NoSQL Database: consistent data reading strong consistency access to any node in the cluster at any time, and the data results are consistent. consistent user consistency is consistent with the data obtained during cluster access for the same user; solve user consistency: Use a sticky session to bind the session to a specific node for processing; this will reduce the performance of the Load balancer;
NoSQL Database: consistent data reading strong consistency access to any node in the cluster at any time, and the data results are consistent. consistent user consistency is consistent with the data obtained during cluster access for the same user; solve user consistency: Use a sticky session to bind the session to a specific node for processing; this will reduce the performance of the Load balancer;
NoSQL Database: consistent reading of data
High Consistency
Access any node in the cluster at any time, and the data obtained is consistent;
User consistency
For the same user, the data obtained during cluster access is consistent;
Solve user consistency: Use a sticky session to bind the session to a specific node for processing;
This will reduce the performance of the Load balancer;
Final consistency
Temporary data inconsistency occurs between nodes in the cluster due to delayed data synchronization. However, after data synchronization is completed, the data consistency is achieved;
Update consistency pessimistic Mode
The use of write locks significantly reduces system response capabilities and may lead to deadlocks.
Optimistic
Conflict occurs first, and then the processing method of automatic merging of sequence is extremely "domain-specific ".
Relax the "consistency constraint" CAP Theorem
Consistency, Availability, and Partition tolerance. The three attributes can only satisfy two at the same time;
Partition tolerance explanation: the cluster is still available when it is divided into multiple due to communication faults
CA system
"Partition" is not available in a single server cluster
PA/PC
When a "partition" occurs in a cluster, the trade-off between "consistency" and "availability" generally sacrifices partial consistency (eg: Use final consistency) to ensure availability.
Relax "persistence" constraints
More Strict Persistence means more performance loss;
Sacrifice "persistence" in exchange for better performance replication "persistence" faults
Master node failure, not synchronized to data loss from the slave node master node recovery, data conflict solution updated during the fault: specify the required durability for a single request
Mind Map
Reference
NoSQL Essence
Posted by: Large CC | 02JUL, 2014
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