost savings in the cloud will still executing the migration in time?

Migrate the workloads to Dataproc plus HOPS, modernize later

Migrate the workloads to Dataproc plus Cloud Storage modernize later

Migrate the Spark workload to Dataproc plus HDFS, and modernize the Hive workload for BigQuery

Modernize the Spark workload for Dataflow and the Hive workload for BigQuery

Show Answer Comment (0)

Question 263

You are collecting loT sensor data from millions of devices across the world and storing the data in BigQuery. Your access pattern is based on recent data tittered by location_id and device_version with the following query:

You want to optimize your queries for cost and performance. How should you structure your data?

Partition table data by create_date, location_id and device_version

Partition table data by create_date cluster table data by tocation_id and device_version

Cluster table data by create_date location_id and device_version

Cluster table data by create_date, partition by location and device_version

Show Answer Comment (0)

Question 264

You want to optimize your queries for cost and performance. How should you structure your data?

Partition table data by create_date, location_id and device_version

Partition table data by create_date cluster table data by location_Id and device_version

Cluster table data by create_date location_id and device_version

Cluster table data by create_date partition by locationed and device_version

Show Answer Comment (0)

Question 265

A live TV show asks viewers to cast votes using their mobile phones. The event generates a large volume of data during a 3 minute period. You are in charge of the Voting restructure* and must ensure that the platform can handle the load and Hal all votes are processed. You must display partial results write voting is open. After voting doses you need to count the votes exactly once white optimizing cost. What should you do?

Create a Memorystore instance with a high availability (HA) configuration

Write votes to a Pub Sub tope and have Cloud Functions subscribe to it and write voles to BigQuery

Write votes to a Pub/Sub tope and toad into both Bigtable and BigQuery via a Dataflow pipeline Query Bigtable for real-time results and BigQuery for later analysis Shutdown the Bigtable instance when voting concludesD Create a Cloud SQL for PostgreSQL database with high availability (HA) configuration and multiple read replicas

Show Answer Comment (0)

Question 266

You are updating the code for a subscriber to a Put/Sub feed. You are concerned that upon deployment the subscriber may erroneously acknowledge messages, leading to message loss. You subscriber is not set up to retain acknowledged messages. What should you do to ensure that you can recover from errors after deployment?

Use Cloud Build for your deployment if an error occurs after deployment, use a Seek operation to locate a tmestamp logged by Cloud Build at the start of the deployment

Create a Pub/Sub snapshot before deploying new subscriber code. Use a Seek operation to redeliver messages that became available after the snapshot was created

Set up the Pub/Sub emulator on your local machine Validate the behavior of your new subscriber togs before deploying it to production

Enable dead-lettering on the Pub/Sub topic to capture messages that aren't successful acknowledged if an error occurs after deployment, re-deliver any messages captured by the deadletter queue

Show Answer Comment (0)

Question 267

Government regulations in the banking industry mandate the protection of client's personally identifiable information (PII). Your company requires PII to be access controlled encrypted and compliant with major data protection standards In addition to using Cloud Data Loss Prevention (Cloud DIP) you want to follow Google-recommended practices and use service accounts to control access to PII. What should you do?

Assign the required identity and Access Management (IAM) roles to every employee, and create a single service account to access protect resources

Use one service account to access a Cloud SQL database and use separate service accounts for each human user

Use Cloud Storage to comply with major data protection standards. Use one service account shared by all users

Use Cloud Storage to comply with major data protection standards. Use multiple service accounts attached to IAM groups to grant the appropriate access to each group

Show Answer Comment (0)

Question 268

You are migrating a table to BigQuery and are deeding on the data model. Your table stores information related to purchases made across several store locations and includes information like the time of the transaction, items purchased, the store ID and the city and state in which the store is located You frequently query this table to see how many of each item were sold over the past 30 days and to look at purchasing trends by state city and individual store. You want to model this table to minimize query time and cost. What should you do?

Partition by transaction time; cluster by state first, then city then store ID

Partition by transaction tome cluster by store ID first, then city, then stale

Top-level cluster by stale first, then city then store

Top-level cluster by store ID first, then city then state.

Show Answer Comment (0)

Question 269

You are building a data pipeline on Google Cloud. You need to prepare data using a casual method for a machine-learning process. You want to support a logistic regression model. You also need to monitor and adjust for null values, which must remain real-valued and cannot be removed. What should you do?

Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataproc job.

Use Cloud Dataprep to find null values in sample source data. Convert all nulls to 0 using a Cloud Dataprep job.

Use Cloud Dataflow to find null values in sample source data. Convert all nulls to 'none' using a Cloud Dataprep job.

Use Cloud Dataflow to find null values in sample source data. Convert all nulls to using a custom script.

Show Answer Comment (0)

Question 270

You have an Oracle database deployed in a VM as part of a Virtual Private Cloud (VPC) network. You want to replicate and continuously synchronize 50 tables to BigQuery. You want to minimize the need to manage infrastructure. What should you do?

Create a Datastream service from Oracle to BigQuery, use a private connectivity configuration to the same VPC network, and a connection profile to BigQuery.

Create a Pub/Sub subscription to write to BigQuery directly Deploy the Debezium Oracle connector to capture changes in the Oracle database, and sink to the Pub/Sub topic.

Deploy Apache Kafka in the same VPC network, use Kafka Connect Oracle Change Data Capture (CDC), and Dataflow to stream the Kafka topic to BigQuery. D O Deploy Apache Kafka in the same VPC network, use Kafka Connect Oracle change data capture (CDC), and the Kafka Connect Google BigQuery Sink Connector.

Show Answer Comment (0)

Total 372 questions

25 26 27 28 29

Go to page: of 38