System Design - Scalability: Sharding Test 1

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Questions and Answers

What is the trade-off between consistency and latency in distributed systems?

More consistency increases complexity and latency, while high availability and performance may require sacrificing some consistency.

How do compensating transactions maintain data integrity in distributed systems?

Compensating transactions undo the effects of previously committed transactions in case of failures or inconsistencies.

What is the primary drawback of synchronous replication in distributed systems?

Synchronous replication may introduce latency, waiting for all replicas to acknowledge writes.

How do automated failover mechanisms ensure high availability in primary-replica configurations?

They switch to a replica if the primary fails, ensuring high availability and minimizing downtime. Signup and view all the answers

What is the primary advantage of multi-data center deployment in distributed systems?

It ensures availability during regional outages and reduces latency for users in different geographic locations. Signup and view all the answers

What is the main challenge of cross-shard queries in distributed systems?

Increased complexity in query design and optimization, and higher latency due to data being fetched from multiple sources. Signup and view all the answers

How does eventual consistency differ from strong consistency in distributed systems?

Eventual consistency allows temporary inconsistencies, whereas strong consistency ensures immediate consistency. Signup and view all the answers

What is the key advantage of asynchronous replication in distributed systems?

It provides higher performance and reduces latency by not waiting for all replicas to acknowledge writes. Signup and view all the answers

What is the primary concern when choosing a shard key in a database sharding strategy?

Distributing data evenly across shards Signup and view all the answers

How does sharding improve database performance, and what is the main consequence of this improvement?

By distributing data across multiple servers, reducing query response times; and the main consequence is improved scalability Signup and view all the answers

What is the key difference between horizontal and vertical partitioning in database systems?

Horizontal partitioning divides a database table into rows, while vertical partitioning divides a database table into columns Signup and view all the answers

What is the main advantage of hash-based sharding over range-based sharding, and what is the trade-off?

Hash-based sharding provides better load balancing, but makes range queries challenging Signup and view all the answers

How does directory-based sharding differ from other sharding strategies, and what is the main benefit of this approach?

Directory-based sharding uses a lookup table to map each shard key to a specific shard, providing better performance and scalability Signup and view all the answers

What is the primary reason for using sharding in database systems, and what are the resulting benefits?

To improve database performance, scalability, and availability, resulting in improved performance, increased scalability, and enhanced availability Signup and view all the answers

What is the main challenge in implementing sharding in a database system, and how can it be addressed?

The main challenge is distributing data evenly across shards, which can be addressed by choosing a suitable shard key and sharding strategy Signup and view all the answers

What are the implications of a poor sharding strategy on database performance and scalability, and how can they be mitigated?

A poor sharding strategy can lead to unbalanced loads, reduced performance, and scalability issues, which can be mitigated by choosing a suitable sharding strategy and shard key Signup and view all the answers

What are the trade-offs of using composite sharding, and how does it address the limitations of other sharding approaches?

Composite sharding offers flexibility and granularity but requires an additional mapping layer. It addresses the limitations of other sharding approaches by providing more control over data distribution. Signup and view all the answers

How does consistent hashing mitigate the impact of shard changes on the overall system, and what are the benefits of using this approach?

Consistent hashing distributes data evenly across shards and minimizes data movement when adding or removing shards, reducing the impact of shard changes on the system. The benefits include even data distribution and minimal data movement. Signup and view all the answers

What are the primary challenges of re-sharding, and how can proactive re-sharding help alleviate these concerns?

The primary challenges of re-sharding include ensuring data consistency, minimizing downtime, and handling split-brain scenarios. Proactive re-sharding can help alleviate these concerns by anticipating growth and performance issues and redistributing data before issues arise. Signup and view all the answers

How does the dual-writes technique ensure zero-downtime migrations during re-sharding, and what are the benefits of this approach?

The dual-writes technique ensures zero-downtime migrations by temporarily writing to both the old and new shard configurations, ensuring that no data is lost during the migration process. The benefits include ensuring continuous service availability during data redistribution. Signup and view all the answers

What are the primary differences between proactive and reactive re-sharding, and when would you use each approach?

Proactive re-sharding involves anticipating growth and performance issues by periodically evaluating the distribution of data and redistributing it before issues arise. Reactive re-sharding involves triggering re-sharding in response to detected imbalances or performance degradation. You would use proactive re-sharding when anticipating growth and reactive re-sharding when responding to detected issues. Signup and view all the answers

How does the Three-Phase Commit (3PC) protocol address the limitations of the Two-Phase Commit (2PC) protocol, and what are the benefits of using 3PC?

The 3PC protocol adds an extra phase to 2PC to mitigate the blocking problem and reduce the likelihood of coordinator failure. The benefits include reducing the likelihood of coordinator failure and allowing for non-blocking transactions. Signup and view all the answers

What are the primary advantages of using hash-based sharding, and how do these benefits impact the overall system performance?

The primary advantages of using hash-based sharding are even data distribution and simplicity. These benefits impact the overall system performance by providing a more efficient and balanced data distribution. Signup and view all the answers

How does incremental data copying reduce the risk of data inconsistency during migration, and what are the benefits of this approach?

Incremental data copying reduces the risk of data inconsistency by gradually copying data from old shards to new ones in small batches, minimizing the impact on system performance. The benefits include reducing the risk of data inconsistency and ensuring a smooth transition. Signup and view all the answers

What are the primary benefits of using dynamic sharding, and how does it adapt to changing data volumes and system loads?

The primary benefits of using dynamic sharding are that it adapts to changing data volumes and system loads by adjusting the number of shards based on the current load and data volume. This provides a more balanced and efficient data distribution. Signup and view all the answers

How does the blue-green deployment approach ensure a smooth transition during re-sharding, and what are the benefits of using this approach?

The blue-green deployment approach ensures a smooth transition during re-sharding by maintaining two parallel environments (old and new shards) and switching traffic seamlessly after the new configuration is fully tested. The benefits include minimizing downtime and ensuring a smooth transition. Signup and view all the answers

Study Notes

Database Sharding

Sharding is a type of database partitioning that splits large databases into smaller, faster, more easily managed parts called shards.
Each shard is an independent database that holds a subset of the data.

Sharding Benefits

Sharding improves database performance, scalability, and availability by distributing data across multiple servers.
It balances the load, reduces query response times, and handles large volumes of data more efficiently.

Horizontal vs Vertical Partitioning

Horizontal partitioning (sharding) involves dividing a database table into rows, with each shard containing a subset of the rows.
Vertical partitioning involves dividing a database table into columns, with each partition containing a subset of the columns.

Shard Key

A shard key is a specific column or set of columns used to determine which shard a particular row of data belongs to.
The choice of shard key is crucial for distributing data evenly across shards.

Sharding Strategies

Hash-Based Sharding

Hash-based sharding uses a hash function on the shard key to distribute data evenly across shards.
This method helps balance the load but can make range queries challenging.

Range-Based Sharding

Range-based sharding divides data into contiguous ranges based on the shard key.
This is useful for queries that involve ranges but can lead to unbalanced loads if the data distribution is skewed.

Directory-Based Sharding

Directory-based sharding uses a lookup table to map each shard key to a specific shard.
This approach offers flexibility but requires maintaining an additional mapping layer.

Composite Sharding

Composite sharding uses multiple columns as the shard key to provide more granularity and control over data distribution.
For example, combining user ID and region ID can help distribute data based on both user identification and geographic location.

Advanced Sharding Concepts

Dynamic Sharding

Dynamic sharding adjusts the number of shards based on the current load and data volume.
This approach requires monitoring and dynamically reallocating data as needed to maintain balanced shards.

Consistent Hashing

Consistent hashing distributes data evenly across shards and minimizes data movement when adding or removing shards.
It reduces the impact of shard changes on the overall system.

Re-Sharding Challenges

Challenges include ensuring data consistency during migration, minimizing downtime, handling split-brain scenarios, and managing the complexity of redistributing data.

Proactive vs Reactive Re-Sharding

Proactive re-sharding involves anticipating growth and performance issues by periodically evaluating the distribution of data and redistributing it before issues arise.
Reactive re-sharding involves triggering re-sharding in response to detected imbalances or performance degradation.

Zero-Downtime Migrations

Dual-Writes Technique

Dual-writes involve temporarily writing to both the old and new shard configurations while reading from the old until the migration is complete.
This ensures that no data is lost during the migration process.

Blue-Green Deployment

Blue-green deployment involves maintaining two parallel environments (old and new shards) and switching traffic seamlessly after the new configuration is fully tested.
This minimizes downtime and ensures a smooth transition.

Consistency Checks

Consistency checks ensure that the data in the old and new shards remains consistent throughout the migration process.
This helps prevent data loss or corruption.

Incremental Data Copying

Incremental data copying involves gradually copying data from old shards to new ones in small batches to minimize impact on system performance and reduce the risk of data inconsistency.

Managing Distributed Transactions

Two-Phase Commit (2PC) Protocol

The Two-Phase Commit (2PC) protocol is a distributed transaction protocol that ensures atomicity by dividing the transaction into two phases: prepare and commit.
It ensures that either all participants commit the transaction or none do.

Three-Phase Commit (3PC) Protocol

The Three-Phase Commit (3PC) protocol adds an extra phase to 2PC to mitigate the blocking problem and reduce the likelihood of coordinator failure.
It provides more safety but increases complexity and latency.

Eventual Consistency

Eventual consistency is a consistency model where, given enough time, all replicas will converge to the same value.
It allows temporary inconsistencies and is suitable for applications that can tolerate them.

Compensating Transactions

Compensating transactions are used to undo the effects of previously committed transactions in case of failures or inconsistencies.
They help maintain data integrity in eventual consistency models.

Ensuring High Availability

Synchronous Replication

Synchronous replication ensures immediate consistency by waiting for all replicas to acknowledge writes before considering the operation complete.
It guarantees data consistency but may introduce latency.

Asynchronous Replication

Asynchronous replication provides higher performance by not waiting for all replicas to acknowledge writes.
It allows for temporary inconsistencies but reduces latency and improves throughput.

Primary-Replica Configuration

In a primary-replica configuration, one primary shard handles writes, and multiple replicas handle reads.
Automated failover mechanisms switch to a replica if the primary fails, ensuring high availability.

Multi-Data Center Deployment

Multi-data center deployment involves deploying shards across multiple data centers to ensure availability during regional outages and reduce latency for users in different geographic locations.

Cross-Shard Queries

Cross-shard queries allow performing complex queries across multiple shards.
Benefits include the ability to perform complex queries, while challenges include increased complexity in query design and optimization, as well as higher latency due to data being fetched from multiple sources.

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