Databricks Databricks Certified Data Engineer Professional Databricks Certified Data Engineer Professional Exam Online Training
Databricks Databricks Certified Data Engineer Professional Online Training
The questions for Databricks Certified Data Engineer Professional were last updated at Dec 20,2025.
- Exam Code: Databricks Certified Data Engineer Professional
- Exam Name: Databricks Certified Data Engineer Professional Exam
- Certification Provider: Databricks
- Latest update: Dec 20,2025
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
Which of the following statements can be used to test the functionality of code to test number of rows in the table equal to 10 in python?
row_count = spark.sql("select count(*) from table").collect()[0][0]
- A . assert (row_count = 10, "Row count did not match")
- B . assert if (row_count = 10, "Row count did not match")
- C . assert row_count == 10, "Row count did not match"
- D . assert if row_count == 10, "Row count did not match"
- E . assert row_count = 10, "Row count did not match"
SELECT * FROM ____________________
- A . SELECT * FROM f{schema_name.table_name}
- B . SELECT * FROM {schem_name.table_name}
- C . SELECT * FROM ${schema_name}.${table_name}
- D . SELECT * FROM schema_name.table_name
When using the complete mode to write stream data, how does it impact the target table?
- A . Entire stream waits for complete data to write
- B . Stream must complete to write the data
- C . Target table cannot be updated while stream is pending
- D . Target table is overwritten for each batch
- E . Delta commits transaction once the stream is stopped
When using the complete mode to write stream data, how does it impact the target table?
- A . Entire stream waits for complete data to write
- B . Stream must complete to write the data
- C . Target table cannot be updated while stream is pending
- D . Target table is overwritten for each batch
- E . Delta commits transaction once the stream is stopped
Latest Databricks Certified Data Engineer Professional Dumps Valid Version with 278 Q&As
Latest And Valid Q&A | Instant Download | Once Fail, Full Refund
