Social graph storage in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the main data structure used for storing user connections in a social graph.

HLD

The social graph is typically stored as a [1] where nodes represent users and edges represent connections.

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Agraph

Barray

Cstack

Dqueue

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing array because it stores lists but doesn't represent connections well.

Choosing stack or queue which are linear and don't model relationships.

The social graph is best represented as a graph data structure because it naturally models users (nodes) and their connections (edges).

2fill in blank

medium

Complete the code to describe the storage method for a social graph with millions of users.

HLD

For scalability, social graphs are often stored in a [1] database that supports relationships efficiently.

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Akey-value

Bgraph

Crelational

Ddocument

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing relational database which can be slow for complex graph queries.

Choosing key-value or document databases which don't natively support relationships.

Graph databases are designed to efficiently store and query relationships, making them ideal for large social graphs.

3fill in blank

hard

Fix the error in describing how to represent user connections in adjacency form.

HLD

An adjacency list stores connections as a dictionary where keys are user IDs and values are lists of [1] user IDs.

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Aconnected

Bunconnected

Crandom

Dinactive

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing unconnected or inactive which do not represent actual connections.

Choosing random which is unrelated.

Adjacency lists store the IDs of users directly connected to each user, so the correct term is connected user IDs.

4fill in blank

hard

Fill both blanks to complete the description of a common query on social graphs.

HLD

To find mutual friends between two users, we compute the intersection of their [1] lists and then filter by [2].

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Afriend

Bfollowers

Cactive

Dconnections

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'followers' which is a one-way relationship, not mutual.

Using 'friend' which is singular and less precise than 'connections'.

We find mutual friends by intersecting the connections lists of two users and then filtering by active status to ensure relevance.

5fill in blank

hard

Fill all three blanks to complete the code snippet for storing social graph data efficiently.

HLD

storage = [1].partition_by([2]).replicate([3])

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Agraph_db

Buser_id

C3

Drelational_db

Attempts:

3 left

💡 Hint

Common Mistakes

Using relational_db which is less efficient for graph data.

Incorrect replication factor or partition key.

Graph databases (graph_db) partition data by user_id for load balancing and replicate data 3 times for fault tolerance.