Neo4j的水平可伸缩性项目Rassilon的状态如何? [英] What is the status on Neo4j's horizontal scalability project Rassilon?

问题描述

只是想知道是否有人对项目Rassilon的状态有任何了解，Rassilon是Neo4j的侧项目，其重点是改善Neo4j的水平可扩展性?

Just wondering if anyone has any information on the status of project Rassilon, Neo4j's side project which focuses on improving horizontal scalability of Neo4j?

最早于2013年1月在此处宣布.

It was first announced in January 2013 here.

我特别想了解何时消除图形大小限制以及何时可以使用跨集群分片的更多信息.

I'm particularly interested in knowing more about when the graph size limitation will be removed and when sharding across clusters will become available.

推荐答案

节点&关系限制在2.1(即将发布的下一个发布版本2.0)中消失了.

The node & relationship limits are going away in 2.1, which is the next release post 2.0 (which now has a release candidate).

Rassilon肯定仍然存在.就是说，这项工作并不优先于诸如2.0中大量新功能之类的事情.原因是，使用以下概述的各种架构功能(带有一些实时示例)，Neo4j具备了极好的扩展能力:

Rassilon is definitely still in the mix. That said, that work is not taking precedence over things like the significant bundle of new features that are in 2.0. The reason is that Neo4j as it stands today is extremely capable of scaling, using the variety of architecture features outlined below (with some live examples):

www.neotechnology.com/neo4j-scales-for-the-enterprise/

当前架构中有很多聪明之处，可让图表执行&无需分片即可很好地扩展.因为一旦开始分片，就注定要遍历网络，这是一件坏事(对于延迟，查询可预测性等).因此，尽管有一些非常大的图，主要是出于写吞吐量的原因，必须权衡(通过分片)超大规模的性能，令人高兴的是，大多数图形不需要这种折衷.仅在1％的情况下才需要分片，这意味着几乎每个人都可以吃蛋糕.当前，生产客户中有Neo4j集群，图中有1B +个人，支持具有数千万用户的Web应用程序.这些使用相对较小(但非常快，非常有效)的群集.为了让您大致了解一下各种性价比，我们已经让用户告诉我们，一个Neo4j实例可以与10个Oracle实例一样工作，但速度更快.

There's lots of cleverness in the current architecture that allows the graph to perform & scale well without sharding. Because once you start sharding, you are destined to traverse over the network, which is a bad thing (for latency, query predictability etc.) So while there are some extremely large graphs that, largely for write throughput reasons, must trade off performance for uber scale (by sharding), the happy thing is that most graphs don't require this compromise. Sharding is required only in the 1% case, which means that nearly everyone can have their cake and eat it too. There are currently Neo4j clusters in production customers with 1B+ individuals in their graph, backing web applications with tens of millions of users. These use comparatively small (but very fast, very efficient) clusters. To give you some idea of the kinds of price-performance we regularly see: we've had users tell us that a single Neo4j instance could the same work as 10 Oracle instances, only faster.

一个经过良好调整的Neo4j集群每秒可以支持多达10K的事务性写入，并且每秒可以支持任意数量的读取.当实例被弹性插入时，读取吞吐量呈线性增长.缓存分片是一种设计模式，可确保您不必将整个图形保留在内存中.

A well-tuned Neo4j cluster can support upwards of 10K transactional writes per second, and an arbitrarily high number of reads per second. Read throughput scales linearly as instances are elastically plugged in. Cache sharding is a design pattern that ensures that you don't have to keep the entire graph in memory.

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