실제 시험과 유사한 환경에서 연습하면 시험 당일의 긴장을 줄이는 데 도움이 됩니다. DumpTOP의 Associate-Developer-Apache-Spark 모의고사는 실전 환경을 재현한 테스트 엔진으로 2026년 Databricks Certified Associate Developer for Apache Spark 3.0 시험에 대비하실 수 있도록 지원합니다.

Databricks Associate-Developer-Apache-Spark 시험 개요:

Databricks Associate-Developer-Apache-Spark 시험 요강 주제:

Databricks Associate-Developer-Apache-Spark 응시 전 꼭 확인해야 할 질문들

최신 Databricks Certification Associate-Developer-Apache-Spark 무료샘플문제

문제 #1

The code block shown below should return a new 2-column DataFrame that shows one attribute from column attributes per row next to the associated itemName, for all suppliers in column supplier whose name includes Sports. Choose the answer that correctly fills the blanks in the code block to accomplish this.
Sample of DataFrame itemsDf:
1.+------+----------------------------------+-----------------------------+-------------------+
2.|itemId|itemName |attributes |supplier |
3.+------+----------------------------------+-----------------------------+-------------------+
4.|1 |Thick Coat for Walking in the Snow|[blue, winter, cozy] |Sports Company Inc.|
5.|2 |Elegant Outdoors Summer Dress |[red, summer, fresh, cooling]|YetiX |
6.|3 |Outdoors Backpack |[green, summer, travel] |Sports Company Inc.|
7.+------+----------------------------------+-----------------------------+-------------------+ Code block:
itemsDf.__1__(__2__).select(__3__, __4__)

A. 1. where
2. col("supplier").contains("Sports")
3. "itemName"
4. "attributes"
B. 1. filter
2. col("supplier").isin("Sports")
3. "itemName"
4. explode(col("attributes"))
C. 1. where
2. "Sports".isin(col("Supplier"))
3. "itemName"
4. array_explode("attributes")
D. 1. filter
2. col("supplier").contains("Sports")
3. "itemName"
4. explode("attributes")
E. 1. where
2. col(supplier).contains("Sports")
3. explode(attributes)
4. itemName

문제 #2

The code block displayed below contains an error. The code block should return a DataFrame where all entries in column supplier contain the letter combination et in this order. Find the error.
Code block:
itemsDf.filter(Column('supplier').isin('et'))

A. The Column operator should be replaced by the col operator and instead of isin, contains should be used.
B. The expression only returns a single column and filter should be replaced by select.
C. The expression inside the filter parenthesis is malformed and should be replaced by isin('et', 'supplier').
D. Instead of isin, it should be checked whether column supplier contains the letters et, so isin should be replaced with contains. In addition, the column should be accessed using col['supplier'].

문제 #3

Which of the following is not a feature of Adaptive Query Execution?

A. Collect runtime statistics during query execution.
B. Coalesce partitions to accelerate data processing.
C. Split skewed partitions into smaller partitions to avoid differences in partition processing time.
D. Replace a sort merge join with a broadcast join, where appropriate.
E. Reroute a query in case of an executor failure.

문제 #4

Which of the following describes the characteristics of accumulators?

A. If an action including an accumulator fails during execution and Spark manages to restart the action and complete it successfully, only the successful attempt will be counted in the accumulator.
B. All accumulators used in a Spark application are listed in the Spark UI.
C. Accumulators are used to pass around lookup tables across the cluster.
D. Accumulators can be instantiated directly via the accumulator(n) method of the pyspark.RDD module.
E. Accumulators are immutable.

문제 #5

Which of the following statements about executors is correct, assuming that one can consider each of the JVMs working as executors as a pool of task execution slots?

A. Slot is another name for executor.
B. Tasks run in parallel via slots.
C. There must be less executors than tasks.
D. An executor runs on a single core.
E. There must be more slots than tasks.

질문과 대답: