Exam Name: Databricks Certified Associate Developer for Apache Spark 3.5 - Python
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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Using Pandas API on Spark | 5% | - Pandas API
|
| Topic 2: Structured Streaming | 10% | - Streaming Applications
|
| Topic 3: Developing Apache Spark DataFrame API Applications | 30% | - DataFrame Operations
|
| Topic 4: Apache Spark Architecture and Components | 20% | - Spark Architecture
|
| Topic 5: Using Spark SQL | 20% | - Spark SQL Operations
|
| Topic 6: Troubleshooting and Tuning | 10% | - Performance Optimization
|
| Topic 7: Using Spark Connect to Deploy Applications | 5% | - Spark Connect
|
Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:
Given a CSV file with the content:
And the following code:
from pyspark.sql.types import *
schema = StructType([
StructField("name", StringType()),
StructField("age", IntegerType())
])
spark.read.schema(schema).csv(path).collect()
What is the resulting output?
- A. [Row(name='alladin', age=20)]
- B. [Row(name='bambi', age=None), Row(name='alladin', age=20)]
- C. [Row(name='bambi'), Row(name='alladin', age=20)]
- D. The code throws an error due to a schema mismatch.
Correct Answer: B 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
A data engineer is reviewing a Spark application that applies several transformations to a DataFrame but notices that the job does not start executing immediately.
Which two characteristics of Apache Spark's execution model explain this behavior?
Choose 2 answers:
- A. The Spark engine optimizes the execution plan during the transformations, causing delays.
- B. Transformations are executed immediately to build the lineage graph.
- C. Transformations are evaluated lazily.
- D. Only actions trigger the execution of the transformation pipeline.
- E. The Spark engine requires manual intervention to start executing transformations.
Correct Answer: C,D 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
19 of 55.
A Spark developer wants to improve the performance of an existing PySpark UDF that runs a hash function not available in the standard Spark functions library.
The existing UDF code is:
import hashlib
from pyspark.sql.types import StringType
def shake_256(raw):
return hashlib.shake_256(raw.encode()).hexdigest(20)
shake_256_udf = udf(shake_256, StringType())
The developer replaces this UDF with a Pandas UDF for better performance:
@pandas_udf(StringType())
def shake_256(raw: str) -> str:
return hashlib.shake_256(raw.encode()).hexdigest(20)
However, the developer receives this error:
TypeError: Unsupported signature: (raw: str) -> str
What should the signature of the shake_256() function be changed to in order to fix this error?
- A. def shake_256(raw: [pd.Series]) -> pd.Series:
- B. def shake_256(raw: str) -> str:
- C. def shake_256(raw: [str]) -> [str]:
- D. def shake_256(raw: pd.Series) -> pd.Series:
Correct Answer: D 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
28 of 55.
A data analyst builds a Spark application to analyze finance data and performs the following operations:
filter, select, groupBy, and coalesce.
Which operation results in a shuffle?
- A. select
- B. groupBy
- C. filter
- D. coalesce
Correct Answer: B 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
35 of 55.
A data engineer is building a Structured Streaming pipeline and wants it to recover from failures or intentional shutdowns by continuing where it left off.
How can this be achieved?
- A. By configuring the option recoveryLocation during SparkSession initialization.
- B. By configuring the option recoveryLocation during writeStream.
- C. By configuring the option checkpointLocation during readStream.
- D. By configuring the option checkpointLocation during writeStream.
Correct Answer: D 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
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