[bug] Indexing silently fails with Elasticsearch #549
Labels
No labels
approved, awaiting change
bug
configuration
documentation
duplicate
enhancement
extremely low priority
feature request
Fix it yourself
help wanted
invalid
mastodon_api
needs docs
needs tests
not a bug
planned
pleroma_api
privacy
question
static_fe
triage
wontfix
No milestone
No project
No assignees
1 participant
Notifications
Due date
No due date set.
Dependencies
No dependencies set.
Reference: AkkomaGang/akkoma#549
Loading…
Reference in a new issue
No description provided.
Delete branch "%!s()"
Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?
Your setup
Docker
Extra details
Slightly modified Docker setup via Podman
Version
3.9.3-28-g9d7c877d
PostgreSQL version
Latest docker container
What were you trying to do?
I am trying to get search working with Elasticsearch. I got a single node setup up and running that I am using with Forgejo successfully and though it might be nice to add Akkoma to the same one.
This is to avoid running an extra Meilisearch, which seems to work fine, but uses a lot of resources without actually speeding up the search much.
What did you expect to happen?
Following the official documentation and previous guidance when I tried the same with Zincsearch (similar error actually) I expected there to be some on screen feedback of the indexing failing or so, but it just takes a long time without any result and seems to time out or only work in RAM and not actually write to the Elasticsearch instance.
What actually happened?
When running
mix pleroma.search import activities
(withMIX_ENV=prod
set) it just gives a blinking cursor for a long time (>30 minutes) and the RAM use of the Akkoma container shoots up, but nothing seems to happen Elasticsearch side and after a while it times out and RAM use returns to normal.Logs
Severity
I cannot use it as easily as I'd like
Have you searched for this issue?
I am somewhat suspecting that the Elasticsearch library might be actively checking for alternative implementations and preventing the use of them :(
At least for a different Python project I am trying with Opensearch that has more verbose out-put that is the case...