Write sharding in DynamoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the main purpose of write sharding in DynamoDB?

Write sharding is used in DynamoDB to:

A Distribute write requests across multiple partitions to increase write throughput

B Encrypt data at rest for security

C Automatically backup data to S3

D Reduce read latency by caching data

💡 Hint

Think about how DynamoDB handles many writes at once.

Write sharding spreads write load across partitions to avoid throttling and improve performance.

❓ query_result

intermediate

What is the output count of items after applying write sharding with 3 shards?

Suppose you have a table with 9 items and you apply write sharding with 3 shards by adding a shard key with values 0, 1, or 2. How many total items will be in the table after sharding?

A 3

B 9

C 27

D 0

💡 Hint

Each original item is duplicated across shards with different shard keys.

Each of the 9 items is duplicated 3 times with different shard keys, so total items = 9 * 3 = 27.

📝 Syntax

advanced

Which DynamoDB update expression correctly increments a shard counter?

Given a DynamoDB item with attribute shardCount, which update expression correctly increments it by 1?

DynamoDB

UpdateExpression = ?

A SET shardCount = shardCount + :inc

B ADD shardCount :inc

C INCREMENT shardCount BY 1

D SET shardCount += 1

💡 Hint

DynamoDB uses ADD to increment numeric attributes.

The ADD keyword increments numeric attributes atomically. Other options are invalid syntax.

❓ optimization

advanced

How does write sharding improve DynamoDB write capacity usage?

Choose the best explanation for how write sharding optimizes write capacity in DynamoDB.

A It caches writes in memory before sending to DynamoDB

B It compresses data to reduce storage size

C It batches writes into a single request to reduce network calls

D It spreads writes across multiple partition keys to avoid hot partitions and throttling

💡 Hint

Think about how DynamoDB partitions data internally.

Write sharding distributes writes across different partition keys, preventing any single partition from becoming a bottleneck.

🔧 Debug

expert

Why does this write sharding implementation cause throttling errors?

You implemented write sharding by adding a random shard key from 0 to 4 to each item. However, you still get throttling errors on writes. What is the most likely cause?

Code snippet:

shard_key = random.randint(0, 4)
item['shard'] = shard_key
put_item(item)

A The shard key is not part of the partition key, so writes still go to the same partition

B Random shard keys cause duplicate items and data corruption

C The code does not batch writes, causing network overhead

D The shard key values are too small, causing uneven distribution

💡 Hint

Check how DynamoDB partitions data based on keys.

If the shard key is not included in the partition key, DynamoDB does not distribute writes across partitions, causing hot partitions and throttling.