Databricks-Certified-Data-Engineer-Associate無料問題集「Databricks Certified Data Engineer Associate」

質問 1

A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to an ELT job. The ELT job has its Databricks SQL query that returns the number of input records containing unexpected NULL values. The data engineer wants their entire team to be notified via a messaging webhook whenever this value reaches 100.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of NULL values reaches 100?

（A）They can set up an Alert with one-time notifications.

（B）They can set up an Alert with a custom template.

（C）They can set up an Alert without notifications.

（D）They can set up an Alert with a new webhook alert destination.

（E）They can set up an Alert with a new email alert destination.

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 2

A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

（A）They can set up the dashboard's SQL endpoint to be serverless.

（B）They can reduce the cluster size of the SQL endpoint.

（C）They can turn on the Auto Stop feature for the SQL endpoint.

（D）They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.

（E）They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.

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 3

A data engineer has a Python variable table_name that they would like to use in a SQL query. They want to construct a Python code block that will run the query using table_name.
They have the following incomplete code block:
____(f"SELECT customer_id, spend FROM {table_name}")
Which of the following can be used to fill in the blank to successfully complete the task?

（A）spark.table

（B）spark.delta.table

（C）spark.sql

（D）dbutils.sql

（E）spark.delta.sql

正解：C 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 4

A data engineer and data analyst are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.
Which of the following changes will need to be made to the pipeline when migrating to Delta Live Tables?

（A）None of these changes will need to be made

（B）The pipeline will need to be written entirely in Python

（C）The pipeline will need to stop using the medallion-based multi-hop architecture

（D）The pipeline will need to be written entirely in SQL

（E）The pipeline will need to use a batch source in place of a streaming source

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 5

Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?

（A）The ability to manipulate the same data using a variety of languages

（B）The ability to support batch and streaming workloads

（C）The ability to collaborate in real time on a single notebook

（D）The ability to set up alerts for query failures

（E）The ability to distribute complex data operations

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 6

A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?

（A）CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions;

（B）CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions;

（C）CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions;

（D）CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions;

（E）CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions;

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 7

Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

（A）Data lake

（B）Data warehouse

（C）None of these

（D）All of these

（E）Data lakehouse

正解：E 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

A data engineer has been given a new record of data:
id STRING = 'a1'
rank INTEGER = 6
rating FLOAT = 9.4
Which of the following SQL commands can be used to append the new record to an existing Delta table my_table?

（A）INSERT VALUES ( 'a1' , 6, 9.4) INTO my_table

（B）INSERT INTO my_table VALUES ('a1', 6, 9.4)

（C）UPDATE VALUES ('a1', 6, 9.4) my_table

（D）UPDATE my_table VALUES ('a1', 6, 9.4)

（E）my_table UNION VALUES ('a1', 6, 9.4)

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 9

A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team's queries uses the same SQL endpoint.
Which of the following approaches can the data engineering team use to improve the latency of the team's queries?

（A）They can turn on the Serverless feature for the SQL endpoint.

（B）They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to "Reliability Optimized."

（C）They can increase the cluster size of the SQL endpoint.

（D）They can turn on the Auto Stop feature for the SQL endpoint.

（E）They can increase the maximum bound of the SQL endpoint's scaling range.

正解：E 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 10

Which of the following data lakehouse features results in improved data quality over a traditional data lake?

（A）A data lakehouse enables machine learning and artificial Intelligence workloads.

（B）A data lakehouse stores data in open formats.

（C）A data lakehouse provides storage solutions for structured and unstructured data.

（D）A data lakehouse allows the use of SQL queries to examine data.

（E）A data lakehouse supports ACID-compliant transactions.

正解：E 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

Databricks-Certified-Data-Engineer-Associate 無料問題集「Databricks Certified Data Engineer Associate」

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