Databricks-DA-Assoc Analyzing Queries Practice Question
When analyzing the execution plan of a query in Databricks SQL, what does a 'BroadcastHashJoin' node typically indicate?
⚠ Common exam trap
Candidates frequently mistake a BroadcastHashJoin for an indicator of data skew or network bottlenecks, when it actually represents an optimized join strategy.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The optimizer successfully avoided a network shuffle by sending a small table to all executors.
A BroadcastHashJoin indicates that the query optimizer determined one table was small enough to be duplicated across all nodes. This avoids expensive shuffles by performing the join locally on each partition. Understanding execution plans allows analysts to verify if their queries are executing as intended and helps identify opportunities to apply hints or optimize join operations for better performance on large-scale distributed data processing tasks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The query is performing a cross join between two large tables.
Why it's wrong here
A BroadcastHashJoin is specifically designed to avoid the performance penalties of large-scale shuffles by broadcasting a small table. A cross join between two large tables would typically result in a Cartesian product or a SortMergeJoin, which are significantly more resource-intensive and likely to cause job failures.
- ✓
The optimizer successfully avoided a network shuffle by sending a small table to all executors.
Why this is correct
This join strategy is chosen when one side of the join is small enough to fit into memory on each worker node. By broadcasting this table, the engine eliminates the need to redistribute the larger table across the network, resulting in much faster execution and reduced cluster load.
- ✗
The query is failing because the join keys are not indexed.
Why it's wrong here
Spark SQL does not rely on traditional database indexes for joins. While partitioning and Z-Ordering help with data skipping, a BroadcastHashJoin is an execution-time optimization strategy that is independent of any column indexing, meaning this node type is not an indicator of missing index structures.
- ✗
The data is being read from multiple external storage locations simultaneously.
Why it's wrong here
Reading from multiple locations relates to the scan phase of a query execution, not the join strategy. The BroadcastHashJoin specifically describes how rows are matched between two datasets after they have been processed or loaded, rather than how the raw bytes are retrieved from underlying storage.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DA-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DA-Assoc exam.