Neo4j 的水平可扩展性项目 Rassilon 处于什么状态? [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了解有关 Neo4j 的侧项目 Rassilon 的状态的信息，该项目专注于提高 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?

它于 2013 年 1 月首次发布此处.

It was first announced in January 2013 here.

我特别想知道更多关于何时取消图形大小限制以及何时可以使用跨集群分片.

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 &2.1 中的关系限制将消失，这是 2.0 后的下一个版本(现在有一个候选版本).

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 肯定还在组合中.也就是说，这项工作并没有优先于诸如 2.0 中的大量新功能之类的事情.原因是目前的 Neo4j 具有极强的扩展能力，使用下面概述的各种架构功能(带有一些现场示例):

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，可以让图执行&无需分片即可很好地扩展.因为一旦开始分片，你就注定要遍历网络，这是一件坏事(对于延迟、查询可预测性等)所以虽然有一些非常大的图，主要是出于写入吞吐量的原因，必须 权衡超级规模的性能(通过分片)，令人高兴的是大多数图不需要这种妥协.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.目前在生产客户中有 Neo4j 集群，他们的图中有 1B+ 个人，支持拥有数千万用户的 Web 应用程序.这些使用相对较小(但非常快速、非常有效)的集群.为了让您了解我们经常看到的各种性价比:我们有用户告诉我们，单个 Neo4j 实例可以与 10 个 Oracle 实例一样工作，只是速度更快.

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.

一个经过良好调优的 Neo4j 集群可以支持每秒 10K 以上的事务写入，以及任意多的每秒读取次数.读取吞吐量随着实例的弹性插入而线性扩展.缓存分片是一种设计模式，可确保您不必将整个图保留在内存中.

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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