You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I am using a machine with 512GB of RAM and am running out of memory when loading a 1BN node / 2BN edge graph. Each node has 3 properties and each edge has 4 properties. Is this an expected amount of memory consumption for a graph of this scale. Is there anything I can be doing to minimize the amount of memory being consumed during the load?
The text was updated successfully, but these errors were encountered:
There's no simple rule for expected memory consumption; factors like the number of labels and relationship types can change the value greatly. I would not be surprised if your graph once loaded consumes at least a few hundred GBs, however.
By default the bulk loader will only buffer 1GB of changes at a time, which is negligible compared to the amount used here. It also maintains a dictionary of node IDs for resolving endpoints, which can get rather large.
To determine whether this is a bulk loader issue or just too large of a graph for your machine, I would try running the process again while monitoring memory usage with htop or similar. If the majority of memory is used by redis-server, then there is nothing to do but try to modify the inputs or provision a larger machine. If the bulk loader process is consuming a large quantity of memory, there may be code changes we can develop to ameliorate the cost of loading.
I am using a machine with 512GB of RAM and am running out of memory when loading a 1BN node / 2BN edge graph. Each node has 3 properties and each edge has 4 properties. Is this an expected amount of memory consumption for a graph of this scale. Is there anything I can be doing to minimize the amount of memory being consumed during the load?
The text was updated successfully, but these errors were encountered: