TAKE Databricks Certification Databricks-Certified-Professional-Data-Engineer PRACTICE QUESTIONS FOR AMAZING RESULTS [Q15-Q35]

NEW QUESTION 15
Which of the following scenarios is the best fit for AUTO LOADER?

Efficiently process new data incrementally from cloud object storage

Efficiently move data incrementally from one delta table to another delta table

Incrementally process new data from streaming data sources like Kafka into delta lake

Incrementally process new data from relational databases like MySQL

Efficiently copy data from one data lake location to another data lake location

NEW QUESTION 16
A SQL Dashboard was built for the supply chain team to monitor the inventory and product orders, but all of the timestamps displayed on the dashboards are showing in UTC format, so they requested to change the time zone to the location of New York. How would you approach resolving this issue?

Move the workspace from Central US zone to East US Zone

Change the timestamp on the delta tables to America/New_York format

Change the spark configuration of SQL endpoint to format the timestamp to Ameri-ca/New_York

Under SQL Admin Console, set the SQL configuration parameter time zone to Ameri-ca/New_York

Add SET Timezone = America/New_York on every of the SQL queries in the dashboard.

NEW QUESTION 17
What is the purpose of the bronze layer in a Multi-hop architecture?

Can be used to eliminate duplicate records

Used as a data source for Machine learning applications.

Perform data quality checks, corrupt data quarantined

Contains aggregated data that is to be consumed into Silver

Provides efficient storage and querying of full unprocessed history of data

NEW QUESTION 18
How do you handle failures gracefully when writing code in Pyspark, fill in the blanks to complete the below statement
1._____
2.
3. Spark.read.table(“table_name”).select(“column”).write.mode(“append”).SaveAsTable(“new_table_name”)
4.
5._____
6.
7. print(f”query failed”)

try: failure:

try: catch:

try: except:

try: fail:

try: error:

NEW QUESTION 19
A table nameduser_ltvis being used to create a view that will be used by data analysts on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
Theuser_ltvtable has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:

An analyst who is not a member of the marketing group executes the following query:
SELECT * FROM email_ltv
Which statement describes the results returned by this query?

Three columns will be returned, but one column will be named “redacted” and contain only null values.

Only the email and itv columns will be returned; the email column will contain all null values.

The email and ltv columns will be returned with the values in user itv.

The email, age. and ltv columns will be returned with the values in user ltv.

Only the email and ltv columns will be returned; the email column will contain the string
“REDACTED” in each row.

NEW QUESTION 20
What is the purpose of the bronze layer in a Multi-hop Medallion architecture?

Copy of raw data, easy to query and ingest data for downstream processes.

Powers ML applications

Data quality checks, corrupt data quarantined

Contain aggregated data that is to be consumed into Silver

Reduces data storage by compressing the data

NEW QUESTION 21
An upstream system has been configured to pass the date for a given batch of data to the Databricks Jobs API as a parameter. The notebook to be scheduled will use this parameter to load data with the following code:
df = spark.read.format(“parquet”).load(f”/mnt/source/(date)”)
Which code block should be used to create the date Python variable used in the above code block?

date = spark.conf.get(“date”)

input_dict = input()
date= input_dict[“date”]

import sys
date = sys.argv[1]

date = dbutils.notebooks.getParam(“date”)

dbutils.widgets.text(“date”, “null”)
date = dbutils.widgets.get(“date”)

NEW QUESTION 22
You are working to set up two notebooks to run on a schedule, the second notebook is dependent on the first notebook but both notebooks need different types of compute to run in an optimal fashion, what is the best way to set up these notebooks as jobs?

Use DELTA LIVE PIPELINES instead of notebook tasks

A Job can only use single cluster, setup job for each notebook and use job dependency to link both jobs together

Each task can use different cluster, add these two notebooks as two tasks in a single job with linear dependency and modify the cluster as needed for each of the tasks

Use a single job to setup both notebooks as individual tasks, but use the cluster API to setup the second cluster before the start of second task

Use a very large cluster to run both the tasks in a single job

NEW QUESTION 23
The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. Therecent_sensor_recordingstable contains an identifyingsensor_idalongside thetimestampandtemperaturefor the most recent 5 minutes of recordings.
The below query is used to create the alert:

The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger whenmean (temperature) > 120. Notifications are triggered to be sent at most every 1 minute.
If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?

The total average temperature across all sensors exceeded 120 on three consecutive executions of the query

Therecent_sensor_recordingstable was unresponsive for three consecutive runs of the query

The source query failed to update properly for three consecutive minutes and then restarted

The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query

The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query

NEW QUESTION 24
The downstream consumers of a Delta Lake table have been complaining about data quality issues impacting performance in their applications. Specifically, they have complained that invalidlatitudeandlongitudevalues in theactivity_detailstable have been breaking their ability to use other geolocation processes.
A junior engineer has written the following code to addCHECKconstraints to the Delta Lake table:

A senior engineer has confirmed the above logic is correct and the valid ranges for latitude and longitude are provided, but the code fails when executed.
Which statement explains the cause of this failure?

Because another team uses this table to support a frequently running application, two-phase locking is preventing the operation from committing.

The activity details table already exists; CHECK constraints can only be added during initial table creation.

The activity details table already contains records that violate the constraints; all existing data must pass CHECK constraints in order to add them to an existing table.

The activity details table already contains records; CHECK constraints can only be added prior to inserting values into a table.

The current table schema does not contain the field valid coordinates; schema evolution will need to be enabled before altering the table to add a constraint.

NEW QUESTION 25
Below table temp_data has one column called raw contains JSON data that records temperature for every four hours in the day for the city of Chicago, you are asked to calculate the maximum temperature that was ever recorded for 12:00 PM hour across all the days. Parse the JSON data and use the necessary array function to calculate the max temp.
Table: temp_date
Column: raw
Datatype: string

Expected output: 58

1.select max(raw.chicago.temp[3]) from temp_data

1.select array_max(raw.chicago[*].temp[3]) from temp_data

1.select array_max(from_json(raw[‘chicago’].temp[3],’array<int>’)) from temp_data

1.select array_max(from_json(raw:chicago[*].temp[3],’array<int>’)) from temp_data

1.select max(from_json(raw:chicago[3].temp[3],’array<int>’)) from temp_data

NEW QUESTION 26
A new data engineer has started at a company. The data engineer has recently been added to the company’s
Databricks workspace as [email protected]. The data engineer needs to be able to query the table
sales in the database retail. The new data engineer already has been granted USAGE on the database retail.
Which of the following commands can be used to grant the appropriate permissions to the new data engineer?

GRANT USAGE ON TABLE sales TO [email protected];

GRANT SELECT ON TABLE [email protected] TO sales;

GRANT SELECT ON TABLE sales TO [email protected];

GRANT CREATE ON TABLE sales TO [email protected];

GRANT USAGE ON TABLE [email protected] TO sales;

NEW QUESTION 27
What statement is true regarding the retention of job run history?

It is retained until you export or delete job run logs

It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3

t is retained for 60 days, during which you can export notebook run results to HTML

It is retained for 60 days, after which logs are archived

It is retained for 90 days or until the run-id is re-used through custom run configuration

NEW QUESTION 28
How does a Delta Lake differ from a traditional data lake?

Delta lake is Datawarehouse service on top of data lake that can provide reliability, se-curity, and performance

Delta lake is a caching layer on top of data lake that can provide reliability, security, and performance

Delta lake is an open storage format like parquet with additional capabilities that can provide reliability, security, and performance

Delta lake is an open storage format designed to replace flat files with additional capa-bilities that can provide reliability, security, and performance

Delta lake is proprietary software designed by Databricks that can provide reliability, security, and performance

NEW QUESTION 29
You noticed that a team member started using an all-purpose cluster to develop a notebook and used the same all-purpose cluster to set up a job that can run every 30 mins so they can update un-derlying tables which are used in a dashboard. What would you recommend for reducing the overall cost of this approach?

Reduce the size of the cluster

Reduce the number of nodes and enable auto scale

Enable auto termination after 30 mins

Change the cluster all-purpose to job cluster when scheduling the job

Change the cluster mode from all-purpose to single-mode

NEW QUESTION 30
What is the purpose of gold layer in Multi hop architecture?

Optimizes ETL throughput and analytic query performance

Eliminate duplicate records

Preserves grain of original data, without any aggregations

Data quality checks and schema enforcement

Optimized query performance for business-critical data

NEW QUESTION 31
A new data engineer notices that a critical field was omitted from an application that writes its Kafka source to Delta Lake. This happened even though the critical field was in the Kafka source. That field was further missing from data written to dependent, long-term storage. The retention threshold on the Kafka service is seven days. The pipeline has been in production for three months.
Which describes how Delta Lake can help to avoid data loss of this nature in the future?

The Delta log and Structured Streaming checkpoints record the full history of the Kafka producer.

Delta Lake schema evolution can retroactively calculate the correct value for newly added fields, as long as the data was in the original source.

Delta Lake automatically checks that all fields present in the source data are included in the ingestion layer.

Data can never be permanently dropped or deleted from Delta Lake, so data loss is not possible under any circumstance.

Ingestine all raw data and metadata from Kafka to a bronze Delta table creates a permanent, replayable history of the data state.

NEW QUESTION 32
Which of the below SQL commands creates a session scoped temporary view?

1.CREATE OR REPLACE TEMPORARY VIEW view_name
2.AS SELECT * FROM table_name
(Correct)

1.CREATE OR REPLACE LOCAL TEMPORARY VIEW view_name
2.AS SELECT * FROM table_name

1.CREATE OR REPLACE GLOBAL TEMPORARY VIEW view_name
2.AS SELECT * FROM table_name

1.CREATE OR REPLACE VIEW view_name
2.AS SELECT * FROM table_name

1.CREATE OR REPLACE LOCAL VIEW view_name
2.AS SELECT * FROM table_name

NEW QUESTION 33
Which of the following programming languages can be used to build a Databricks SQL dashboard?

Python

Scala

SQL

R

All of the above

NEW QUESTION 34
A data engineer has created a Delta table as part of a data pipeline. Downstream data analysts now need
SELECT permission on the Delta table.
Assuming the data engineer is the Delta table owner, which part of the Databricks Lakehouse Plat-form can
the data engineer use to grant the data analysts the appropriate access?

Jobs
B Dashboards

Data Explorer

Repos

Databricks Filesystem

NEW QUESTION 35
Which of the following data workloads will utilize a gold table as its source?

A job that enriches data by parsing its timestamps into a human-readable format

A job that queries aggregated data that already feeds into a dashboard

A job that ingests raw data from a streaming source into the Lakehouse

A job that aggregates cleaned data to create standard summary statistics

A job that cleans data by removing malformatted records