- A
Coalesce the number of partitions to reduce overhead.
Why wrong: Coalescing reduces partitions, potentially increasing shuffle size.
- B
Enable checkpointing to persist intermediate results.
Why wrong: Checkpointing adds disk I/O but does not directly reduce shuffling.
- C
Broadcast one of the tables if it is small enough to fit in memory.
Broadcast join eliminates shuffle by replicating the small table to all executors.
- D
Disable dynamic resource allocation.
Why wrong: Disabling dynamic allocation may cause resource underutilization or contention.
- E
Increase the number of shuffle partitions using 'spark.sql.shuffle.partitions'.
More partitions can reduce the amount of data per task, reducing shuffle pressure.
Quick Answer
The correct actions are to increase the number of shuffle partitions using spark.sql.shuffle.partitions and to broadcast a small lookup table to avoid shuffles in joins. Excessive shuffling in Azure Synapse occurs when data is redistributed across executors, causing long execution times; increasing partitions spreads data more evenly, reducing the volume of data moved per task, while broadcasting eliminates the shuffle entirely for small tables by sending a read-only copy to each executor. On the DP-203 exam, this tests your understanding of Spark’s shuffle mechanics and the trade-offs between partitioning and broadcast joins—a common trap is choosing coalesce, which reduces partitions and worsens the bottleneck, or disabling dynamic allocation, which starves resources. Remember the mnemonic “Broadcast to bypass, partition to parallelize” to recall that small tables should be broadcast and large datasets need more partitions for balanced shuffling.
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO actions should you take to optimize a Spark job in Azure Synapse Analytics that is experiencing excessive shuffling and long execution times?
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
Broadcast one of the tables if it is small enough to fit in memory.
Option A is correct because broadcasting a small lookup table can avoid shuffles in joins. Option C is correct because increasing the number of partitions can spread data more evenly, reducing shuffle size. Option B is wrong because coalescing reduces partitions, which may worsen shuffling. Option D is wrong because disabling dynamic allocation may lead to resource contention. Option E is wrong because enabling checkpointing adds overhead and does not directly reduce shuffling.
Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Coalesce the number of partitions to reduce overhead.
Why it's wrong here
Coalescing reduces partitions, potentially increasing shuffle size.
- ✗
Enable checkpointing to persist intermediate results.
Why it's wrong here
Checkpointing adds disk I/O but does not directly reduce shuffling.
- ✓
Broadcast one of the tables if it is small enough to fit in memory.
Why this is correct
Broadcast join eliminates shuffle by replicating the small table to all executors.
Related concept
CIDR notation defines the prefix length.
- ✗
Disable dynamic resource allocation.
Why it's wrong here
Disabling dynamic allocation may cause resource underutilization or contention.
- ✓
Increase the number of shuffle partitions using 'spark.sql.shuffle.partitions'.
Why this is correct
More partitions can reduce the amount of data per task, reducing shuffle pressure.
Related concept
CIDR notation defines the prefix length.
Common exam traps
Common exam trap: usable hosts are not the same as total addresses
Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.
Detailed technical explanation
How to think about this question
Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.
KKey Concepts to Remember
- CIDR notation defines the prefix length.
- Block size helps identify subnet boundaries.
- Network and broadcast addresses are not usable hosts in normal IPv4 subnets.
- The required host count determines the smallest suitable subnet.
TExam Day Tips
- Write the block size before choosing the subnet.
- Check whether the question asks for hosts, subnets or a specific address range.
- Do not confuse /24, /25, /26 and /27 host counts.
Key takeaway
Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related DP-203 subnetting questions on CIDR, address ranges, and subnet selection.
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Develop data processing — study guide chapter
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FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — CIDR notation defines the prefix length..
What is the correct answer to this question?
The correct answer is: Broadcast one of the tables if it is small enough to fit in memory. — Option A is correct because broadcasting a small lookup table can avoid shuffles in joins. Option C is correct because increasing the number of partitions can spread data more evenly, reducing shuffle size. Option B is wrong because coalescing reduces partitions, which may worsen shuffling. Option D is wrong because disabling dynamic allocation may lead to resource contention. Option E is wrong because enabling checkpointing adds overhead and does not directly reduce shuffling.
What should I do if I get this DP-203 question wrong?
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related DP-203 subnetting questions on CIDR, address ranges, and subnet selection.
What is the key concept behind this question?
CIDR notation defines the prefix length.
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Last reviewed: Jun 21, 2026
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