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: Developing Apache Spark DataFrame API Applications | 30% | - User-defined functions (UDFs) - Creating DataFrames and defining schemas - Joining and combining datasets - Selecting, renaming, and modifying columns - Handling missing values and data quality - Reading and writing data in various formats - Filtering, sorting, and aggregating data - Partitioning and bucketing data |
| Topic 2: Using Pandas API on Apache Spark | 5% | - Converting between Pandas and Spark structures - Overview of Pandas API on Spark - Key differences and limitations |
| Topic 3: Apache Spark Architecture and Components | 20% | - Shuffling, actions, and broadcasting - Execution hierarchy and lazy evaluation - Spark architecture overview - Execution and deployment modes - Fault tolerance and garbage collection |
| Topic 4: Troubleshooting and Tuning Apache Spark DataFrame API Applications | 10% | - Identifying performance bottlenecks - Debugging and logging - Optimizing transformations and actions - Managing memory and resource usage |
| Topic 5: Using Spark Connect to Deploy Applications | 5% | - Running applications via Spark Connect - Spark Connect architecture - Connecting to remote Spark clusters |
| Topic 6: Using Spark SQL | 20% | - Running SQL queries - Using catalog and metadata APIs - Integrating Spark SQL with DataFrames - Working with functions and expressions |
| Topic 7: Structured Streaming | 10% | - Output modes and triggers - Fault tolerance and state management - Defining streaming queries - Streaming concepts and architecture |
Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:
1. 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) coalesce
B) groupBy
C) filter
D) select
2. How can a Spark developer ensure optimal resource utilization when running Spark jobs in Local Mode for testing?
Options:
A) Set the spark.executor.memory property to a large value.
B) Use the spark.dynamicAllocation.enabled property to scale resources dynamically.
C) Configure the application to run in cluster mode instead of local mode.
D) Increase the number of local threads based on the number of CPU cores.
3. 8 of 55.
A data scientist at a large e-commerce company needs to process and analyze 2 TB of daily customer transaction data. The company wants to implement real-time fraud detection and personalized product recommendations.
Currently, the company uses a traditional relational database system, which struggles with the increasing data volume and velocity.
Which feature of Apache Spark effectively addresses this challenge?
A) Support for SQL queries on structured data
B) Ability to process small datasets efficiently
C) In-memory computation and parallel processing capabilities
D) Built-in machine learning libraries
4. 32 of 55.
A developer is creating a Spark application that performs multiple DataFrame transformations and actions. The developer wants to maintain optimal performance by properly managing the SparkSession.
How should the developer handle the SparkSession throughout the application?
A) Avoid using a SparkSession and rely on SparkContext only.
B) Create a new SparkSession instance before each transformation.
C) Stop and restart the SparkSession after each action.
D) Use a single SparkSession instance for the entire application.
5. What is the benefit of using Pandas on Spark for data transformations?
Options:
A) It runs on a single node only, utilizing the memory with memory-bound DataFrames and hence cost-efficient.
B) It is available only with Python, thereby reducing the learning curve.
C) It executes queries faster using all the available cores in the cluster as well as provides Pandas's rich set of features.
D) It computes results immediately using eager execution, making it simple to use.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: C |
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