Databricks

Databricks Spark Developer Associate: Practice Questions

360 Python-focused questions, four topic tests and two 45-question mocks for Spark developer certification preparation

DatabricksAmerican English6 套练习

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Databricks Spark Developer Associate: Practice Questions

课程概览

你将练习的内容

题目及解析语言:American English

考试参考Databricks
本课程版本发布日期
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  • Explain Spark execution, resource roles, caching, partitioning and deployment decisions.
  • Choose Spark SQL and data-source APIs for specified file, JDBC, table and view requirements.
  • Predict DataFrame results involving nulls, duplicates, dates, joins, schemas and column transformations.
  • Diagnose performance and memory issues using partition behavior, AQE and driver or executor evidence.
  • Reason about streaming output modes, windows, checkpoints, state and watermark-based deduplication.
  • Identify Spark Connect boundaries and apply pandas API on Spark and pandas UDF contracts.

了解完整课程

This course contains the use of artificial intelligence.

Prepare for the Databricks Certified Associate Developer for Apache Spark with 360 original practice questions that ask you to reason about code, data, execution and operational constraints. This course follows the seven domains in the exam guide effective October 30, 2025, including Spark Connect and the pandas API on Spark.

A structured practice path

Start with four focused tests containing 270 questions. Use them to identify gaps and revisit the documentation before attempting two full-length mocks. Each mock contains 45 single-answer questions with a 90-minute practice limit. Domain counts are rounded to whole questions from the published weights; these mocks model scored content rather than any additional unscored exam items.

The six tests cover:

  • Architecture, execution hierarchy, resources, caching, Spark modules, Connect and deployment modes.
  • Spark SQL, JDBC and file sources, save modes, persistent tables, temporary views, pandas APIs and pandas UDFs.
  • DataFrame transformations, data quality, aggregation, dates, joins, schemas, sorting, UDFs, broadcasts and accumulators.
  • Partition tuning, Adaptive Query Execution, troubleshooting, streaming outputs, windows, checkpoints and deduplication.
  • Two mixed-domain mocks that use different decisions and conditions to help you assess readiness.

Learn from each decision

Every question includes feedback for all four options, an overall explanation, a revision tip and links to relevant official documentation. Practice includes predicting small outputs, selecting an API that meets stated requirements, recognizing an invalid assumption, and using evidence to diagnose a problem. The aim is to understand the reasoning behind an answer so that you can apply it to a different situation.

Examples use Python and documented Apache Spark 3.5 APIs. The exam guide does not specify a particular runtime patch version; this documentation baseline is not a claim that the exam is restricted to Spark 3.5.6. A Spark environment is useful for your own experiments, but it is not required to take the tests.

Use your results constructively

The course's 80% score target is an author-defined revision goal, not an official passing score or a guarantee of certification. Review incorrect answers and answers you guessed, then try the second mock without checking explanations during the attempt. Use the current official exam guide for registration details and any later changes to the exam.

This is an independent practice resource, not an official Databricks course or an actual exam question bank. It is not affiliated with or endorsed by Databricks or the Apache Software Foundation.

练习安排

6 套练习. 360 道题.

01

Architecture, Components, Connect and Deployment

68 道题136 分钟

02

Spark SQL, Data Sources and Pandas APIs

67 道题134 分钟

03

DataFrame Transformations and Application Logic

81 道题162 分钟

04

Tuning, Troubleshooting and Structured Streaming

54 道题108 分钟

05

Full-Length Mock Exam 1

45 道题90 分钟

06

Full-Length Mock Exam 2

45 道题90 分钟

免费课程体验

先作答,再理解。

本课程的三道原创单选样题。作答仅在当前页面保留,离开后清除。

选择一个答案1 / 3

A team runs a 20 KB calculation once per day. Its current local script takes 30 milliseconds. Why might moving it to a Spark cluster increase latency?

开始前的准备

  • Working knowledge of Python, SQL and basic DataFrame operations.
  • Familiarity with introductory Apache Spark concepts; this is a practice course rather than a first tutorial.
  • Optional access to a Spark environment for trying examples and exploring the linked documentation.

适合哪些学习者

  • Developers preparing for the Databricks Certified Associate Developer for Apache Spark exam.
  • Data engineers who want to test their reasoning about PySpark transformations and execution.
  • Learners who have studied the basics and want focused practice followed by timed mixed-domain mocks.

常见问题

迈出下一步之前。

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不包含。课程是独立备考材料,正式考试报名、费用和证书由认证机构提供。

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