DP-700 Monitor and Optimize an Analytics Solution Practice Question
Exhibit
{
"queryPlan": {
"operators": [
{ "type": "RemoteScan", "target": "OneLake", "details": "Table1" },
{ "type": "HashJoin", "condition": "Equal", "output": 100000000 },
{ "type": "BroadcastExchange", "details": "SmallTable" }
]
}
}Refer to the exhibit. You are reviewing the execution plan for a query running on a Fabric SQL Analytics Endpoint. The query is performing slower than expected. Based on the JSON snippet of the plan, what is the most likely cause of the performance bottleneck?
⚠ Common exam trap
Candidates often mistake a BroadcastExchange for a successful optimization without checking the output row counts, assuming that broadcasting is always the correct join strategy regardless of table size.
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 BroadcastExchange is moving too much data for a large table join.
Analyzing query plans in the SQL Analytics Endpoint is vital for performance tuning. The presence of a BroadcastExchange for a table that results in a very high output count after a HashJoin suggests that the data being moved across the network is excessive. This often happens when the engine incorrectly estimates the size of a table or when data is not properly distributed.
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 RemoteScan is failing to find the Parquet files in OneLake.
Why it's wrong here
If the RemoteScan failed to find files, the query would result in an error rather than just being slow. The query plan shows that the scan is a part of the execution, meaning the engine has successfully located the metadata and is proceeding to read the data from OneLake storage.
- ✓
The BroadcastExchange is moving too much data for a large table join.
Why this is correct
BroadcastExchange is efficient for small tables but becomes a bottleneck if the table is large, as it sends a full copy of the data to every compute node. The high output row count indicates that a significant volume of data is being processed, which can saturate the network and degrade performance.
- ✗
The HashJoin is using an unsupported data type for the join condition.
Why it's wrong here
Unsupported data types would prevent the query from being compiled or executed by the SQL Analytics Endpoint. Since the plan shows a HashJoin operator, the engine has already validated the join condition and determined that a hash-based join is the most appropriate physical operation for the provided SQL.
- ✗
OneLake storage is currently in a read-only state due to maintenance.
Why it's wrong here
OneLake is designed for high availability and does not typically enter a 'read-only' state that would allow query planning but slow down execution. Any storage-level availability issues would manifest as connection errors or time-outs rather than a specific operator like a BroadcastExchange appearing in a query plan.
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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 Microsoft exam blueprint
This DP-700 practice question is part of Courseiva's free Microsoft 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 DP-700 exam.