3 ms·

Hmm, OK, I guess I'm kind of lost then. In my mind, the system I described never loses anything. I'm OK nipping this convo because I kind of feel like we're goi

Hmm, OK, I guess I'm kind of lost then. In my mind, the system I described never loses anything. I'm OK nipping this convo because I kind of feel like we're going in circles, but if you do want to continue I'm not sure how because I don't quite understand where we're misunderstanding each other. Maybe show an explicit example of the kind of data loss you're talking about? My best guess is that I've described my design poorly and I'm leaving something critical out. I think the only way for me to figure out what I've left out is to hear more of your objection. :-)

Karrot_Kream 9y ago
Not sure if I can respond properly on mobile but I'll do my best. 1. There are differences between system conflicts and user conflicts. Let's say I'm collaborating on a Google doc. Both my collaborator and I start writing in the same part of the document. If the concurrent system is designed "poorly" (for example, it has last write wins semantics), then only one of our writing appears. You can store this history in the system and show that your changes were overwritten by their changes, but this can be frustrating if you are both collaborating on the end of the document. 2. Commutative operations give better guarantees. Let's take for instance an append only DAG. We restrict this DAG to having 2 operations: creating a vertex (and associated edges) between 2 existing vertices and creating an edge between 2 existing vertices. In this case, even if both my collaborator and I add a vertex between 2 existing vertices, the system will converge on a DAG where both vertices are added. You can follow the same argument with adding edges. This DAG is an example of a CRDT. It has a limited set of operations (addEdge and addBetween) which allow convergent semantics through concurrent operations Happy to chat more about this stuff and hope my mobile response makes sense heh.
- burntsushi 9y ago
  So w.r.t. to (1), yeah, I totally get that. And I agree that is a hard problem to solve in the context of document editing (or more precisely, anything that contains a sequence). But for a graph, the logic is considerably simpler because a graph is just two sets. So if the system "loses" work that the client has done, it's only when some other client has deleted or changed something. So if two clients are editing the same graph and one drops a vertex and the other creates an edge that connects to that vertex, what is the right outcome in that circumstance? It seems to me like the edge gets deleted, and that this is a natural user conflict, no? (Regardless of how you order the operations in this case, the edge gets dropped.) W.r.t. to (2), yeah, sure, but if clients need to be able to remove things then you lose commutativity and you end up missing the requirements of the system itself. Or is there some other component of a CRDT system that's supposed to handle this? (My big picture takeaway from the OP paper was that it was specifically trying to handle the non-commutative operations.)
  - Karrot_Kream 9y ago
    Yup! Removes are where a lot of these things get tricky. The typical strategy is as you say, removes take precedence over adds, so if one client adds vertices/edges onto a vertex that gets removed by another client, when the DAGs converge, the remove gets precedence and "drops" all edges/vertices attached. It seems like we're basically saying the same thing. Removes are also tricky because if you're just transmitting the remove operation itself, you have to ensure that updates appear to the client in order, or else removes and adds could conflict, causing inconsistent state.
    - burntsushi 9y ago
      Yeah, in practice, each client maintains a persistent data structure, where each "mutation" is the application of a single operation. If a new operation comes in that occurs before other operations that have already been applied to the persistent data structure, then the client rewinds the structure to its state just before the new out-of-order operation, applies that operation, and then applies the rest of the operations that it already has. (I think of this as very similar to a `git rebase`.) But yeah, this might not work at all for sequences. And of course, there are other issues with respect to the memory requirements of the persistent data structure in the client. Some sort of compaction is probably necessary.

Karrot_Kream 9y ago

Not sure if I can respond properly on mobile but I'll do my best. 1. There are differences between system conflicts and user conflicts. Let's say I'm collaborating on a Google doc. Both my collaborator and I start writing in the same part of the document. If the concurrent system is designed "poorly" (for example, it has last write wins semantics), then only one of our writing appears. You can store this history in the system and show that your changes were overwritten by their changes, but this can be frustrating if you are both collaborating on the end of the document. 2. Commutative operations give better guarantees. Let's take for instance an append only DAG. We restrict this DAG to having 2 operations: creating a vertex (and associated edges) between 2 existing vertices and creating an edge between 2 existing vertices. In this case, even if both my collaborator and I add a vertex between 2 existing vertices, the system will converge on a DAG where both vertices are added. You can follow the same argument with adding edges. This DAG is an example of a CRDT. It has a limited set of operations (addEdge and addBetween) which allow convergent semantics through concurrent operations Happy to chat more about this stuff and hope my mobile response makes sense heh.

burntsushi 9y ago
So w.r.t. to (1), yeah, I totally get that. And I agree that is a hard problem to solve in the context of document editing (or more precisely, anything that contains a sequence). But for a graph, the logic is considerably simpler because a graph is just two sets. So if the system "loses" work that the client has done, it's only when some other client has deleted or changed something. So if two clients are editing the same graph and one drops a vertex and the other creates an edge that connects to that vertex, what is the right outcome in that circumstance? It seems to me like the edge gets deleted, and that this is a natural user conflict, no? (Regardless of how you order the operations in this case, the edge gets dropped.) W.r.t. to (2), yeah, sure, but if clients need to be able to remove things then you lose commutativity and you end up missing the requirements of the system itself. Or is there some other component of a CRDT system that's supposed to handle this? (My big picture takeaway from the OP paper was that it was specifically trying to handle the non-commutative operations.)
- Karrot_Kream 9y ago
  Yup! Removes are where a lot of these things get tricky. The typical strategy is as you say, removes take precedence over adds, so if one client adds vertices/edges onto a vertex that gets removed by another client, when the DAGs converge, the remove gets precedence and "drops" all edges/vertices attached. It seems like we're basically saying the same thing. Removes are also tricky because if you're just transmitting the remove operation itself, you have to ensure that updates appear to the client in order, or else removes and adds could conflict, causing inconsistent state.
  - burntsushi 9y ago
    Yeah, in practice, each client maintains a persistent data structure, where each "mutation" is the application of a single operation. If a new operation comes in that occurs before other operations that have already been applied to the persistent data structure, then the client rewinds the structure to its state just before the new out-of-order operation, applies that operation, and then applies the rest of the operations that it already has. (I think of this as very similar to a `git rebase`.) But yeah, this might not work at all for sequences. And of course, there are other issues with respect to the memory requirements of the persistent data structure in the client. Some sort of compaction is probably necessary.