For use in production in case on-demand download turns out to be
problematic during tenant_attach, or when we eventually introduce layer
eviction.
Co-authored-by: Dmitry Rodionov <dmitry@neon.tech>
Motivation
==========
Layer Eviction Needs Context
----------------------------
Before we start implementing layer eviction, we need to collect some
access statistics per layer file or maybe even page.
Part of these statistics should be the initiator of a page read request
to answer the question of whether it was page_service vs. one of the
background loops, and if the latter, which of them?
Further, it would be nice to learn more about what activity in the pageserver
initiated an on-demand download of a layer file.
We will use this information to test out layer eviction policies.
Read more about the current plan for layer eviction here:
https://github.com/neondatabase/neon/issues/2476#issuecomment-1370822104
task_mgr problems + cancellation + tenant/timeline lifecycle
------------------------------------------------------------
Apart from layer eviction, we have long-standing problems with task_mgr,
task cancellation, and various races around tenant / timeline lifecycle
transitions.
One approach to solve these is to abandon task_mgr in favor of a
mechanism similar to Golang's context.Context, albeit extended to
support waiting for completion, and specialized to the needs in the
pageserver.
Heikki solves all of the above at once in PR
https://github.com/neondatabase/neon/pull/3228 , which is not yet
merged at the time of writing.
What Is This Patch About
========================
This patch addresses the immediate needs of layer eviction by
introducing a `RequestContext` structure that is plumbed through the
pageserver - all the way from the various entrypoints (page_service,
management API, tenant background loops) down to
Timeline::{get,get_reconstruct_data}.
The struct carries a description of the kind of activity that initiated
the call. We re-use task_mgr::TaskKind for this.
Also, it carries the desired on-demand download behavior of the entrypoint.
Timeline::get_reconstruct_data can then log the TaskKind that initiated
the on-demand download.
I developed this patch by git-checking-out Heikki's big RequestContext
PR https://github.com/neondatabase/neon/pull/3228 , then deleting all
the functionality that we do not need to address the needs for layer
eviction.
After that, I added a few things on top:
1. The concept of attached_child and detached_child in preparation for
cancellation signalling through RequestContext, which will be added in
a future patch.
2. A kill switch to turn DownloadBehavior::Error into a warning.
3. Renamed WalReceiverConnection to WalReceiverConnectionPoller and
added an additional TaskKind WalReceiverConnectionHandler.These were
necessary to create proper detached_child-type RequestContexts for the
various tasks that walreceiver starts.
How To Review This Patch
========================
Start your review with the module-level comment in context.rs.
It explains the idea of RequestContext, what parts of it are implemented
in this patch, and the future plans for RequestContext.
Then review the various `task_mgr::spawn` call sites. At each of them,
we should be creating a new detached_child RequestContext.
Then review the (few) RequestContext::attached_child call sites and
ensure that the spawned tasks do not outlive the task that spawns them.
If they do, these call sites should use detached_child() instead.
Then review the todo_child() call sites and judge whether it's worth the
trouble of plumbing through a parent context from the caller(s).
Lastly, go through the bulk of mechanical changes that simply forwards
the &ctx.
Before this patch, when `initialize_with_lock` was called via
`timeline_init_and_sync`, we would transition the timeline like so:
load_local_timeline/load_remote_timeline:
timeline_init_and_sync
Timeline::new
() => Loading
initialize_with_lock:
set_state(Active)
Loading => Active
timeline.activate()
Active => Active
this makes debugging problematic cases in the future easier, as we can
just request the model inputs, use them locally to reproduce the issue
with the model.
I noticed that `compute_ctl` updates all roles on each start, search for
rows like
> - web_access:[FILTERED] -> update
in the compute startup log.
It happens since we had an adhoc hack for md5 hashes comparison, which
doesn't work with scram hashes stored in the `pg_authid`. It doesn't
really hurt, as nothing changes, but we just run >= 2 extra queries on
each start, so fix it.
The TimelineState::Suspsended was dubious to begin with. I suppose
that the intention was that timelines could transition back and
forth between Active and Suspended states.
But practically, the code before this patch never did that.
The transitions were:
() ==Timeline::new==> Suspended ==*==> {Active,Broken,Stopping}
One exception: Tenant::set_stopping() could transition timelines like
so:
!Broken ==Tenant::set_stopping()==> Suspended
But Tenant itself cannot transition from stopping state to any other
state.
Thus, this patch removes TimelineState::Suspended and introduces a new
state Loading. The aforementioned transitions change as follows:
- () ==Timeline::new==> Suspended ==*==> {Active,Broken,Stopping}
+ () ==Timeline::new==> Loading ==*==> {Active,Broken,Stopping}
- !Broken ==Tenant::set_stopping()==> Suspended
+ !Broken ==Tenant::set_stopping()==> Stopping
Walreceiver's connection manager loop watches TimelineState to decide
whether it should retry connecting, or exit.
This patch changes the loop to exit when it observes the transition
into Stopping state.
Walreceiver isn't supposed to be started until the timeline transitions
into Active state. So, this patch also adds some warn!() messages
in case this happens anyways.
Small changes, but hopefully this will help with the panic detected in
staging, for which we cannot get the debugging information right now
(end-of-branch before branch-point).
Before only the timelines which have passed the `gc_horizon` were
processed which failed with orphans at the tree_sort phase. Example
input in added `test_branched_empty_timeline_size` test case.
The PR changes iteration to happen through all timelines, and in
addition to that, any learned branch points will be calculated as they
would had been in the original implementation if the ancestor branch had
been over the `gc_horizon`.
This also changes how tenants where all timelines are below `gc_horizon`
are handled. Previously tenant_size 0 was returned, but now they will
have approximately `initdb_lsn` worth of tenant_size.
The PR also adds several new tenant size tests that describe various corner
cases of branching structure and `gc_horizon` setting.
They are currently disabled to not consume time during CI.
Co-authored-by: Joonas Koivunen <joonas@neon.tech>
Co-authored-by: Anastasia Lubennikova <anastasia@neon.tech>
Previously, we were trying to re-assign owned objects of the already
deleted role. This were causing a crash loop in the case when compute
was restarted with a spec that includes delta operation for role
deletion. To avoid such cases, check that role is still present before
calling `reassign_owned_objects`.
Resolvesneondatabase/cloud#3553
This reverts commit 826e89b9ce.
The problem with that commit was that it deletes the TempDir while
there are still EphemeralFile instances open.
At first I thought this could be fixed by simply adding
Handle::current().block_on(task_mgr::shutdown(None, Some(tenant_id), None))
to TenantHarness::drop, but it turned out to be insufficient.
So, reverting the commit until we find a proper solution.
refs https://github.com/neondatabase/neon/issues/3385
Refactors Compute::prepare_and_run. It's split into subroutines
differently, to make it easier to attach tracing spans to the
different stages. The high-level logic for waiting for Postgres to
exit is moved to the caller.
Replace 'env_logger' with 'tracing', and add `#instrument` directives
to different stages fo the startup process. This is a fairly
mechanical change, except for the changes in 'spec.rs'. 'spec.rs'
contained some complicated formatting, where parts of log messages
were printed directly to stdout with `print`s. That was a bit messed
up because the log normally goes to stderr, but those lines were
printed to stdout. In our docker images, stderr and stdout both go to
the same place so you wouldn't notice, but I don't think it was
intentional.
This changes the log format to the default
'tracing_subscriber::format' format. It's different from the Postgres
log format, however, and because both compute_tools and Postgres print
to the same log, it's now a mix of two different formats. I'm not
sure how the Grafana log parsing pipeline can handle that. If it's a
problem, we can build custom formatter to change the compute_tools log
format to be the same as Postgres's, like it was before this commit,
or we can change the Postgres log format to match tracing_formatter's,
or we can start printing compute_tool's log output to a different
destination than Postgres
Before this patch, we would start all layer downloads simultaneously.
There is at most one download_all_remote_layers task per timeline.
Hence, the specified limit is per timeline.
There is still no global concurrency limit for layer downloads.
We'll have to revisit that at some point and also prioritize on-demand
initiated downloads over download_all_remote_layers downloads.
But that's for another day.
