Database sharding strategies in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the sharding key in a database shard.

HLD

shard_key = request.get('[1]')

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Asession_id

Btimestamp

Ctransaction_id

Duser_id

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a timestamp as shard key can cause hotspotting.

Using session_id may not distribute data evenly.

The user_id is commonly used as a sharding key to distribute data evenly across shards.

2fill in blank

medium

Complete the code to calculate the shard number using modulo sharding.

HLD

shard_number = hash(user_id) [1] total_shards

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A+

B%

C/

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using division instead of modulo causes float results.

Adding hash and total_shards does not map to a shard.

The modulo operator % is used to map the hash value to a shard number within the total shards.

3fill in blank

hard

Fix the error in the shard lookup function to correctly route requests.

HLD

def get_shard(user_id):
    shard_id = hash(user_id) [1] num_shards
    return shards[shard_id]

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A/

B+

C%

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using division returns float, causing index errors.

Multiplying or adding does not limit shard_id range.

The modulo operator % ensures the shard_id is within the valid shard range.

4fill in blank

hard

Fill both blanks to implement range-based sharding for user IDs.

HLD

if user_id [1] 1000:
    shard = shards[[2]]

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A<

B>

C0

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using > instead of < reverses the condition.

Assigning shard 1 instead of 0 for this range.

Users with IDs less than 1000 go to shard 0.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension for consistent hashing buckets.

HLD

buckets = [1]: hash([2]) [3] num_buckets for [2] in nodes}

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Anode

C%

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiplication instead of modulo for bucket assignment.

Mismatching key and iteration variable names.

The comprehension maps each node to a bucket using modulo of its hash.