英文:
Age's extension using distributed graph processing
问题
分布式图处理涉及分析分布在多台机器上的大规模图形。在这种方法中，将大图数据分割成小图，然后在不同的机器上处理所有这些小图。
我的问题是Apache Age如何确保在这种情况下的一致性和可靠性。
英文:
Since distributed graph processing involves the analyzing large scale graphs distributed across multiple machines. In this approach the large graph data is partitioned into small graphs and all those small graphs are processed on different machines.
My question is that how does Apache Age ensure consistency and reliability in this scenario.
答案1
得分: 2
Apache age（PostgreSQL的图形扩展）意味着它继承了PostgreSQL的数据一致性和可靠性特性。
它增加了额外的机制，以确保图处理中的一致性和可靠性。
它通过允许存储在不同机器上的相同数据的多个副本来实现容错。
它提供了分布式锁管理器和主从节点架构。
英文:
As Apache age ( a graph extension of PostgreSQL) means that it inherits the PostgreSql features for the data consistency and reliability.
It adds additional mechanisms to ensure the consistency and the reliability in graph processing.
It provides us Fault tolerant by allowing multiple replicas of same data that stored on different machines.
It provides us Distributed lock manager and master-slave node architecture.
答案2
得分: 0
有许多可以用来确保可靠性和一致性的方法，其中一些如下所示：
- 复制
- 容错性
- 一致性
第一个机制有助于确保数据始终存在，即使您的机器出现故障。
第二种方法提供功能，帮助系统在相关机器出现故障时继续在备用机器上运行。
对于一致性，AGE 确保每个事务都已提交或回滚。
英文:
There are many methods that can be used to ensure reliability and consistency, some of them are as follows:
- Replication
- Fault Tolerance
- Consistency
The first mechanism helps to make sure that data is always present even if your machine fails.
The second method gives functionality that helps the system to continue working on the alternate machines, if the concerned machine fails.
For the consistency, AGE make sure that every transaction is committed rolled back.
答案3
得分: 0
Apache AGE 使用各种分布式系统概念，例如
-
一致性哈希：这将图数据分区到多台机器上，确保如果一台机器失败或加入集群，只需重新分区图的一小部分。
-
复制
分布式事务：这确保多台机器可以共同执行涉及多个子图的事务。分布式事务确保事务中的所有操作要么全部提交，要么一起中止，确保一致性。
英文:
Apache AGE uses various distributed systems concepts such as
-
Consistent hashing: This partitions the graph data across multiple machines, which ensures that if a machine fails or joins the cluster, only a small portion of the graph needs to be re-partitioned.
-
Replication
Distributed transactions: This ensures that multiple machines can work together to perform a transaction that involves multiple subgraphs. Distributed transactions ensure that all operations in a transaction are either committed or aborted together, ensuring consistency.
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