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Databricks-Certified-Data-Engineer-Associate Test Collection Pdf & Key Databricks-Certified-Data-Engineer-Associate Concepts

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q102-Q107):

NEW QUESTION # 102
A data engineer wants to create a new table containing the names of customers who live in France.
They have written the following command:
CREATE TABLE customersInFrance
_____ AS
SELECT id,
firstName,
lastName
FROM customerLocations
WHERE country = 'FRANCE';
A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (Pll).
Which line of code fills in the above blank to successfully complete the task?

A. "COMMENT PII"
B. TBLPROPERTIES PII
C. COMMENT "Contains PIT
D. 0

Answer: B

Explanation:
To include a property indicating that a table contains personally identifiable information (PII), the TBLPROPERTIES keyword is used in SQL to add metadata to a table. The correct syntax to define a table property for PII is as follows:
CREATE TABLE customersInFrance
USING DELTA
TBLPROPERTIES ('PII' = 'true')
AS
SELECT id,
firstName,
lastName
FROM customerLocations
WHERE country = 'FRANCE';
The TBLPROPERTIES ('PII' = 'true') line correctly sets a table property that tags the table as containing personally identifiable information. This is in accordance with organizational policies for handling sensitive information.
Reference:
Databricks documentation on Delta Lake: Delta Lake on Databricks

NEW QUESTION # 103
A data engineer has left the organization. The data team needs to transfer ownership of the data engineer's Delta tables to a new data engineer. The new data engineer is the lead engineer on the data team.
Assuming the original data engineer no longer has access, which of the following individuals must be the one to transfer ownership of the Delta tables in Data Explorer?

A. Original data engineer
B. New lead data engineer
C. Workspace administrator
D. This transfer is not possible
E. Databricks account representative

Answer: B

NEW QUESTION # 104
A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table:

Which of the following changes needs to be made so this code block will work when the transactions table is a stream source?

A. Replace schema(schema) with option ("maxFilesPerTrigger", 1)
B. Replace predict with a stream-friendly prediction function
C. Replace format("delta") with format("stream")
D. Replace spark.read with spark.readStream
E. Replace "transactions" with the path to the location of the Delta table

Answer: D

Explanation:
1: To read from a stream source, the data engineer needs to use the spark.readStream method instead of the spark.read method. The spark.readStream method returns a DataStreamReader object that can be used to specify the details of the input source, such as the format, the schema, the path, and the options. The spark.read method is only suitable for batch processing, not streaming processing. The other changes are not necessary or correct for reading from a stream source. Reference: Structured Streaming Programming Guide, Read a stream, Databricks Data Sources

NEW QUESTION # 105
Which of the following approaches should be used to send the Databricks Job owner an email in the case that the Job fails?

A. Manually programming in an alert system in each cell of the Notebook
B. Setting up an Alert in the Notebook
C. MLflow Model Registry Webhooks
D. Setting up an Alert in the Job page
E. There is no way to notify the Job owner in the case of Job failure

Answer: D

Explanation:
Explanation
https://docs.databricks.com/en/workflows/jobs/job-notifications.html

NEW QUESTION # 106
In which of the following file formats is data from Delta Lake tables primarily stored?

A. JSON
B. A proprietary, optimized format specific to Databricks
C. Parquet
D. Delta
E. CSV

Answer: C

Explanation:
Delta Lake is an open source project that provides ACID transactions, time travel, and other features on top of Apache Parquet, a columnar file format that is widely used for big data analytics. Delta Lake uses versioned Parquet files to store your data in your cloud storage, along with JSON files as transaction logs and checkpoint files to track the changes and ensure data integrity. Delta Lake is compatible with any Apache Hive compatible file format, such as CSV, JSON, or AVRO, but it primarily stores data as Parquet files for better performance and compression. Reference: How to Create Delta Lake tables, 5 reasons to choose Delta Lake format (on Databricks), Parquet vs Delta format in Azure Data Lake Gen 2 store, What is Delta Lake? - Azure Databricks, Lakehouse and Delta tables - Microsoft Fabric

NEW QUESTION # 107
......

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