Google인증 실제 시험문제, Professional-Data-Engineer 덤프문제집

문제1
You designed a data warehouse in BigQuery to analyze sales data. You want a self-serving, low- maintenance, and cost- effective solution to share the sales dataset to other business units in your organization. What should you do?

A. Create an Analytics Hub private exchange, and publish the sales dataset.

B. Use the BigQuery Data Transfer Service to create a schedule that copies the sales dataset to the other business units' projects.

C. Create and share views with the users in the other business units.

D. Enable the other business units' projects to access the authorized views of the sales dataset.

정답: A

문제2
You are analyzing the price of a company's stock. Every 5 seconds, you need to compute a moving average of the past 30 seconds' worth of data. You are reading data from Pub/Sub and using DataFlow to conduct the analysis. How should you set up your windowed pipeline?

A. Use a sliding window with a duration of 5 seconds. Emit results by setting the following trigger:
AfterProcessingTime.pastFirstElementInPane().plusDelayOf(Duration.standardSeconds(30))

B. Use a fixed window with a duration of 30 seconds. Emit results by setting the following trigger:
AfterWatermark.pastEndOfWindow().plusDelayOf(Duration.standardSeconds(5))

C. Use a sliding window with a duration of 30 seconds and a period of 5 seconds.Emit results by setting the following trigger: AfterWatermark.pastEndOfWindow()

D. Use a fixed window with a duration of 5 seconds. Emit results by setting the following trigger:
AfterProcessingTime.pastFirstElementInPane().plusDelayOf(Duration.standardSeconds(30))

정답: C

문제3
Which role must be assigned to a service account used by the virtual machines in a Dataproc cluster so they can execute jobs?

A. Dataproc Runner

B. Dataproc Editor

C. Dataproc Worker

D. Dataproc Viewer

정답: C

설명: (ITDumpsKR 회원만 볼 수 있음)

문제4
You work for a large financial institution that is planning to use Dialogflow to create a chatbot for the company's mobile app. You have reviewed old chat logs and lagged each conversation for intent based on each customer's stated intention for contacting customer service. About 70% of customer requests are simple requests that are solved within 10 intents. The remaining 30% of inquiries require much longer, more complicated requests. Which intents should you automate first?

A. Automate intents in places where common words such as "payment" appear only once so the software isn't confused

B. Automate the 10 intents that cover 70% of the requests so that live agents can handle more complicated requests

C. Automate a blend of the shortest and longest intents to be representative of all intents

D. Automate the more complicated requests first because those require more of the agents' time

정답: B

문제5
You migrated your on-premises Apache Hadoop Distributed File System (HDFS) data lake to Cloud Storage. The data scientist team needs to process the data by using Apache Spark and SQL. Security policies need to be enforced at the column level. You need a cost-effective solution that can scale into a data mesh. What should you do?

A. 1. Define a BigLake table.
2. Create a taxonomy of policy tags in Data Catalog.
3. Add policy tags to columns.
4. Process with the Spark-BigQuery connector or BigQuery SQL.

B. 1. Apply an Identity and Access Management (IAM) policy at the file level in Cloud Storage.
2. Define a BigQuery external table for SQL processing.
3. Use Dataproc Spark to process the Cloud Storage files.

C. 1. Load the data to BigQuery tables.
2. Create a taxonomy of policy tags in Data Catalog.
3. Add policy tags to columns.
4. Process with the Spark-BigQuery connector or BigQuery SQL.

D. 1. Deploy a long-living Dataproc cluster with Apache Hive and Ranger enabled.
2. Configure Ranger for column level security.
3. Process with Dataproc Spark or Hive SQL.

정답: A

문제6
After migrating ETL jobs to run on BigQuery, you need to verify that the output of the migrated jobs is the same as the output of the original. You've loaded a table containing the output of the original job and want to compare the contents with output from the migrated job to show that they are identical. The tables do not contain a primary key column that would enable you to join them together for comparison. What should you do?

A. Create stratified random samples using the OVER() function and compare equivalent samples from each table.

B. Select random samples from the tables using the RAND() function and compare the samples.

C. Use a Dataproc cluster and the BigQuery Hadoop connector to read the data from each table and calculate a hash from non-timestamp columns of the table after sorting. Compare the hashes of each table.

D. Select random samples from the tables using the HASH() function and compare the samples.

정답: C

문제7
One of your encryption keys stored in Cloud Key Management Service (Cloud KMS) was exposed. You need to re- encrypt all of your CMEK-protected Cloud Storage data that used that key, and then delete the compromised key. You also want to reduce the risk of objects getting written without customer-managed encryption key (CMEK) protection in the future. What should you do?

A. Create a new Cloud KMS key. Create a new Cloud Storage bucket configured to use the new key as the default CMEK key. Copy all objects from the old bucket to the new bucket without specifying a key.

B. Create a new Cloud KMS key. Set the default CMEK key on the existing Cloud Storage bucket to the new one.

C. Rotate the Cloud KMS key version. Continue to use the same Cloud Storage bucket.

D. Create a new Cloud KMS key. Create a new Cloud Storage bucket. Copy all objects from the old bucket to the new one bucket while specifying the new Cloud KMS key in the copy command.

정답: A

문제8
You orchestrate ETL pipelines by using Cloud Composer. One of the tasks in the Apache Airflow directed acyclic graph (DAG) relies on a third-party service. You want to be notified when the task does not succeed. What should you do?

A. Assign a function with notification logic to the sla_miss_callback parameter for the operator responsible for the task at risk.

B. Assign a function with notification logic to the on_retry_callback parameter for the operator responsible for the task at risk.

C. Configure a Cloud Monitoring alert on the sla_missed metric associated with the task at risk to trigger a notification.

D. Assign a function with notification logic to the on_failure_callback parameter tor the operator responsible for the task at risk.

정답: D

문제9
When a Cloud Bigtable node fails, ____ is lost.

A. no data

B. the time dimension

C. all data

D. the last transaction

정답: A

설명: (ITDumpsKR 회원만 볼 수 있음)

문제10
You have spent a few days loading data from comma-separated values (CSV) files into the Google BigQuery table CLICK_STREAM. The column DT stores the epoch time of click events.
For convenience, you chose a simple schema where every field is treated as the STRING type.
Now, you want to compute web session durations of users who visit your site, and you want to change its data type to the TIMESTAMP. You want to minimize the migration effort without making future queries computationally expensive. What should you do?

A. Create a view CLICK_STREAM_V, where strings from the column DT are cast into TIMESTAMP values. the view CLICK_STREAM_V instead of the table CLICK_STREAM from now on.

B. Add a column TS of the TIMESTAMP type to the table CLICK_STREAM, and populate the numeric values from the column TS for each row. the column TS instead of the column DT from now on.

C. Delete the table CLICK_STREAM, and then re-create it such that the column DT is of the TIMESTAMP type. Reload the data.

D. Add two columns to the table CLICK STREAM: TS of the TIMESTAMP type and IS_NEW of the BOOLEAN type. Reload all data in append mode. For each appended row, set the value of IS_NEW to true. For future queries, the column TS instead of the column DT, with the WHERE clause ensuring that the value of IS_NEW must be true.

E. Construct a query to return every row of the table CLICK_STREAM, while using the built-in function to cast strings from the column DT into TIMESTAMP values. Run the query into a destination table NEW_CLICK_STREAM, in which the column TS is the TIMESTAMP type. the table NEW_CLICK_STREAM instead of the table CLICK_STREAM from now on. In the future, new data is loaded into the table NEW_CLICK_STREAM.

정답: E

설명: (ITDumpsKR 회원만 볼 수 있음)

문제11
You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A. Use a larger instance type for your Cloud Dataflow workers

B. Increase the number of max workers

C. Create a temporary table in Cloud Spanner that will act as a buffer for new data. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery

D. Change the zone of your Cloud Dataflow pipeline to run in us-central1

E. Create a temporary table in Cloud Bigtable that will act as a buffer for new data. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery

정답: A,B

문제12
You are developing a new deep learning model that predicts a customer's likelihood to buy on your ecommerce site. After running an evaluation of the model against both the original training data and new test data, you find that your model is overfitting the data. You want to improve the accuracy of the model when predicting new data. What should you do?

A. Reduce the size of the training dataset, and decrease the number of input features.

B. Increase the size of the training dataset, and decrease the number of input features.

C. Reduce the size of the training dataset, and increase the number of input features.

D. Increase the size of the training dataset, and increase the number of input features.

정답: B

설명: (ITDumpsKR 회원만 볼 수 있음)

문제13
You are deploying a MySQL database workload onto Cloud SQL. The database must be able to scale up to support several readers from various geographic regions. The database must be highly available and meet low RTO and RPO requirements, even in the event of a regional outage. You need to ensure that interruptions to the readers are minimal during a database failover. What should you do?

A. Create a highly available Cloud SQL instance in region A. Create a highly available read replica in region B. Scale up read workloads by creating cascading read replicas in multiple regions.
Promote the read replica in region B when region A is down.

B. Create a highly available Cloud SQL instance in region A. Scale up read workloads by creating read replicas in multiple regions. Promote one of the read replicas when region A is down.

C. Create a highly available Cloud SQL instance in region Create a highly available read replica in region B. Scale up read workloads by creating cascading read replicas in multiple regions.
Backup the Cloud SQL instances to a multi-regional Cloud Storage bucket. Restore the Cloud SQL backup to a new instance in another region when Region A is down.

D. Create a highly available Cloud SQL instance in region A. Scale up read workloads by creating read replicas in the same region. Failover to the standby Cloud SQL instance when the primary instance fails.

정답: A

문제14
You store historic data in Cloud Storage. You need to perform analytics on the historic data. You want to use a solution to detect invalid data entries and perform data transformations that will not require programming or knowledge of SQL. What should you do?

A. Use federated tables in BigQuery with queries to detect errors and perform transformations.

B. Use Cloud Dataprep with recipes to detect errors and perform transformations.

C. Use Cloud Dataflow with Beam to detect errors and perform transformations.

D. Use Cloud Dataproc with a Hadoop job to detect errors and perform transformations.

정답: B

문제15
Cloud Bigtable is Google's ______ Big Data database service.

A. SQL Server

B. mySQL

C. Relational

D. NoSQL

정답: D

설명: (ITDumpsKR 회원만 볼 수 있음)

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