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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Developing Apache Spark DataFrame API Applications | 30% | - DataFrame Operations
|
| Using Pandas API on Spark | 5% | - Pandas API
|
| Apache Spark Architecture and Components | 20% | - Spark Architecture
|
| Troubleshooting and Tuning | 10% | - Performance Optimization
|
| Using Spark SQL | 20% | - Spark SQL Operations
|
| Using Spark Connect to Deploy Applications | 5% | - Spark Connect
|
| Structured Streaming | 10% | - Streaming Applications
|
Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:
20 of 55.
What is the difference between df.cache() and df.persist() in Spark DataFrame?
- A. cache() - Persists the DataFrame with the default storage level (MEMORY_AND_DISK_DESER), and persist() - Can be used to set different storage levels to persist the contents of the DataFrame.
- B. persist() - Persists the DataFrame with the default storage level (MEMORY_AND_DISK_DESER), and cache() - Can be used to set different storage levels.
- C. Both cache() and persist() can be used to set the default storage level (MEMORY_AND_DISK_DESER).
- D. Both functions perform the same operation. The persist() function provides improved performance as its default storage level is DISK_ONLY.
Correct Answer: A 🗳️
Explanation: Only visible for DumpsFree members. You can sign-up / login (it's free).
A data scientist is working with a Spark DataFrame called customerDF that contains customer information. The DataFrame has a column named email with customer email addresses. The data scientist needs to split this column into username and domain parts.
Which code snippet splits the email column into username and domain columns?
- A. customerDF.withColumn("username", substring_index(col("email"), "@", 1)) \
.withColumn("domain", substring_index(col("email"), "@", -1)) - B. customerDF.select(
regexp_replace(col("email"), "@", "").alias("username"),
regexp_replace(col("email"), "@", "").alias("domain")
) - C. customerDF.withColumn("username", split(col("email"), "@").getItem(0)) \
.withColumn("domain", split(col("email"), "@").getItem(1)) - D. customerDF.select(
col("email").substr(0, 5).alias("username"),
col("email").substr(-5).alias("domain")
)
Correct Answer: C 🗳️
Explanation: Only visible for DumpsFree members. You can sign-up / login (it's free).
12 of 55.
A data scientist has been investigating user profile data to build features for their model. After some exploratory data analysis, the data scientist identified that some records in the user profiles contain NULL values in too many fields to be useful.
The schema of the user profile table looks like this:
user_id STRING,
username STRING,
date_of_birth DATE,
country STRING,
created_at TIMESTAMP
The data scientist decided that if any record contains a NULL value in any field, they want to remove that record from the output before further processing.
Which block of Spark code can be used to achieve these requirements?
- A. filtered_users = raw_users.dropna(how="all")
- B. filtered_users = raw_users.dropna(how="any")
- C. filtered_users = raw_users.na.drop("all")
- D. filtered_users = raw_users.na.drop("any")
Correct Answer: B 🗳️
Explanation: Only visible for DumpsFree members. You can sign-up / login (it's free).
A developer is running Spark SQL queries and notices underutilization of resources. Executors are idle, and the number of tasks per stage is low.
What should the developer do to improve cluster utilization?
- A. Increase the value of spark.sql.shuffle.partitions
- B. Enable dynamic resource allocation to scale resources as needed
- C. Reduce the value of spark.sql.shuffle.partitions
- D. Increase the size of the dataset to create more partitions
Correct Answer: A 🗳️
Explanation: Only visible for DumpsFree members. You can sign-up / login (it's free).
Which Spark configuration controls the number of tasks that can run in parallel on the executor?
Options:
- A. spark.driver.cores
- B. spark.executor.cores
- C. spark.task.maxFailures
- D. spark.executor.memory
Correct Answer: B 🗳️
Explanation: Only visible for DumpsFree members. You can sign-up / login (it's free).
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