Databricks Certified Associate Developer for Apache Spark
Tests your grasp of Spark architecture and your ability to use the DataFrame API for everyday data work: selecting and reshaping columns, filtering, sorting and aggregating rows, handling missing data, joining, reading and writing partitioned DataFrames with schemas, and using UDFs and Spark SQL functions. It also covers execution modes, lazy evaluation, shuffling, Structured Streaming and common tuning fixes. Passing shows you can complete core Spark DataFrame tasks in Python.
Exam blueprint
Exam sections
Apache Spark Architecture and Components20%
Using Spark SQL20%
Developing Apache Spark™ DataFrame/DataSet API Applications30%
Troubleshooting and Tuning Apache Spark DataFrame API Applications10%
Hands-on API usageDataFrame transformations, schemas, joins and aggregations.
Execution awarenessJobs, stages, shuffles, partitions and performance choices.
Production readinessTroubleshooting, tuning and working with common Spark workloads.
Step-by-step preparation guide
Start here and follow this plan until exam day
Use PySpark.in as the preparation hub: first verify the official Databricks exam details, then study every domain, practise hands-on and finish with timed mock tests.
Roadmap links open official Databricks documentation or registration pages. Use those pages for source-of-truth exam details, then return to PySpark.in for practice and mocks.
Step 1Understand the exam blueprint
Know the domains, time limit, question pattern and official registration path before studying.
Read the official Databricks exam page and PySpark.in exam summary.
Note the seven domains and their weightage.
Set a target exam date 4 to 6 weeks away if you already know Spark basics.
Step 2Build Spark architecture fundamentals
Become confident with driver, executors, jobs, stages, tasks, lazy evaluation and shuffles.
Revise SparkSession, cluster execution, partitions and transformations vs actions.
Practice questions on stage boundaries, caching and fault tolerance.
Use Spark UI concepts to understand why a query is slow.
Step 3Master DataFrame API tasks
Practise the highest-weighted area: selecting, filtering, joins, aggregation, schemas and writes.
Solve PySpark DataFrame challenges daily.
Practise column expressions, null handling, UDFs, joins and partitioned writes.
Rewrite common SQL logic using DataFrame APIs.
Step 4Revise Spark SQL and functions
Handle SQL questions quickly: temp views, functions, joins, windows and query plans.
Practise Spark SQL syntax with realistic tables.
Review built-in functions and why they are preferred over Python UDFs.
Use explain plans to connect SQL with Spark execution.
Step 5Cover tuning, streaming and new domains
Round out lower-weighted but important topics: AQE, skew, Structured Streaming, Spark Connect and Pandas API on Spark.
Review shuffle partitions, broadcast joins, salting and repartition vs coalesce.
Study Adaptive Query Execution (AQE) for runtime partition, join and skew optimization.
Learn watermarking, checkpointing, output modes and foreachBatch basics.
Understand Spark Connect as a decoupled client-server architecture.
Do not book the official exam after one lucky score. Use short mocks for diagnosis, full mocks for stamina, and review every wrong answer before retrying.
Book the official exam when:You score 80%+ twice in full mocks, finish within 90 minutes, and can explain why each missed answer was wrong.
Databricks Certified Associate Developer for Apache Spark practice hub
Practise, pass and get your PySpark.in certificate automatically
Use the free mocks to diagnose weak areas, then take the full 60-question PySpark.in Spark Developer Certification Exam when you are ready for a certificate-backed assessment.
verifiedAutomatic PySpark.in certificate after passing
Once the PySpark.in Spark Developer Certification Exam is cleared with 70% or higher, the platform generates a downloadable certificate with your name, score and certificate ID.
Certificate included
PAID EXAMMOCK-SPARK-FULL
PySpark.in Spark Developer Certification Exam
90 min60 questionsPass: 70%
A full-length 90-minute Spark assessment from PySpark.in. Clear the exam with 70% or higher and your downloadable certificate is generated automatically with your result.
workspace_premium
Certificate generated on passing
Clear with 70%+ to download your PySpark.in Databricks Certified Associate Developer for Apache Spark certificate immediately.
Rs. 300One-time payment, lifetime access
verified Lifetime accessdescription Auto certificate
Certificate on 70%+
FREE MOCKMOCK-SPARK-20
Spark Core Readiness Check
45 min20 questionsPass: 70%
A focused timed practice to validate Spark architecture, DataFrame, SQL and execution basics before the full mock.
20 timed questionsCore Spark domains
FREE MOCKMOCK-GUIDE-DEMO
Databricks Guide Sample Practice
15 min10 questionsPass: 70%
A compact guide-style warm-up based on official sample patterns for a quick confidence check before deeper practice.
Guide-style questionsFast warm-up
Official exam path
Official exam links and extra learning options
Use Databricks links for source-of-truth exam details, voucher rules and booking. Use PySpark.in practice resources and selected courses to prepare with confidence.
Official DatabricksExam, vouchers and registration
Redirect users to Databricks/Webassessor for source-of-truth exam details, voucher events and booking.
PySpark.in is independent and not affiliated with Databricks. Official vouchers, registration, proctoring and certification decisions are handled only by Databricks/Webassessor. External course links may be partner links at no extra cost to you.