Databricks Certified Associate Developer for Apache Spark practice examsIn development
Databricks Certified Associate Developer for Apache Spark
The de facto Spark credential: driver and executors with one task per partition bounding parallelism, lazy transformations against eager actions and the narrow-wide distinction that decides cost, the DataFrame verbs and join types including semi and anti, then the Catalyst optimiser with predicate pushdown and column pruning, the file formats and write modes, lazy caching and the coalesce against repartition choice, and diagnosing skew, spill and shuffle in the Spark UI.
What you get
Papers are cut from the bank and weighted like the real exam, and no question appears in two of them. Every wrong answer comes back on later days until you have it right.
What the exam covers
| The Spark architecture and the DataFrame API | Not published |
| Execution, input and output, and tuning | Not published |
Two sample questions
1. Which approach makes a write safe to repeat?
- A blind append
- A truncate then append
- An idempotent merge on a business key — correct
- No approach
Why: A keyed merge produces the same result whether run once or several times.
2. How does Spark treat nulls in a comparison?
- A null comparison yields null, not true — correct
- Nulls always compare as equal to zero
- Nulls are dropped before any comparison
- Nulls are treated as empty strings
Why: Comparisons with null return null, so explicit null-handling functions are needed to test for them.
The real Databricks Certified Associate Developer for Apache Spark exam
| Length | 120 minutes |
|---|---|
| Questions | 60 |
| Pass mark | 70% |
| Price | Purchased per attempt through the Databricks certification portal |
| Recommended before you sit it | None enforced. Working Python or Scala and six months of Spark use are assumed. |
| Valid for | 2 years |
Exam facts as published by Databricks; always check the vendor’s page before you book.
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