Exam Topics 4 Flashcards
Question #: 152
Topic #: 1
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?
A. BigQuery
B. Cloud Bigtable
C. Cloud Datastore
D. Cloud SQL for PostgreSQL
A. BigQuery
Question #: 156
Topic #: 1
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?
A. Deploy a Cloud 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://
B. Deploy a Cloud 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://
C. Install 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://
D. Install 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://
A. Deploy a Cloud 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://
Reason: Dataproc is managed serviced. Standard PD is cheaper than SSD
Question #: 160
Topic #: 1
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?
A. Cloud SQL
B. Cloud Bigtable
C. Cloud Spanner
D. Cloud Datastore
A. Cloud SQL
Reason: CloudSQL limit 64TB
Question #: 158
Topic #: 1
You need to deploy additional dependencies to all 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?
A. Deploy the Cloud SQL Proxy on the Cloud Dataproc master
B. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
C. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
D. Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
C. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
Question #: 157
Topic #: 1
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?
A. Perform hyperparameter tuning
B. Train a classifier with deep neural networks, because neural networks would always beat SVMs
C. Deploy the model and measure the real-world AUC; it’s always higher because of generalization
D. Scale predictions you get out of the model (tune a scaling factor as a hyperparameter) in order to get the highest AUC
A. Perform hyperparameter tuning
Question #: 154
Topic #: 1
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?
A. Create a Cloud SQL instance in one zone, and create a failover replica in another zone within the same region.
B. Create a Cloud SQL instance in one zone, and create a read replica in another zone within the same region.
C. Create a Cloud SQL instance in one zone, and configure an external read replica in a zone in a different region.
D. Create a Cloud SQL instance in a region, and configure automatic backup to a Cloud Storage bucket in the same region.
A. Create a Cloud SQL instance in one zone, and create a failover replica in another zone within the same region.
Reason: high availability = failover replica
Question #: 153
Topic #: 1
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?
A. Consume the stream of data in Cloud 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.
B. Consume the stream of data in Cloud 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.
C. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Sub. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtable. Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour. If that number falls below 4000, send an alert.
D. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Sub. Use a Cloud Dataflow template to write your messages from Cloud 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.
A. Consume the stream of data in Cloud 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.
Reason: sliding window. C and D is not real time
Question #: 151
Topic #: 1
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?
A. Use Cloud ML Engine for training existing Spark ML models
B. Rewrite your models on TensorFlow, and start using Cloud ML Engine
C. Use Cloud Dataproc for training existing Spark ML models, but start reading data directly from BigQuery
D. Spin up a Spark cluster on Compute Engine, and train Spark ML models on the data exported from BigQuery
C. Use Cloud Dataproc for training existing Spark ML models, but start reading data directly from BigQuery
Reason: lift-and-shift so Dataproc.
Question #: 162
Topic #: 1
You want to archive data in Cloud Storage. Because some data is very sensitive, you want to use the “Trust No One” (TNO) approach to encrypt your data to prevent the cloud provider staff from decrypting your data. What should you do?
A. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key and unique additional authenticated data (AAD). Use gsutil cp to upload each encrypted file to the Cloud Storage bucket, and keep the AAD outside of Google Cloud.
B. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key. Use gsutil cp to upload each encrypted file to the Cloud Storage bucket. Manually destroy the key previously used for encryption, and rotate the key once.
C. Specify customer-supplied encryption key (CSEK) in the .boto configuration file. Use gsutil cp to upload each archival file to the Cloud Storage bucket. Save the CSEK in Cloud Memorystore as permanent storage of the secret.
D. Specify customer-supplied encryption key (CSEK) in the .boto configuration file. Use gsutil cp to upload each archival file to the Cloud Storage bucket. Save the CSEK in a different project that only the security team can access.
A. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key and unique additional authenticated data (AAD). Use gsutil cp to upload each encrypted file to the Cloud Storage bucket, and keep the AAD outside of Google Cloud.
Reason: AAD is outside of Google Cloud so cloud provider staff cannot decrypt
Question #: 163
Topic #: 1
You have data pipelines running on BigQuery, Cloud Dataflow, and Cloud Dataproc. You need to perform health checks and monitor their behavior, and then notify the team managing the pipelines if they fail. You also need to be able to work across multiple projects. Your preference is to use managed products of features of the platform. What should you do?
A. Export the information to Cloud Stackdriver, and set up an Alerting policy
B. Run a Virtual Machine in Compute Engine with Airflow, and export the information to Stackdriver
C. Export the logs to BigQuery, and set up App Engine to read that information and send emails if you find a failure in the logs
D. Develop an App Engine application to consume logs using GCP API calls, and send emails if you find a failure in the logs
A. Export the information to Cloud Stackdriver, and set up an Alerting policy
Question #: 155
Topic #: 1
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:
✑ The ability to seek to a particular offset in a topic, possibly back to the start of all data ever captured
✑ Support for publish/subscribe semantics on hundreds of topics
✑ Retain per-key ordering
Which system should you choose?
A. Apache Kafka
B. Cloud Storage
C. Cloud Pub/Sub
D. Firebase Cloud Messaging
A. Apache Kafka
Reason: pub/sub max retention 31 days only
Question #: 159
Topic #: 1
You need to choose a database for a new project that has the following requirements:
✑ Fully managed
✑ Able to automatically scale up
✑ Transactionally consistent
✑ Able to scale up to 6 TB
✑ Able to be queried using SQL
Which database do you choose?
A. Cloud SQL
B. Cloud Bigtable
C. Cloud Spanner
D. Cloud Datastore
A. Cloud SQL
Reason: 6TB is ok, max 30TB for Cloud SQL
Question #: 161
Topic #: 1
You need to choose a database to store time series CPU and memory usage for millions of computers. You need to store this data in one-second interval samples. Analysts will be performing real-time, ad hoc analytics against the database. You want to avoid being charged for every query executed and ensure that the schema design will allow for future growth of the dataset. Which database and data model should you choose?
A. Create a table in BigQuery, and append the new samples for CPU and memory to the table
B. Create a wide table in BigQuery, create a column for the sample value at each second, and update the row with the interval for each second
C. Create a narrow table in Cloud Bigtable with a row key that combines the Computer Engine computer identifier with the sample time at each second
D. Create a wide table in Cloud Bigtable with a row key that combines the computer identifier with the sample time at each minute, and combine the values for each second as column data.
C. Create a narrow table in Cloud Bigtable with a row key that combines the Computer Engine computer identifier with the sample time at each second
Reason: Each row stores only 1 data point for 1 computer at a given time. Faster to write and read.
