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Databricks Certified Data Engineer Professional Exam Sample Questions (Q126-Q131):

NEW QUESTION # 126
A task orchestrator has been configured to run two hourly tasks. First, an outside system writes Parquet data to a directory mounted at /mnt/raw_orders/. After this data is written, a Databricks job containing the following code is executed:
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Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order, and that the time field indicates when the record was queued in the source system.
If the upstream system is known to occasionally enqueue duplicate entries for a single order hours apart, which statement is correct?

A. Duplicate records enqueued more than 2 hours apart may be retained and the orders table may contain duplicate records with the same customer_id and order_id.
B. All records will be held in the state store for 2 hours before being deduplicated and committed to the orders table.
C. The orders table will not contain duplicates, but records arriving more than 2 hours late will be ignored and missing from the table.
D. The orders table will contain only the most recent 2 hours of records and no duplicates will be present.
E. Duplicate records arriving more than 2 hours apart will be dropped, but duplicates that arrive in the same batch may both be written to the orders table.

Answer: A

NEW QUESTION # 127
The data governance team has instituted a requirement that all tables containing Personal Identifiable Information (PH) must be clearly annotated. This includes adding column comments, table comments, and setting the custom table property "contains_pii" = true.
The following SQL DDL statement is executed to create a new table:
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Which command allows manual confirmation that these three requirements have been met?

A. DESCRIBE HISTORY dev.pii test
B. DESCRIBE EXTENDED dev.pii test
C. SHOW TABLES dev
D. DESCRIBE DETAIL dev.pii test
E. SHOW TBLPROPERTIES dev.pii test

Answer: B

Explanation:
This is the correct answer because it allows manual confirmation that these three requirements have been met. The requirements are that all tables containing Personal Identifiable Information (PII) must be clearly annotated, which includes adding column comments, table comments, and setting the custom table property "contains_pii" = true. The DESCRIBE EXTENDED command is used to display detailed information about a table, such as its schema, location, properties, and comments. By using this command on the dev.pii_test table, one can verify that the table has been created with the correct column comments, table comment, and custom table property as specified in the SQL DDL statement.

NEW QUESTION # 128
A junior data engineer has been asked to develop a streaming data pipeline with a grouped aggregation using DataFrame df. The pipeline needs to calculate the average humidity and average temperature for each non-overlapping five-minute interval. Incremental state information should be maintained for 10 minutes for late-arriving data.
Streaming DataFrame df has the following schema:
"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"
Code block:

Choose the response that correctly fills in the blank within the code block to complete this task.

A. slidingWindow("event_time", "10 minutes")
B. awaitArrival("event_time", "10 minutes")
C. delayWrite("event_time", "10 minutes")
D. withWatermark("event_time", "10 minutes")
E. await("event_time + `10 minutes'")

Answer: D

Explanation:
This is because the question asks for incremental state information to be maintained for 10 minutes for late-arriving data. The withWatermark method is used to define the watermark for late data. The watermark is a timestamp column and a threshold that tells the system how long to wait for late data. In this case, the watermark is set to 10 minutes. The other options are incorrect because they are not valid methods or syntax for watermarking in Structured Streaming.

NEW QUESTION # 129
Which distribution does Databricks support for installing custom Python code packages?

A. CRAN
B. sbt
C. jars
D. CRAM
E. nom
F. Wheels

Answer: E

Explanation:
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https://learn.microsoft.com/en-us/azure/databricks/workflows/jobs/how-to/use-python-wheels-in- workflows

NEW QUESTION # 130
All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:
key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion.
However, for non-PII information, it would like to retain these records indefinitely.
Which of the following solutions meets the requirements?

A. Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.
B. Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.
C. Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.
D. Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.
E. All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.

Answer: B

Explanation:
By default partitionning by a column will create a separate folder for each subset data linked to the partition.

NEW QUESTION # 131
......

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