How to Work with Transactions with Gremlin Python
I`m trying to implement transactions but I have two scenarios.
I start a transaction but when I use iterate on every add_v it saves on my gremlin_server before the commit. The second situation is if if take out the .iterate() and run a commit() it doenst save on gremlin-server. What am I doing wrong?...
Solution:
If you're looking to optimize for write throughput on Neptune, you want to consider the following:
- For each write requests, attempt to batch 100-200 "object" into a single write request/query. An "object" would be any combination of a vertex, edge, or subsequent vertex/edge properties (vertex with 4 properties == 5 "objects").
- Use parallel write requests. If using Python, consider using
multiprocessing to create separate processes. They can share a connection pool to Neptune if you so choose. The number of parallel processes should equal the number of query execution threads available on your Neptune writer instance (which is equal to 2x the number of vCPUs on whatever size instance you're using).
If you follow those guidelines, you should get similar performance to what you would see with Neptune's bulk loader. Note that conditional writes will have overhead. If using mergeV(), you're unlikely to see the same write throughput as Neptune's bulk loader as the bulk loader is not doing conditional writes....
Possibilities to improve performance on query?
I have a Python application with FastAPI that performs 3 actions when the endpoint is called: querying the structure that returns vertices and edges (21 itens in total), removing edges and registering/updating vertices and edges. For the query process to return the values, it takes a long time to process and the average is 1.4 seconds. Before, I separated this query that I will leave attached and sent it in threads, but it still took a little longer. Im also using the cluster reader url and both...
Neptune Cluster Balancing Configuration
I'm trying to reach 40 rps in the registration flow, currently I'm reaching 20 rps. I have 6 instances of a python application in fastapi and I notice that each interaction takes around 200-400ms to communicate with neptune, for query flows I notice that there is a bottleneck where some of these queries take around 200ms-1s. about the cluster and the application, both are in the same region and with the same vpc. When analyzing the cluster I notice that some instances are having more CPU consump...
Solution:
What are you using to send queries to Neptune? Are you using the gremlin-python client and connecting via websockets? If so, each websocket connection is going to act like a "sticky session". It will connect to the same instance for the life of the connection.
The reader endpoint is a DNS endpoint that is configured to resolve to a different read replica approximately every 5 seconds. So depending on when you establish your websocket connections or if you're just sending http requests, those could all go to the same instance if sent in quick succession.
Customers have solved this in a number of ways. Some will create load balancers in front of Neptune read replicas that can more precisely "load balance" requests across the instances....
