Graphs in RavenDBQuery results

time to read 2 min | 381 words

imageWe run into an interesting design issue when building graph queries for RavenDB. The problem statement is fairly easy. Should a document be allowed to be bound to multiple aliases in the query results, or just one? However, without context, the problem statement in not meaningful, so let’s talk about what the actual problem is. Consider the graph on the right. We have three documents, Arava, Oscar and Phoebe and the following edges:

  • Arava Likes Oscar
  • Phoebe Likes Oscar

We now run the following query:


This query asks for a a dog that likes another dog that is liked by a dog. Another way to express the same sentiment (indeed, how RavenDB actually considers this type of query) is to write it as follows:


When processing the and expression, we require that documents that match to the same alias will be the same. Given the graph that we execute this on, what would you consider the right result?

Right now, we have the first option, in which a document can be match to multiple different alias in the same result, which would lead to the following results:


Note that in this case, the first and last entries match A and C to the same document.

The second option is to ensure that a document can only be bound to a single alias in the result, which would remove the duplicate results above and give us only:


Note that in either case, position matters, and the minimum number of results this query will generate is two, because we need to consider different starting points for the pattern match on the graph.

What do you think should we do in such a case? Are there reasons to want this behavior or that and should it be something that the user select?

More posts in "Graphs in RavenDB" series:

  1. (08 Nov 2018) Real world use cases
  2. (01 Nov 2018) Recursive queries
  3. (31 Oct 2018) Inconsistency abhorrence
  4. (29 Oct 2018) Selecting the syntax
  5. (26 Oct 2018) What’s the role of the middle man?
  6. (25 Oct 2018) I didn’t mean to build this feature!
  7. (22 Oct 2018) Query results
  8. (21 Sep 2018) Graph modeling vs. document modeling
  9. (20 Sep 2018) Pre-processing the queries
  10. (19 Sep 2018) The query language
  11. (18 Sep 2018) The overall design