Databricks-Certified-Professional-Data-Engineer

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The Databricks Certified Professional Data Engineer exam is an excellent choice for data engineers who want to demonstrate their expertise in using Databricks to process big data. The certification exam is recognized globally and highly valued by organizations that use Databricks for their big data processing needs. By passing the exam, data engineers can validate their knowledge and skills and increase their chances of career advancement.

NEW QUESTION 38
Which of the following Structured Streaming queries successfully performs a hop from a Silver to Gold table?

1.(spark.table(“sales”)
2..groupBy(“store”)
3..agg(sum(“sales”))
4..writeStream
5..option(“checkpointLocation”, checkpointPath)
6..outputMode(“complete”)
7..table(“aggregatedSales”) )
(Correct)

1.(spark.table(“sales”)
2..writeStream
3..option(“checkpointLocation”, checkpointPath)
4..outputMode(“complete”)
5..table(“sales”) )

1.(spark.table(“sales”)
2..withColumn(“avgPrice”, col(“sales”) / col(“units”))
3..writeStream
4..option(“checkpointLocation”, checkpointPath)
5..outputMode(“append”)
6..table(“cleanedSales”) )

1.(spark.readStream.load(rawSalesLocation)
2..writeStream
3..option(“checkpointLocation”, checkpointPath)
4..outputMode(“append”)
5..table(“uncleanedSales”) )

1.(spark.read.load(rawSalesLocation)
2. .writeStream
3. .option(“checkpointLocation”, checkpointPath)
4. .outputMode(“append”)
5. .table(“uncleanedSales”) )

NEW QUESTION 39
You would like to build a spark streaming process to read from a Kafka queue and write to a Delta table every
15 minutes, what is the correct trigger option

trigger(“15 minutes”)

trigger(process “15 minutes”)

trigger(processingTime = 15)

trigger(processingTime = “15 Minutes”)

trigger(15)

NEW QUESTION 40
You have accidentally deleted records from a table called transactions, what is the easiest way to restore the records deleted or the previous state of the table? Prior to deleting the version of the table is 3 and after delete the version of the table is 4.

RESTORE TABLE transactions FROM VERSION as of 4

RESTORE TABLE transactions TO VERSION as of 3
C .
1.INSERT INTO OVERWRITE transactions
2.SELECT * FROM transactions VERSION AS OF 3
3.MINUS
4.SELECT * FROM transactions

1.INSERT INTO OVERWRITE transactions
2.SELECT * FROM transactions VERSION AS OF 4
3.INTERSECT
4.SELECT * FROM transactions

COPY OVERWRITE transactions from VERSION as of 3

NEW QUESTION 41
You were asked to write python code to stop all running streams, which of the following command can be used to get a list of all active streams currently running so we can stop them, fill in the blank.
1.for s in _______________:
2. s.stop()

Spark.getActiveStreams()

spark.streams.active

activeStreams()

getActiveStreams()

spark.streams.getActive

NEW QUESTION 42
Question-26. There are 5000 different color balls, out of which 1200 are pink color. What is the maximum
likelihood estimate for the proportion of “pink” items in the test set of color balls?

2.4

24 0

.24

.48

4.8

NEW QUESTION 43
Which of the following developer operations in the CI/CD can only be implemented through a GIT provider when using Databricks Repos.

Trigger Databricks Repos pull API to update the latest version

Commit and push code

Create and edit code

Create a new branch

Pull request and review process

NEW QUESTION 44
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 45
Which of the following approaches can the data engineer use to obtain a version-controllable con-figuration of the Job’s schedule and configuration?

They can link the Job to notebooks that are a part of a Databricks Repo.

They can submit the Job once on a Job cluster.

They can download the JSON equivalent of the job from the Job’s page.

They can submit the Job once on an all-purpose cluster.

They can download the XML description of the Job from the Job’s page

NEW QUESTION 46
One of the queries in the Databricks SQL Dashboard takes a long time to refresh, which of the be-low steps can be taken to identify the root cause of this issue?

Restart the SQL endpoint

Select the SQL endpoint cluster, spark UI, SQL tab to see the execution plan and time spent in each step

Run optimize and Z ordering

Change the Spot Instance Policy from “Cost optimized” to “Reliability Optimized.”

Use Query History, to view queries and select query, and check query profile to time spent in each step

NEW QUESTION 47
The data engineering team noticed that one of the job normally finishes in 15 mins but gets stuck randomly when reading remote databases due to a network packet drop, which of the following steps can be used to improve the stability of the job?

Use Databrick REST API to monitor long running jobs and issue a kill command

Use Jobs runs, active runs UI section to monitor and kill long running job

Modify the task, to include a timeout to kill the job if it runs more than 15 mins.

Use Spark job time out setting in the Spark UI

Use Cluster timeout setting in the Job cluster UI

NEW QUESTION 48
Which of the following commands can be used to run one notebook from another notebook?

notebook.utils.run(“full notebook path”)

execute.utils.run(“full notebook path”)

dbutils.notebook.run(“full notebook path”)

only job clusters can run notebook

spark.notebook.run(“full notebook path”)

NEW QUESTION 49
Which of the following functions can be used to convert JSON string to Struct data type?

TO_STRUCT (json value)

FROM_JSON (json value)

FROM_JSON (json value, schema of json)

CONVERT (json value, schema of json)

CAST (json value as STRUCT)

NEW QUESTION 50
You are designing an analytical to store structured data from your e-commerce platform and un-structured data from website traffic and app store, how would you approach where you store this data?

Use traditional data warehouse for structured data and use data lakehouse for un-structured data.

Data lakehouse can only store unstructured data but cannot enforce a schema

Data lakehouse can store structured and unstructured data and can enforce schema

Traditional data warehouses are good for storing structured data and enforcing schema

NEW QUESTION 51
Projecting a multi-dimensional dataset onto which vector has the greatest variance?

first principal component

first eigenvector

not enough information given to answer

second eigenvector

second principal component

NEW QUESTION 52
You are working on a email spam filtering assignment, while working on this you find there is new word e.g.
HadoopExam comes in email, and in your solutions you never come across this word before, hence probability
of this words is coming in either email could be zero. So which of the following algorithm can help you to
avoid zero probability?

Naive Bayes

Laplace Smoothing

Logistic Regression

All of the above

NEW QUESTION 53
A data engineer needs to dynamically create a table name string using three Python varia-bles: region, store,
and year. An example of a table name is below when region = “nyc”, store = “100”, and year = “2021”:
nyc100_sales_2021
Which of the following commands should the data engineer use to construct the table name in Py-thon?

“{region}+{store}+_sales_+{year}”

“{region}+{store}+”_sales_”+{year}”

f”{region}+{store}+_sales_+{year}”

f”{region}{store}_sales_{year}”

“{region}{store}_sales_{year}”

NEW QUESTION 54
Kevin is the owner of the schema sales, Steve wanted to create new table in sales schema called regional_sales so Kevin grants the create table permissions to Steve. Steve creates the new table called regional_sales in sales schema, who is the owner of the table regional_sales

Kevin is the owner of sales schema, all the tables in the schema will be owned by Kevin

Steve is the owner of the table

By default ownership is assigned DBO

By default ownership is assigned to DEFAULT_OWNER

Kevin and Smith both are owners of table

NEW QUESTION 55
Which of the following is true, when building a Databricks SQL dashboard?

A dashboard can only use results from one query

Only one visualization can be developed with one query result

A dashboard can only connect to one schema/Database

More than one visualization can be developed using a single query result

A dashboard can only have one refresh schedule

NEW QUESTION 56
The sales team has asked the Data engineering team to develop a dashboard that shows sales per-formance for all stores, but the sales team would like to use the dashboard but would like to select individual store location, which of the following approaches Data Engineering team can use to build this functionality into the dashboard.

Use query Parameters which then allow user to choose any location

Currently dashboards do not support parameters

Use Databricks REST API to create a dashboard for each location

Use SQL UDF function to filter the data based on the location

Use Dynamic views to filter the data based on the location

NEW QUESTION 57
In order to use Unity catalog features, which of the following steps needs to be taken on man-aged/external tables in the Databricks workspace?

Enable unity catalog feature in workspace settings

Migrate/upgrade objects in workspace managed/external tables/view to unity catalog

Upgrade to DBR version 15.0

Copy data from workspace to unity catalog

Upgrade workspace to Unity catalog

NEW QUESTION 58
Which of the below SQL commands create a Global temporary view?

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

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
(Correct)

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 59
How do you access or use tables in the unity catalog?

schema_name.table_name

schema_name.catalog_name.table_name

catalog_name.table_name

catalog_name.database_name.schema_name.table_name

catalog_name.schema_name.table_name

The Databricks Certified Professional Data Engineer certification is recognized by leading companies in the tech industry as a benchmark of excellence in the field of data engineering. It is a valuable credential for individuals who are looking to advance their careers in this field and are seeking to demonstrate their expertise in Databricks technologies. Additionally, companies that employ Databricks Certified Professional Data Engineers can be assured that they have the necessary skills to build and maintain complex data pipelines and analytics systems.

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