Signed-off-by: Alan Guo <aguo@anyscale.com>
## Why are these changes needed?
Reduces memory footprint of the dashboard.
Also adds some cleanup to the errors data.
Also cleans up actor cache by removing dead actors from the cache.
Dashboard UI no longer allows you to see logs for all workers in a node. You must click into each worker's logs individually.
<img width="1739" alt="Screen Shot 2022-07-20 at 9 13 00 PM" src="https://user-images.githubusercontent.com/711935/180128633-1633c187-39c9-493e-b694-009fbb27f73b.png">
## Related issue number
fixes#23680fixes#22027fixes#24272
Enable checking of the ray core module, excluding serve, workflows, and tune, in ./ci/lint/check_api_annotations.py. This required moving many files to ray._private and associated fixes.
This PR implements ray list tasks and ray list objects APIs.
NOTE: You can ignore the merge conflict for now. It is because the first PR was reverted. There's a fix PR open now.
This is a rebase version of #11592. As task spec info is only needed when gcs create or start an actor, so we can remove it from actor table and save the serialization time and memory/network cost when gcs clients get actor infos from gcs.
As internal repository varies very much from the community. This pr just add some manual check with simple cherry pick. Welcome to comment first and at the meantime I'll see if there's any test case failed or some points were missed.
GCS pubsub has been the default for awhile. There is little chance that we would need to revert back to Redis pubsub in future. This is the step in removing Redis pubsub, by first removing the `enable_gcs_pubsub()` feature guard.
As we are turning redisless ray by default, dashboard doesn't need to talk with redis anymore. Instead it should talk with gcs and gcs can talk with redis.
This is the second part of https://docs.google.com/document/d/12qP3x5uaqZSKS-A_kK0ylPOp0E02_l-deAbmm8YtdFw/edit#. After this PR, dashboard agents will fully work with minimal ray installation.
Note that this PR requires to introduce "aioredis", "frozenlist", and "aiosignal" to the minimal installation. These dependencies are very small (or will be removed soon), and including them to minimal makes thing very easy. Please see the below for the reasoning.
Currently, GCS KV client only has blocking API. Calling them from dashboard event loop can block other operations for many seconds, leading to failures such as taking too long (> 2min) to submit a job and making nightly tests fail (#21699). This PR offloads the blocking work to a separate thread. Implementing async GCS KV API will be done in the future.
This PR contains most of the fixes @iycheng made in #21232, to make tests pass with GCS bootstrapping by supporting both Redis and GCS address as the bootstrap address. The main change is to use address_info["address"] to obtain the bootstrap address to pass to ray.init(), instead of using address_info["redis_address"]. In a subsequent PR, address_info["address"] will return the Redis or GCS address depending on whether using GCS to bootstrap.
This is part of gcs ha project. This PR try to bootstrap dashboard with gcs address instead of redis.
Co-authored-by: mwtian <81660174+mwtian@users.noreply.github.com>
