問題1
A data engineer needs to control access to data assets across multiple workspaces and enforce centralized governance policies. The organization wants fine-grained access control for tables, schemas, and catalogs. Which Databricks feature supports this requirement?
A data engineer needs to control access to data assets across multiple workspaces and enforce centralized governance policies. The organization wants fine-grained access control for tables, schemas, and catalogs. Which Databricks feature supports this requirement?
正確答案: A
問題2
A data engineer streams customer orders into a Kafka topic (orders_topic) and is currently writing the ingestion script of a DLT pipeline. The data engineer needs to ingest the data from Kafka brokers to DLT using Databricks. What is the correct code for ingesting the data?
A data engineer streams customer orders into a Kafka topic (orders_topic) and is currently writing the ingestion script of a DLT pipeline. The data engineer needs to ingest the data from Kafka brokers to DLT using Databricks. What is the correct code for ingesting the data?
正確答案: B
說明：（僅 NewDumps 成員可見）
問題3
What is the structure of an Asset Bundle?
What is the structure of an Asset Bundle?
正確答案: B
說明：（僅 NewDumps 成員可見）
問題4
A Python file is ready for production and the client wants to use the most efficient yet cost- effective type of cluster possible. The workload is quite small, only processing 10GBs of data with only simple joins and no complex aggregations or wide transformations.
Which cluster meets the requirement?
A Python file is ready for production and the client wants to use the most efficient yet cost- effective type of cluster possible. The workload is quite small, only processing 10GBs of data with only simple joins and no complex aggregations or wide transformations.
Which cluster meets the requirement?
正確答案: C
說明：（僅 NewDumps 成員可見）
問題5
A data engineer is writing a DataFrame to a Delta table and wants to physically divide the data into directories based on a specific column such as country. Which Spark DataFrame writer option should be used?
A data engineer is writing a DataFrame to a Delta table and wants to physically divide the data into directories based on a specific column such as country. Which Spark DataFrame writer option should be used?
正確答案: B
問題6
A data engineer needs to access the view created by the sales team, using a shared cluster. The data engineer has been provided usage permissions on the catalog and schema. In order to access the view created by sales team. What are the minimum permissions the data engineer would require in addition?
A data engineer needs to access the view created by the sales team, using a shared cluster. The data engineer has been provided usage permissions on the catalog and schema. In order to access the view created by sales team. What are the minimum permissions the data engineer would require in addition?
正確答案: D
問題7
A data engineer needs to create a table in Databricks using data from a CSV file at location
/path/to/csv.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
A data engineer needs to create a table in Databricks using data from a CSV file at location
/path/to/csv.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
正確答案: B
問題8
A data engineer is loading a dataset into a Delta table but expects the schema to evolve over time as new columns are added. The pipeline should automatically handle new fields without failing ingestion jobs. Which Delta Lake option should the engineer enable during the write operation?
A data engineer is loading a dataset into a Delta table but expects the schema to evolve over time as new columns are added. The pipeline should automatically handle new fields without failing ingestion jobs. Which Delta Lake option should the engineer enable during the write operation?
正確答案: A
問題9
Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?
Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?
正確答案: B
問題10
The Delta transaction log for the 'students' tables is shown using the 'DESCRIBE HISTORY students' command. A Data Engineer needs to query the table as it existed before the UPDATE operation listed in the log. Which command should the Data Engineer use to achieve this?
(Choose two.)
The Delta transaction log for the 'students' tables is shown using the 'DESCRIBE HISTORY students' command. A Data Engineer needs to query the table as it existed before the UPDATE operation listed in the log. Which command should the Data Engineer use to achieve this?
(Choose two.)
正確答案: A,E
說明：（僅 NewDumps 成員可見）
問題11
A data engineer needs to develop integration tests for an ETL process and deploy a version- controlled, packaged workflow into production using an external job scheduler. Which tool should the data engineer use for this job?
A data engineer needs to develop integration tests for an ETL process and deploy a version- controlled, packaged workflow into production using an external job scheduler. Which tool should the data engineer use for this job?
正確答案: B
說明：（僅 NewDumps 成員可見）
問題12
A data engineer needs to read files from cloud object storage into a Spark DataFrame in Databricks. The files are stored in CSV format with headers and comma delimiters. Which Spark DataFrame reader option ensures that column names are correctly inferred from the first row?
A data engineer needs to read files from cloud object storage into a Spark DataFrame in Databricks. The files are stored in CSV format with headers and comma delimiters. Which Spark DataFrame reader option ensures that column names are correctly inferred from the first row?
正確答案: A
問題13
A data engineer needs to optimize the data layout and query performance for an e-commerce transactions Delta table. The table is partitioned by "purchase_date" a date column which helps with time-based queries but does not optimize searches on user statistics "customer_id", a high- cardinality column.
The table is usually queried with filters on "customer_id" within specific date ranges, but since this data is spread across multiple files in each partition, it results in full partition scans and increased runtime and costs.
How should the data engineer optimize the Data Layout for efficient reads?
A data engineer needs to optimize the data layout and query performance for an e-commerce transactions Delta table. The table is partitioned by "purchase_date" a date column which helps with time-based queries but does not optimize searches on user statistics "customer_id", a high- cardinality column.
The table is usually queried with filters on "customer_id" within specific date ranges, but since this data is spread across multiple files in each partition, it results in full partition scans and increased runtime and costs.
How should the data engineer optimize the Data Layout for efficient reads?
正確答案: D
說明：（僅 NewDumps 成員可見）
問題14
Which two conditions are applicable for governance in Databricks Unity Catalog? (Choose two.)
Which two conditions are applicable for governance in Databricks Unity Catalog? (Choose two.)
正確答案: A,D
說明：（僅 NewDumps 成員可見）