View Databricks-Certified-Data-Engineer-Associate Exam Question Dumps With Latest Demo [Jan 16, 2024]
Free Databricks-Certified-Data-Engineer-Associate Test Questions Real Practice Test Questions
NEW QUESTION # 24
A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:
After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?
- A. The names of the files to be copied were not included with the FILES keyword.
- B. The PARQUET file format does not support COPY INTO.
- C. The previous day's file has already been copied into the table.
- D. The COPY INTO statement requires the table to be refreshed to view the copied rows.
- E. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
Answer: C
NEW QUESTION # 25
Which of the following commands will return the location of database customer360?
- A. DESCRIBE LOCATION customer360;
- B. DESCRIBE DATABASE customer360;
- C. DROP DATABASE customer360;
- D. USE DATABASE customer360;
- E. ALTER DATABASE customer360 SET DBPROPERTIES ('location' = '/user'};
Answer: B
Explanation:
Explanation
To retrieve the location of a database named "customer360" in a database management system like Hive or Databricks, you can use the DESCRIBE DATABASE command followed by the database name. This command will provide information about the database, including its location.
NEW QUESTION # 26
In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?
- A. Checkpointing and Idempotent Sinks
- B. Structured Streaming cannot record the offset range of the data being processed in each trigger.
- C. Replayable Sources and Idempotent Sinks
- D. Checkpointing and Write-ahead Logs
- E. Write-ahead Logs and Idempotent Sinks
Answer: A
NEW QUESTION # 27
Which of the following data lakehouse features results in improved data quality over a traditional data lake?
- A. A data lakehouse enables machine learning and artificial Intelligence workloads.
- B. A data lakehouse provides storage solutions for structured and unstructured data.
- C. A data lakehouse stores data in open formats.
- D. A data lakehouse allows the use of SQL queries to examine data.
- E. A data lakehouse supports ACID-compliant transactions.
Answer: D
NEW QUESTION # 28
A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run.
Which of the following tools can the data engineer use to solve this problem?
- A. Databricks SQL
- B. Data Explorer
- C. Unity Catalog
- D. Auto Loader
- E. Delta Lake
Answer: D
NEW QUESTION # 29
A data engineer is maintaining a data pipeline. Upon data ingestion, the data engineer notices that the source data is starting to have a lower level of quality. The data engineer would like to automate the process of monitoring the quality level.
Which of the following tools can the data engineer use to solve this problem?
- A. Delta Live Tables
- B. Data Explorer
- C. Unity Catalog
- D. Auto Loader
- E. Delta Lake
Answer: A
Explanation:
Explanation
https://docs.databricks.com/delta-live-tables/expectations.html
Delta Live Tables is a tool provided by Databricks that can help data engineers automate the monitoring of data quality. It is designed for managing data pipelines, monitoring data quality, and automating workflows.
With Delta Live Tables, you can set up data quality checks and alerts to detect issues and anomalies in your data as it is ingested and processed in real-time. It provides a way to ensure that the data quality meets your desired standards and can trigger actions or notifications when issues are detected. While the other tools mentioned may have their own purposes in a data engineeringenvironment, Delta Live Tables is specifically designed for data quality monitoring and automation within the Databricks ecosystem.
NEW QUESTION # 30
A new data engineering team has been assigned to work on a project. The team will need access to database customers in order to see what tables already exist. The team has its own group team.
Which of the following commands can be used to grant the necessary permission on the entire database to the new team?
- A. GRANT USAGE ON CATALOG team TO customers;
- B. GRANT VIEW ON CATALOG customers TO team;
- C. GRANT CREATE ON DATABASE customers TO team;
- D. GRANT USAGE ON DATABASE customers TO team;
- E. GRANT CREATE ON DATABASE team TO customers;
Answer: D
Explanation:
Explanation
The GRANT statement is used to grant privileges on a database, table, or view to a user or role. The ALL PRIVILEGES option grants all possible privileges on the specified object, such as CREATE, SELECT, MODIFY, and USAGE. The syntax of the GRANT statement is:
GRANT privilege_type ON object TO user_or_role;
Therefore, to grant full permissions on the database customers to the new data engineering team, the command should be:
GRANT ALL PRIVILEGES ON DATABASE customers TO team;
NEW QUESTION # 31
A data engineer that is new to using Python needs to create a Python function to add two integers together and return the sum?
Which of the following code blocks can the data engineer use to complete this task?
- A.
- B.
- C.
- D.
- E.
Answer: A
Explanation:
Explanation
https://www.w3schools.com/python/python_functions.asp
NEW QUESTION # 32
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. Workspace administrator
- B. Original data engineer
- C. This transfer is not possible
- D. New lead data engineer
- E. Databricks account representative
Answer: A
Explanation:
Explanation
https://docs.databricks.com/sql/admin/transfer-ownership.html
NEW QUESTION # 33
A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?
- A. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions; - B. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions; - C. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions; - D. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions; - E. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions;
Answer: A
Explanation:
Explanation
To create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records, you should use the UNION operator, as shown in option B. This operator combines the result sets of the two tables while automatically removing duplicate records.
NEW QUESTION # 34
A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:
After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?
- A. The names of the files to be copied were not included with the FILES keyword.
- B. The PARQUET file format does not support COPY INTO.
- C. The previous day's file has already been copied into the table.
- D. The COPY INTO statement requires the table to be refreshed to view the copied rows.
- E. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
Answer: C
Explanation:
Explanation
https://docs.databricks.com/en/ingestion/copy-into/index.html The COPY INTO SQL command lets you load data from a file location into a Delta table. This is a re-triable and idempotent operation; files in the source location that have already been loaded are skipped. if there are no new records, the only consistent choice is C no new files were loaded because already loaded files were skipped.
NEW QUESTION # 35
In which of the following scenarios should a data engineer select a Task in the Depends On field of a new Databricks Job Task?
- A. When another task has the same dependency libraries as the new task
- B. When another task needs to fail before the new task begins
- C. When another task needs to use as little compute resources as possible
- D. When another task needs to be replaced by the new task
- E. When another task needs to successfully complete before the new task begins
Answer: E
NEW QUESTION # 36
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's data was smaller than 10 GB
- C. The table did not have a location
- D. The table was external
- E. The table was managed
Answer: D
Explanation:
Explanation
The reason why the data files still exist while the metadata files were deleted is because the table was external.
When a table is external in Spark SQL (or in other database systems), it means that the table metadata (such as schema information and table structure) is managed externally, and Spark SQL assumes that the data is managed and maintained outside of the system. Therefore, when you execute a DROP TABLE statement for an external table, it removes only the table metadata from the catalog, leaving the data files intact. On the other hand, for managed tables (option E), Spark SQL manages both the metadata and the data files. When you drop a managed table, it deletes both the metadata and the associated data files, resulting in a complete removal of the table.
NEW QUESTION # 37
A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?
- A. There is no way to share data between PySpark and SQL.
- B. SELECT * FROM sales
- C. spark.delta.table("sales")
- D. spark.sql("sales")
- E. spark.table("sales")
Answer: E
Explanation:
Explanation
https://spark.apache.org/docs/3.2.1/api/python/reference/api/pyspark.sql.SparkSession.table.html
NEW QUESTION # 38
A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?
- A. They can reduce the cluster size of the SQL endpoint.
- B. They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.
- C. They can turn on the Auto Stop feature for the SQL endpoint.
- D. They can set up the dashboard's SQL endpoint to be serverless.
- E. They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
Answer: C
NEW QUESTION # 39
A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the original task.
Which of the following approaches can the data engineer use to set up the new task?
- A. They can clone the existing task to a new Job and then edit it to run the new notebook.
- B. They can create a new task in the existing Job and then add the original task as a dependency of the new task.
- C. They can create a new task in the existing Job and then add it as a dependency of the original task.
- D. They can clone the existing task in the existing Job and update it to run the new notebook.
- E. They can create a new job from scratch and add both tasks to run concurrently.
Answer: C
Explanation:
Explanation
To set up the new task to run a new notebook prior to the original task in a single-task Job, the data engineer can use the following approach: In the existing Job, create a new task that corresponds to the new notebook that needs to be run. Set up the new task with the appropriate configuration, specifying the notebook to be executed and any necessary parameters or dependencies. Once the new task is created, designate it as a dependency of the original task in the Job configuration. This ensures that the new task is executed before the original task.
NEW QUESTION # 40
Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?
- A.
- B.
- C.
- D.
- E.
Answer: C
NEW QUESTION # 41
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
- A. org.apache.spark.sql.jdbc
- B. org.apache.spark.sql.sqlite
- C. autoloader
- D. sqlite
- E. DELTA
Answer: B
NEW QUESTION # 42
A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values.
Which of the following describes why Auto Loader inferred all of the columns to be of the string type?
- A. JSON data is a text-based format
- B. There was a type mismatch between the specific schema and the inferred schema
- C. All of the fields had at least one null value
- D. Auto Loader cannot infer the schema of ingested data
- E. Auto Loader only works with string data
Answer: A
Explanation:
Explanation
JSON data is a text-based format that uses strings to represent all values. When Auto Loader infers the schema of JSON data, it assumes that all values are strings. This is because Auto Loader cannot determine the type of a value based on its string representation. https://docs.databricks.com/en/ingestion/auto-loader/schema.html Forexample, the following JSON string represents a value that is logically a boolean: JSON "true" Use code with caution. Learn more However, Auto Loader would infer that the type of this value is string. This is because Auto Loader cannot determine that the value is a boolean based on its string representation. In order to get Auto Loader to infer the correct types for columns, the data engineer can provide type inference or schema hints. Type inference hints can be used to specify the types of specific columns. Schema hints can be used to provide the entire schema of the data.
Therefore, the correct answer is B. JSON data is a text-based format.
NEW QUESTION # 43
A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?
- A. They can reduce the cluster size of the SQL endpoint.
- B. They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.
- C. They can turn on the Auto Stop feature for the SQL endpoint.
- D. They can set up the dashboard's SQL endpoint to be serverless.
- E. They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
Answer: C
NEW QUESTION # 44
Which of the following must be specified when creating a new Delta Live Tables pipeline?
- A. A location of a target database for the written data
- B. At least one notebook library to be executed
- C. A key-value pair configuration
- D. The preferred DBU/hour cost
- E. A path to cloud storage location for the written data
Answer: B
Explanation:
Explanation
https://docs.databricks.com/en/delta-live-tables/tutorial-pipelines.html
NEW QUESTION # 45
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 are dropped from the target dataset and recorded as invalid in the event log.
- B. Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.
- C. Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.
- D. Records that violate the expectation cause the job to fail.
- E. Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.
Answer: A
Explanation:
Explanation
With the defined constraint and expectation clause, when a batch of data is processed, any records that violate the expectation (in this case, where the timestamp is not greater than '2020-01-01') will be dropped from the target dataset. These dropped records will also be recorded as invalid in the event log, allowing for auditing and tracking of the data quality issues without causing the entire job to fail.
https://docs.databricks.com/en/delta-live-tables/expectations.html
NEW QUESTION # 46
A data engineer is attempting to drop a Spark SQL table my_table and runs the following command:
DROP TABLE IF EXISTS my_table;
After running this command, the engineer notices that the data files and metadata files have been deleted from the file system.
Which of the following describes why all of these files were deleted?
- A. The table's data was larger than 10 GB
- B. The table's data was smaller than 10 GB
- C. The table was managed
- D. The table did not have a location
- E. The table was external
Answer: C
Explanation:
Explanation
managed tables files and metadata are managed by metastore and will be deleted when the table is dropped .
while external tables the metadata is stored in a external location. hence when a external table is dropped you clear off only the metadata and the files (data) remain.
NEW QUESTION # 47
Which of the following data workloads will utilize a Gold table as its source?
- A. A job that queries aggregated data designed to feed into a dashboard
- B. A job that aggregates uncleaned data to create standard summary statistics
- C. A job that cleans data by removing malformatted records
- D. A job that ingests raw data from a streaming source into the Lakehouse
- E. A job that enriches data by parsing its timestamps into a human-readable format
Answer: A
NEW QUESTION # 48
Which of the following describes the storage organization of a Delta table?
- A. Delta tables are stored in a collection of files that contain only the data stored within the table.
- B. Delta tables store their data in a single file and all metadata in a collection of files in a separate location.
- C. Delta tables are stored in a single file that contains data, history, metadata, and other attributes.
- D. Delta tables are stored in a single file that contains only the data stored within the table.
- E. Delta tables are stored in a collection of files that contain data, history, metadata, and other attributes.
Answer: E
NEW QUESTION # 49
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