Gremlin查询是否有效取决于上下文 [英] Gremlin query works or not depending on the context

问题描述

在查询中(通过斯蒂芬·马莱特(Stephen Mallette)在

In a query (by the way written by stephen mallette in this question) the problem is that works in gremlify, but when I paste it in my project gives an incorrect output.

因此，我打开gremlify编写了一个数据创建查询，然后将其粘贴到gremlin控制台中，以便可以在那里进行测试，并且我发现如果在查询的数据创建部分之后执行了该代码，并且在gremlify中不起作用，据我了解，它应该可以工作.

So I opened gremlify to write a data creation query to then paste it in the gremlin console so I can test it there, and I noticed it doesn't work in gremlify if it's executed after the data creation part of the query and it should work as far as I understand.

查询是这样的:

g.V().as('a').
  repeat(both().simplePath()).
    times(2).
  where(both().as('a')).
  path().
  map(unfold().limit(3).order().by(id).dedup().fold())
  dedup().
  group('m').
    by(limit(local,2)).
  group('m').
    by(tail(local,2)).
  group('m').
    by(union(limit(local,1),tail(local,1)).fold()).     
  cap('m').
  unfold().
  map(select(values).unfold().unfold().order().by(id).dedup().fold()).
  dedup().
  map(unfold().values('name').fold())

在这里有效，输出正确: https://gremlify.com/psiygozr559

Here it works, output is correct: https://gremlify.com/psiygozr559

此处给出了错误的输出: https://gremlify.com/mqw6ut0y1z (相同的图形，但通过查询创建)

Here it gives an incorrect output: https://gremlify.com/mqw6ut0y1z (same graph but created with a query)

这里根本不提供任何输出: https://gremlify.com/fzgmzdq1omq (与以前相同，但第1行有所更改)

Here it does not give any output at all: https://gremlify.com/fzgmzdq1omq (same than before with a change in line 1)

在我的项目中也给出了不正确的输出，并且在执行查询之前，我没有执行任何奇怪的事情，就像上面的gremlify项目中一样.

In my project also gives an incorrect output and I'm not executing anything weird before the query like in the gremlify projects above.

还有另一个查询，它是我自己编写的，效率较低，但在所有相同情况下和我的项目中均能完美运行，请参阅:

There is another query that does the same, I wrote it myself, is less efficient but works perfectly in all the same situations and in my project, see:

https://gremlify.com/zihygx0w8e

https://gremlify.com/xsc6q8dranj

在我的项目中，我使用Node.js在未更改默认配置的情况下以本地方式连接到gremlin服务器.

In my project I'm connecting to gremlin server locally with with the default configuration untouched, using Node.js.

这里发生了我不理解的事情.

Something is happening here that I don't understand.

推荐答案

通过扩展遍历，您扩展了Path.将addV('j')放在遍历的前面会添加一些我的原始算法未考虑的内容:

By extending the traversal you've extended the Path. Placing addV('j') at the front of the traversal adds something my original algorithm did not take into account:

gremlin> g.addV("j").sideEffect(V().drop()).sideEffect(
......1>     addV("user").property("name", "luana").as("luana")
......2>     .addV("user").property("name", "luisa").as("luisa")
......3>     .addV("user").property("name", "sabrina").as("sabrina")
......4>     .addV("user").property("name", "marcello").as("marcello")
......5>     .addV("user").property("name", "mario").as("mario")
......6>     .addV("user").property("name", "lidia").as("lidia")
......7>     
......7>     .addE("friend").from("luana").to("luisa")
......8>     .addE("friend").from("luana").to("sabrina")
......9>     .addE("friend").from("luana").to("marcello")
.....10>     .addE("friend").from("luana").to("mario")
.....11>     .addE("friend").from("luana").to("lidia")
.....12>     
.....12>     .addE("friend").from("sabrina").to("luisa")
.....13>     .addE("friend").from("sabrina").to("marcello")
.....14>     .addE("friend").from("sabrina").to("mario")
.....15>     
.....15>     .addE("friend").from("mario").to("luisa")
.....16>     .addE("friend").from("mario").to("marcello")
.....17>     ).V().as('a').
.....18>   repeat(both().simplePath()).
.....19>     times(2).
.....20>   where(both().as('a')).
.....21>   path().by(label)
==>[j,user,user,user]
==>[j,user,user,user]
==>[j,user,user,user]
==>[j,user,user,user]
...
==>[j,user,user,user]

您可以通过以下方式解决此问题:命名您关心的路径，或者限制或过滤掉该初始路径元素:

You can account for that by naming the path you care about or otherwise limiting or filtering away that initial path element:

gremlin> g.addV("j").sideEffect(V().drop()).sideEffect(
......1>     addV("user").property("name", "luana").as("luana")
......2>     .addV("user").property("name", "luisa").as("luisa")
......3>     .addV("user").property("name", "sabrina").as("sabrina")
......4>     .addV("user").property("name", "marcello").as("marcello")
......5>     .addV("user").property("name", "mario").as("mario")
......6>     .addV("user").property("name", "lidia").as("lidia")
......7>     
......7>     .addE("friend").from("luana").to("luisa")
......8>     .addE("friend").from("luana").to("sabrina")
......9>     .addE("friend").from("luana").to("marcello")
.....10>     .addE("friend").from("luana").to("mario")
.....11>     .addE("friend").from("luana").to("lidia")
.....12>     
.....12>     .addE("friend").from("sabrina").to("luisa")
.....13>     .addE("friend").from("sabrina").to("marcello")
.....14>     .addE("friend").from("sabrina").to("mario")
.....15>     
.....15>     .addE("friend").from("mario").to("luisa")
.....16>     .addE("friend").from("mario").to("marcello")
.....17>     ).V().as('a').
.....18>   repeat(both().simplePath()).
.....19>     times(2).
.....20>   where(both().as('a')).
.....21>   path().from('a').
.....22>   map(unfold().limit(3).order().by(id).dedup().fold()).
.....23>   dedup().
.....24>   group('m').
.....25>     by(limit(local,2)).
.....26>   group('m').
.....27>     by(tail(local,2)).
.....28>   group('m').
.....29>     by(union(limit(local,1),tail(local,1)).fold()).     
.....30>   cap('m').
.....31>   unfold().
.....32>   map(select(values).unfold().unfold().order().by(id).dedup().fold()).
.....33>   dedup().
.....34>   map(unfold().values('name').fold())
==>[luana,luisa,sabrina,mario]
==>[luana,sabrina,marcello,mario]
==>[luana,luisa,sabrina,marcello,mario]

请注意上面的第21行，我们仅需添加path().from('a')，即在步骤标签"a"处开始路径，然后该查询将再次开始工作.

Note line 21 above where we simply add path().from('a') which says, start the path at the step label "a", and then the query starts working again.

关于另一个不使用sideEffect()来添加示例图形数据的示例，请注意path()遵循repeat()时的输出:

Regarding your other example that doesn't use sideEffect() to add the sample graph data, note the output of path() when it follows repeat():

gremlin> g.addV("j").sideEffect(V().drop()).
......1>   addV("user").property("name", "luana").as("luana").
......2>   addV("user").property("name", "luisa").as("luisa").
......3>   addV("user").property("name", "sabrina").as("sabrina").
......4>   addV("user").property("name", "marcello").as("marcello").
......5>   addV("user").property("name", "mario").as("mario").
......6>   addV("user").property("name", "lidia").as("lidia").
......7>     
......7>   addE("friend").from("luana").to("luisa").
......8>   addE("friend").from("luana").to("sabrina").
......9>   addE("friend").from("luana").to("marcello").
.....10>   addE("friend").from("luana").to("mario").
.....11>   addE("friend").from("luana").to("lidia").
.....12>     
.....12>   addE("friend").from("sabrina").to("luisa").
.....13>   addE("friend").from("sabrina").to("marcello").
.....14>   addE("friend").from("sabrina").to("mario").
.....15>     
.....15>   addE("friend").from("mario").to("luisa").
.....16>   addE("friend").from("mario").to("marcello").
.....17>   V().as('a').both().path()
==>[v[712],v[713],v[715],v[717],v[719],v[721],v[723],e[725][713-friend->715],e[726][713-friend->717],e[727][713-friend->719],e[728][713-friend->721],e[729][713-friend->723],e[730][717-friend->715],e[731][717-friend->719],e[732][717-friend->721],e[733][721-friend->715],e[734][721-friend->719],v[721],v[715]]
==>[v[712],v[713],v[715],v[717],v[719],v[721],v[723],e[725][713-friend->715],e[726][713-friend->717],e[727][713-friend->719],e[728][713-friend->721],e[729][713-friend->723],e[730][717-friend->715],e[731][717-friend->719],e[732][717-friend->721],e[733][721-friend->715],e[734][721-friend->719],v[721],v[719]]
...
==>[v[712],v[713],v[715],v[717],v[719],v[721],v[723],e[725][713-friend->715],e[726][713-friend->717],e[727][713-friend->719],e[728][713-friend->721],e[729][713-friend->723],e[730][717-friend->715],e[731][717-friend->719],e[732][717-friend->721],e[733][721-friend->715],e[734][721-friend->719],v[719],v[721]]

在sideEffect()之外添加顶点/边时，它们将包含在该输出中.因此，当您尝试遍历V().as('a')时，simplePath()立即将它们过滤掉！

As you've added vertices/edges outside of the sideEffect() they are included in that output. Therefore, simplePath() immediately filters them away as soon as you try to traverse V().as('a')!

==>[v[712],v[713],v[715],v[717],v[719],v[721],v[723],e[725][713-friend->715],e[726][713-friend->717],e[727][713-friend->719],e[728][713-friend->721],e[729][713-friend->723],e[730][717-friend->715],e[731][717-friend->719],e[732][717-friend->721],e[733][721-friend->715],e[734][721-friend->719],v[721],v[715]]

查看v[721]出现两次的方式-一次用于addV()，一次用于V(). simplePath()看到您遍历了该顶点并返回了该顶点.

See how v[721] appears twice - once for addV() and once for V(). simplePath() sees that you traversed that vertex and returned to it.

我调试此问题的方法(因为尚未立即弄清答案)是首先profile()两次遍历并比较相似部分的计数.我注意到它们开始有所不同的地方，这使我对问题开始的地方一目了然.从那里开始，我开始并排执行查询，直到注意到Path周围的输出差异.您可以在此处上学习一些有关如何区分和调试Gremlin查询的知识.

My approach to debugging this (as the answer was not immediately clear) was to first profile() the two traversals and compare the counts of the like sections. I noted where they started to differ which put me in the viscinity of where the problem started. From there I started executing the query up to those steps side-by-side until I noted the difference in output around the Path. You can learn a bit on how to pick apart and debug Gremlin queries here.

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