NoSQL database: Consistent read consistency for data
Strong consistency
Access to any node in the cluster at any time, resulting in consistent data results;
User consistency
The same user, access to the cluster during the data consistent;
Resolve user consistency: Use sticky sessions to bind sessions to specific nodes for processing;
This reduces the performance of the load balancer;
Final consistency
The data synchronization between the nodes in the cluster is inconsistent with the temporary data, but after the data synchronization is complete, the final consistency is achieved.
Update consistency
Pessimistic Way
Using write locks to significantly reduce system responsiveness can lead to deadlocks
Optimistic Way
Let the conflict happen first, and then the process of automatic merging is very “ domain-specific ” problem
Easing consistency constraints
Cap theorem
Consistency (consistency), availability (availability), and partition tolerance (Partition tolerance), 3 properties can only meet 2 at a time;
Explanation of partition tolerance: clusters are still available if the cluster is divided into multiple communications failures
CA system
A partition appears in a single-server cluster and is not available
Pa/pc
When a cluster is partitioned, a tradeoff between consistency and availability is typically sacrificed partial consistency (eg: using eventual consistency) to ensure availability
Easing persistent constraints
More stringent durability means more performance loss;
Sacrificing persistence for better performance
Replication Persistence failure
Primary node failure, synchronization to data loss from node recovery, data conflict resolution updated during failure solution: Specify the persistence required for a single request
Attached Mind Map
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Reference
The essence of NoSQL
Posted by: Big CC | 02jul,2014
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