Professional-Data-Engineer無料問題集「Google Certified Professional Data Engineer」

質問 1

You are testing a Dataflow pipeline to ingest and transform text files. The files are compressed gzip, errors are written to a dead-letter queue, and you are using Sidelnputs to join data You noticed that the pipeline is taking longer to complete than expected, what should you do to expedite the Dataflow job?

（A）Use CoGroupByKey instead of the Sidelnput

（B）Switch to compressed Avro files

（C）Retry records that throw an error

（D）Reduce the batch size

正解：D 解答を投票する

質問 2

You are creating a model to predict housing prices. Due to budget constraints, you must run it on a single resource-constrained virtual machine. Which learning algorithm should you use?

（A）Linear regression

（B）Feedforward neural network

（C）Recurrent neural network

（D）Logistic classification

正解：A 解答を投票する

質問 3

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?

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

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

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

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

正解：A 解答を投票する

質問 4

MJTelco is building a custom interface to share dat
a. They have these requirements:
They need to do aggregations over their petabyte-scale datasets.
They need to scan specific time range rows with a very fast response time (milliseconds).
Which combination of Google Cloud Platform products should you recommend?

（A）Cloud Datastore and Cloud Bigtable

（B）BigQuery and Cloud Bigtable

（C）BigQuery and Cloud Storage

（D）Cloud Bigtable and Cloud SQL

正解：B 解答を投票する

質問 5

The data analyst team at your company uses BigQuery for ad-hoc queries and scheduled SQL pipelines in a Google Cloud project with a slot reservation of 2000 slots. However, with the recent introduction of hundreds of new non time-sensitive SQL pipelines, the team is encountering frequent quota errors. You examine the logs and notice that approximately 1500 queries are being triggered concurrently during peak time. You need to resolve the concurrency issue. What should you do?

（A）Increase the slot capacity of the project with baseline as 2000 and maximum reservation size as 3000.

（B）Update SQL pipelines and ad-hoc queries to run as interactive query jobs.

（C）Increase the slot capacity of the project with baseline as 0 and maximum reservation size as 3000.

（D）Update SOL pipelines to run as a batch query, and run ad-hoc queries as interactive query jobs.

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 6

Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?

（A）Use the Google Cloud Billing API to see what account the warehouse is being billed to.

（B）Use Google Stackdriver Audit Logs to review data access.

（C）Get the identity and access management IIAM) policy of each table

（D）Use Stackdriver Monitoring to see the usage of BigQuery query slots.

正解：B 解答を投票する

質問 7

You are building an ELT solution in BigQuery by using Dataform. You need to perform uniqueness and null value checks on your final tables. What should you do to efficiently integrate these checks into your pipeline?

（A）Build Dataform assertions into your code

（B）Build BigQuery user-defined functions (UDFs).

（C）Create Dataplex data quality tasks.

（D）Write a Spark-based stored procedure.

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 8

An aerospace company uses a proprietary data format to store its night dat a. You need to connect this new data source to BigQuery and stream the data into BigQuery. You want to efficiency import the data into BigQuery where consuming as few resources as possible. What should you do?

（A）Use a standard Dataflow pipeline to store the raw data m BigQuery and then transform the format later when the data is used

（B）Use an Apache Beam custom connector to write a Dataflow pipeline that streams the data into BigQuery in Avro format

（C）Use Apache Hive to write a Dataproc job that streams the data into BigQuery in CSV format

（D）Write a she script that triggers a Cloud Function that performs periodic ETL batch jobs on the new data source

正解：B 解答を投票する

質問 9

You migrated a data backend for an application that serves 10 PB of historical product data for analytics. Only the last known state for a product, which is about 10 GB of data, needs to be served through an API to the other applications. You need to choose a cost-effective persistent storage solution that can accommodate the analytics requirements and the API performance of up to 1000 queries per second (QPS) with less than 1 second latency. What should you do?

（A）1. Store the historical data in BigQuery for analytics.
2. In a Cloud SQL table, store the last state of the product after every product change.
3. Serve the last state data directly from Cloud SQL to the API.

（B）1. Store the products as a collection in Firestore with each product having a set of historical changes.
2. Use simple and compound queries for analytics.
3. Serve the last state data directly from Firestore to the API.

（C）1. Store the historical data in BigQuery for analytics.
2. Use a materialized view to precompute the last state of a product.
3. Serve the last state data directly from BigQuery to the API.

（D）1. Store the historical data in Cloud SQL for analytics.
2. In a separate table, store the last state of the product after every product change.
3. Serve the last state data directly from Cloud SQL to the API.

正解：C 解答を投票する

質問 10

You maintain ETL pipelines. You notice that a streaming pipeline running on Dataflow is taking a long time to process incoming data, which causes output delays. You also noticed that the pipeline graph was automatically optimized by Dataflow and merged into one step. You want to identify where the potential bottleneck is occurring. What should you do?

（A）Insert output sinks after each key processing step, and observe the writing throughput of each block.

（B）Insert a Reshuffle operation after each processing step, and monitor the execution details in the Dataflow console.

（C）Verify that the Dataflow service accounts have appropriate permissions to write the processed data to the output sinks

（D）Log debug information in each ParDo function, and analyze the logs at execution time.

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 11

You are creating a data model in BigQuery that will hold retail transaction dat a. Your two largest tables, sales_transation_header and sales_transation_line. have a tightly coupled immutable relationship. These tables are rarely modified after load and are frequently joined when queried. You need to model the sales_transation_header and sales_transation_line tables to improve the performance of data analytics queries. What should you do?

（A）Create a sale_transaction table that holds the sales_transaction_header and sales_transaction_line information as rows, duplicating the sales_transaction_header data for each line.

（B）Create separate sales_transation_header and sales_transation_line tables and. when querying, specify the sales transition line first in the WHERE clause.

（C）Create a sal es_transaction table that Stores the sales_tran3action_header and sales_transaction_line data as a JSON data type.

（D）Create a sale3_transaction table that holds the sales_transaction_header information as rows and the sales_transaction_line rows as nested and repeated fields.

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 12

You have a variety of files in Cloud Storage that your data science team wants to use in their models Currently, users do not have a method to explore, cleanse, and validate the data in Cloud Storage. You are looking for a low code solution that can be used by your data science team to quickly cleanse and explore data within Cloud Storage. What should you do?

（A）Create an external table in BigQuery and use SQL to transform the data as necessary Provide the data science team access to the external tables to explore the raw data.

（B）Provide the data science team access to Dataprep to prepare, validate, and explore the data within Cloud Storage.

（C）Provide the data science team access to Dataflow to create a pipeline to prepare and validate the raw data and load data into BigQuery for data exploration.

（D）Load the data into BigQuery and use SQL to transform the data as necessary Provide the data science team access to staging tables to explore the raw data.

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

Professional-Data-Engineer 無料問題集「Google Certified Professional Data Engineer」

弊社を連絡する

関連リンク

トップ試験