"cargo clippy" started to complain about these, after running "cargo
update". Not sure why it didn't complain before, but seems reasonable to
fix these. (The "cargo update" is not included in this commit)
Before this patch, importing a physical backup followed the same path
as ingesting any WAL records:
1. All the data pages from the backup are first collected in the
DatadirModification object.
2. Then, they are "committed" to the Repository. They are written to
the in-memory layer
3. Finally, the in-memory layer is frozen, and flushed to disk as a
L0 delta layer file.
This was pretty inefficient. In step 1, the whole physical backup was
held in memory. If the backup is large, you simply run out of
memory. And in step 3, the resulting L0 delta layer file is large,
holding all the data again. That's a problem if the backup is larger
than 5 GB: Amazon S3 doesn't allow uploading files larger than 5 GB
(without using multi-part upload, see github issue #1910). So we want
to avoid that.
To alleviate those problems, optimize the codepath for importing a
physical backup. The basic flow is the same as before, but step 1
is optimized so that it doesn't accumulate all the data in memory,
and step 3 writes the data in image layers instead of one large delta
layer.
Previously, upon branching, if no starting LSN is specified, we
determine the start LSN based on the source timeline's last record LSN
in `timelines::create_timeline` function, which then calls `Repository::branch_timeline`
to create the timeline.
Inside the `LayeredRepository::branch_timeline` function, to start branching,
we try to acquire a GC lock to prevent GC from removing data needed
for the new timeline. However, a GC iteration takes time, so the GC lock
can be held for a long period of time. As a result, the previously determined
starting LSN can become invalid because of GC.
This PR fixes the above issue by delaying the LSN calculation part and moving it to be
inside `LayeredRepository::branch_timeline` function.
download operations of all timelines for one tenant are now grouped
together so when attach is invoked pageserver downloads all of them
and registers them in a single apply_sync_status_update call so
branches can be used safely with attach/detach
I noticed that the pageserver has a very large virtual memory size,
several GB, even though it doesn't actually use that much
memory. That's not much of a problem normally, but I hit it because I
wanted to run tests with a limited virtual memory size, by calling
setrlimit(RLIMIT_AS), but the highest limit you can set is 2 GB. I was
not able to start pageserver with a limit of 2 GB.
On Linux, each thread allocates 32 MB of virtual memory. I read this
on some random forum on the Internet, but unfortunately could not find
the source again now. Empirically, reducing the number of threads clearly
helps to bring down the virtual memory size.
Aside from the virtual memory usage, it seems excessive to launch 40
threads in both of those thread pools. The tokio default is to have as
many worker threads as there are CPU cores in the system. That seems
like a fine heuristic for us, too, so remove the explicit setting of
the pool size and rely on the default. Note that the GC and compaction
tasks are actually run with tokio spawn_blocking, so the threads that
are actually doing the work, and possibly waiting on I/O, are not
consuming threads from the thread pool. The WAL receiver work is done
in the tokio worker threads, but the WAL receivers are more CPU bound
so that seems OK.
Also remove the explicit maxinum on blocking tasks. I'm not sure what
the right value for that would be, or whether the value we set (100)
would be better than the tokio default (512). Since the value was
arbitrary, let's just rely on the tokio default for that, too.
* Avoid reconnecting to safekeeper immediately after its failure by limiting candidates to those with fewest connection attempts. Thus we don't have to wait lagging_wal_timeout (10s by default) before switch happens even if no new changes are generated, and current test_restarts_under_load expects some commits to happen within 4s.
* Make default max_lsn_wal_lag larger, otherwise we constant reconnections happen during normal work.
* Fix wal_connection_attempts maintanance, preventing busy loop of reconnections.
* Implement page servise 'fullbackup' endpoint that works like basebackup, but also sends relational files
* Add test_runner/batch_others/test_fullbackup.py
Co-authored-by: bojanserafimov <bojan.serafimov7@gmail.com>
E g this log line contains duplicated data:
INFO /timeline_create{tenant=8d367870988250a755101b5189bbbc17
new_timeline=Some(27e2580f51f5660642d8ce124e9ee4ac) lsn=None}:
bootstrapping{timeline=27e2580f51f5660642d8ce124e9ee4ac
tenant=8d367870988250a755101b5189bbbc17}:
created root timeline 27e2580f51f5660642d8ce124e9ee4ac
timeline.lsn 0/16960E8
this avoids variable duplication in `bootstrapping` subspan
