Free Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Questions

Become Databricks Certified with updated Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam questions and correct answers

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Total 420 Questions | Updated On: Nov 14, 2024

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Question 1

We have an unmanaged table “my_table”

If we run the code block down below

spark.sql(“DROP TABLE IF EXISTS my_table”)

What will happen to data in my_table ?

A : data will be removed but you will no longer be able to refer to this data by the table name.

B : data will be dropped also

C : ark will remove the table and also associated views

D : is is not a valid code block

Answer: A

Question 2

The code block shown below should return a single-column DataFrame with a column named consonant_ct

that, for each row, shows the number of consonants in column itemName of DataFrame

itemsDf. Choose the answer that correctly fills the blanks in the code block to accomplish this.

DataFrame itemsDf:

1.+------+----------------------------------+-----------------------------+-------------------+

3.+------+----------------------------------+-----------------------------+-------------------+

7.+------+----------------------------------+-----------------------------+-------------------+

Code block:

itemsDf.select(__1__(__2__(__3__(__4__), "a|e|i|o|u|\s", "")).__5__("consonant_ct"))

A : 1. length2. regexp_extract3. upper4. col("itemName")5. as

B : 1. size2. regexp_replace3. lower4. "itemName"5. alias

C : 1. lower2. regexp_replace3. length4. "itemName"5. alias

D : 1. length2. regexp_replace3. lower4. col("itemName")5. alias

E : 1. size2. regexp_extract3. lower4. col("itemName")5. alias

Answer: D

Question 3

Which of the following code blocks immediately removes the previously cached DataFrame transactionsDf from memory and disk?

A : ray_remove(transactionsDf, "*")

B : ansactionsDf.unpersist()

C : l transactionsDf

D : ansactionsDf.clearCache()

E : ansactionsDf.persist()

Answer: B

Question 4

The code block shown below should return a column that indicates through boolean variables whether rows in DataFrame transactionsDf have values greater or equal to 20 and smaller or equal to 30 in column storeId and have the value 2 in column productId. Choose the answer that correctly fills the

blanks in the code block to accomplish this.

transactionsDf.__1__((__2__.__3__) __4__ (__5__))

A : 1. select 2. col("storeId") 3. between(20, 30) 4. and 5. col("productId")==2

B : 1. where2. col("storeId")3. geq(20).leq(30)4. &5. col("productId")==2

C : 1. select2. "storeId"3. between(20, 30)4. &&5. col("productId")==2

D : 1. select2. col("storeId")3. between(20, 30)4. &&5. col("productId")=2

E : 1. select2. col("storeId")3. between(20, 30)4. &5. col("productId")==2

Answer: D

Question 5

What are the possible strategies in order to decrease garbage collection time ?

A : rsist objects in serialized form

B : eate fewer objects

C : crease java heap space size

Answer: A,B,C

Page: 1 / 84

Total 420 Questions | Updated On: Nov 14, 2024

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