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

質問 1

Which of the following tools is used by Auto Loader process data incrementally?

（A）Checkpointing

（B）Databricks SQL

（C）Data Explorer

（D）Unity Catalog

（E）Spark Structured Streaming

正解：E 解答を投票する

質問 2

Which of the following commands will return the number of null values in the member_id column?

（A）SELECT null(member_id) FROM my_table;

（B）SELECT count_null(member_id) FROM my_table;

（C）SELECT count_if(member_id IS NULL) FROM my_table;

（D）SELECT count(member_id) - count_null(member_id) FROM my_table;

（E）SELECT count(member_id) FROM my_table;

正解：C 解答を投票する

質問 3

A data engineer wants to create a new table containing the names of customers that live in France.
They have written the following command:

A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (PII).
Which of the following lines of code fills in the above blank to successfully complete the task?

（A）"COMMENT PII"

（B）TBLPROPERTIES PII

（C）COMMENT "Contains PII"

（D）There is no way to indicate whether a table contains PII.

（E）PII

正解：C 解答を投票する

質問 4

A dataset has been defined using Delta Live Tables and includes an expectations clause:
CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON
VIOLATION DROP ROW
What is the expected behavior when a batch of data containing data that violates these constraints is processed?

（A）Records that violate the expectation cause the job to fail.

（B）Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.

（C）Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.

（D）Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.

（E）Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.

正解：B 解答を投票する

質問 5

A company is collaborating with a partner that does not use Databricks but needs access to a large historical dataset stored in Delta format. The data engineer needs to ensure that the partner can access the data securely, without the need for them to set up an account, and with read-only access. How should the data be shared?

（A）Share the dataset by exporting it to a CSV file and manually transferring the file to the partner's system.

（B）Share the dataset using Delta Sharing, which allows your partner to access the data using a secure, read-only URL without requiring a Databricks account, ensuring that they cannot modify the data.

（C）Share the dataset using Unity Catalog, ensuring that both teams have full write access to the data within the same organization.

（D）Grant your partner access to your Databricks workspace and assign them full write permissions to the Delta table, enabling them to modify the dataset.

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

Identify the impact of ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATE for a constraint violation.
A data engineer has created an ETL pipeline using Delta Live table to manage their company travel reimbursement detail, they want to ensure that the if the location details has not been provided by the employee, the pipeline needs to be terminated.
How can the scenario be implemented?

（A）CONSTRAINT valid_location EXPECT (location != NULL) ON VIOLATION FAIL UPDATE

（B）CONSTRAINT valid_location EXPECT (location != NULL) ON DROP ROW

（C）CONSTRAINT valid_location EXPECT (location = NULL)

（D）CONSTRAINT valid_location EXPECT (location != NULL) ON VIOLATION FAIL

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 7

A data engineer wants to create an external table in Databricks that references data stored in an Azure Data Lake Storage (ADLS) location. The goal is to enable Databricks to access and query this external data without moving it into the Databricks-managed storage. Which step should the data engineer take to successfully create the external table?

（A）Use the CREATE TABLE statement and specify the LOCATION clause with the path to the external data.

（B）CREATE UNMANAGED TABLE statement without specifying a LOCATION clause.

（C）Use the CREATE MANAGED TABLE statement and specify the LOCATION clause with the path to the external data.

（D）CREATE EXTERNAL TABLE statement without specifying a LOCATION clause.

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 organization plans to share a large dataset stored in a Databricks workspace on AWS with a partner organization whose Databricks workspace is hosted on Azure. The data engineer wants to minimize data transfer costs while ensuring secure and efficient data sharing. Which strategy will reduce data egress costs associated with cross-cloud data sharing?

（A）Using Delta Sharing without any additional configurations

（B）Configure VPN connection between AWS and Azure for faster data sharing

（C）Sharing data via pre-signed URLs without monitoring egress costs

（D）Migrating the dataset to Cloudflare R2 object storage before sharing

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 9

A data engineer is standardizing repository layouts for multiple teams adopting Databricks Asset Bundles. The engineer wants to ensure every project has a single authoritative configuration file at the repository root that defines the bundle name, targets, workspace settings, permissions, and resource mappings (for jobs and pipelines).
What strategy should the data engineer use to meet the goal?

（A）Place exactly one databricks.yml at the repository root; it is the main configuration file and may reference additional configuration files via the include mapping.

（B）Place a databricks.yaml at the repository root and optional databricks.yml in subfolders; the CLI prefers .yamlover .ymlwhen both exist.

（C）Place multiple databricks.ymlfiles under each subfolder (for example, jobs/pipelines/, workspace/) and merge them at deploy time using the include mapping.

（D）Place a databricks.ymlin a databricks/hidden folder at the repository root; only hidden locations are valid for bundle configs.

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 10

A data engineer is writing Spark code to group sales data by region and calculate total revenue for each region. Which Spark DataFrame transformation performs grouping operations?

（A）groupBy

（B）orderBy

（C）filter

（D）select

正解：A 解答を投票する

質問 11

A data engineer has been provided a PySpark DataFrame named dfwith columns product and revenue. The data engineer needs to compute complex aggregations to determine each product's total revenue, average revenue, and transaction count. Which code snippet should the data engineer use?

（A）

（B）

（C）

（D）

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

What can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

（A）Delta Lake

（B）Data lake

（C）Data warehouse

（D）Data lakehouse

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 13

A data engineer needs to process SQL queries on a large dataset with fluctuating workloads. The workload requires automatic scaling based on the volume of queries, without the need to manage or provision infrastructure. The solution should be cost-efficient and charge only for the compute resources used during query execution. Which compute option should the data engineer use?

（A）Serverless SQL Warehouse

（B）Databricks Jobs

（C）Databricks SQL Analytics

（D）Databricks Runtime for ML

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 14

Which of the following queries is performing a streaming hop from raw data to a Bronze table?

（A）

（B）

（C）

（D）

（E）

正解：B 解答を投票する

質問 15

A data engineer is attempting to drop a Spark SQL table my_table. The data engineer wants to delete all table metadata and data.
They run the following command:
DROP TABLE IF EXISTS my_table
While the object no longer appears when they run SHOW TABLES, the data files still exist.
Which of the following describes why the data files still exist and the metadata files were deleted?

（A）The table's data was larger than 10 GB

（B）The table did not have a location

（C）The table's data was smaller than 10 GB

（D）The table was external

（E）The table was managed

正解：D 解答を投票する

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

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