Try to follow Prometheus style-guide https://prometheus.io/docs/practices/naming/ for metrics names. More specifically:
- Use `pageserver_` prefix for all pagserver metrics
- Specify `_seconds` unit in time metrics
- Use unit as a suffix in other cases, such as `_hits`, `_bytes`, `_records`
- Use `_total` suffix for accumulating counters (note that Histograms append that suffix internally)
Add tenant config API and 'zenith tenant config' CLI command.
Add 'show' query to pageserver protocol for tenantspecific config parameters
Refactoring: move tenant_config code to a separate module.
Save tenant conf file to tenant's directory, when tenant is created to recover it on pageserver restart.
Ignore error during tenant config loading, while it is not supported by console
Define PiTR interval for GC.
refer #1320
This depends on a hacked version of the 'pprof-rs' crate. Because of
that, it's under an optional 'profiling' feature. It is disabled by
default, but enabled for release builds in CircleCI config. It doesn't
currently work on macOS.
The flamegraph is written to 'flamegraph.svg' in the pageserver
workdir when the 'pageserver' process exits.
Add a performance test that runs the perf_pgbench test, with profiling
enabled.
We now use a page cache for those, instead of slurping the whole index into
memory.
Fixes https://github.com/zenithdb/zenith/issues/1356
This is a backwards-incompatible change to the storage format, so
bump STORAGE_FORMAT_VERSION.
This introduces two new abstraction layers for I/O:
- Block I/O, and
- Blob I/O.
The BlockReader trait abstracts a file or something else that can be read
in 8kB pages. It is implemented by EphemeralFiles, and by a new
FileBlockReader struct that allows reading arbitrary VirtualFiles in that
manner, utilizing the page cache.
There is also a new BlockCursor struct that works as a cursor over a
BlockReader. When you create a BlockCursor and read the first page using
it, it keeps the reference to the page. If you access the same page again,
it avoids going to page cache and quickly returns the same page again.
That can save a lot of lookups in the page cache if you perform multiple
reads.
The Blob-oriented API allows reading and writing "blobs" of arbitrary
length. It is a layer on top of the block-oriented API. When you write
a blob with the write_blob() function, it writes a length field
followed by the actual data to the underlying block storage, and
returns the offset where the blob was stored. The blob can be
retrieved later using the offset.
Finally, this replaces the I/O code in image-, delta-, and in-memory
layers to use the new abstractions. These replace the 'bookfile'
crate.
This is a backwards-incompatible change to the storage format.
This is a backwards-incompatible change. The new pageserver cannot
read repositories created with an old pageserver binary, or vice
versa.
Simplify Repository to a value-store
------------------------------------
Move the responsibility of tracking relation metadata, like which
relations exist and what are their sizes, from Repository to a new
module, pgdatadir_mapping.rs. The interface to Repository is now a
simple key-value PUT/GET operations.
It's still not any old key-value store though. A Repository is still
responsible from handling branching, and every GET operation comes
with an LSN.
Mapping from Postgres data directory to keys/values
---------------------------------------------------
All the data is now stored in the key-value store. The
'pgdatadir_mapping.rs' module handles mapping from PostgreSQL objects
like relation pages and SLRUs, to key-value pairs.
The key to the Repository key-value store is a Key struct, which
consists of a few integer fields. It's wide enough to store a full
RelFileNode, fork and block number, and to distinguish those from
metadata keys.
'pgdatadir_mapping.rs' is also responsible for maintaining a
"partitioning" of the keyspace. Partitioning means splitting the
keyspace so that each partition holds a roughly equal number of keys.
The partitioning is used when new image layer files are created, so
that each image layer file is roughly the same size.
The partitioning is also responsible for reclaiming space used by
deleted keys. The Repository implementation doesn't have any explicit
support for deleting keys. Instead, the deleted keys are simply
omitted from the partitioning, and when a new image layer is created,
the omitted keys are not copied over to the new image layer. We might
want to implement tombstone keys in the future, to reclaim space
faster, but this will work for now.
Changes to low-level layer file code
------------------------------------
The concept of a "segment" is gone. Each layer file can now store an
arbitrary range of Keys.
Checkpointing, compaction
-------------------------
The background tasks are somewhat different now. Whenever
checkpoint_distance is reached, the WAL receiver thread "freezes" the
current in-memory layer, and creates a new one. This is a quick
operation and doesn't perform any I/O yet. It then launches a
background "layer flushing thread" to write the frozen layer to disk,
as a new L0 delta layer. This mechanism takes care of durability. It
replaces the checkpointing thread.
Compaction is a new background operation that takes a bunch of L0
delta layers, and reshuffles the data in them. It runs in a separate
compaction thread.
Deployment
----------
This also contains changes to the ansible scripts that enable having
multiple different pageservers running at the same time in the staging
environment. We will use that to keep an old version of the pageserver
running, for clusters created with the old version, at the same time
with a new pageserver with the new binary.
Author: Heikki Linnakangas
Author: Konstantin Knizhnik <knizhnik@zenith.tech>
Author: Andrey Taranik <andrey@zenith.tech>
Reviewed-by: Matthias Van De Meent <matthias@zenith.tech>
Reviewed-by: Bojan Serafimov <bojan@zenith.tech>
Reviewed-by: Konstantin Knizhnik <knizhnik@zenith.tech>
Reviewed-by: Anton Shyrabokau <antons@zenith.tech>
Reviewed-by: Dhammika Pathirana <dham@zenith.tech>
Reviewed-by: Kirill Bulatov <kirill@zenith.tech>
Reviewed-by: Anastasia Lubennikova <anastasia@zenith.tech>
Reviewed-by: Alexey Kondratov <alexey@zenith.tech>
This introduces a new module to handle thread creation and shutdown.
All page server threads are now registered in a global hash map, and
there's a function to request individual threads to shut down gracefully.
Thread shutdown request is signalled to the thread with a flag, as well
as a Future that can be used to wake up async operations if shutdown is
requested. Use that facility to have the libpq listener thread respond
to pageserver shutdown, based on Kirill's earlier prototype
(https://github.com/zenithdb/zenith/pull/1088). That addresses
https://github.com/zenithdb/zenith/issues/1036, previously the libpq
listener thread would not exit until one more connection arrives.
This also eliminates a resource leak in the accept() loop. Previously,
we added the JoinHanlde of each new thread to a vector but old handles
for threads that had already exited were never removed.
Move the code for decoding a WAL stream into WAL records into
'postgres_ffi', and keep the code to parse the WAL records deeper in
'pageserver' crate, renamed to walrecord.rs.
This tidies up the dependencies a bit. 'walkeeper' reuses the same
waldecoder routines, and it used to depend on 'pageserver' because of
that. Now it only depends on 'postgres_ffi'.
(The comment in walkeeper/Cargo.toml that claimed that the dependency was
needed for ZTimelineId was obsolete. ZTimelineId is defined in
'zenith_utils', the dependency was actually needed for the waldecoder.)
Out of scope LSNs include pre initdb LSNs, and LSNs prior to
latest_gc_cutoff.
To get there there was also two cleanups:
* Fix error handling in Execute message handler. This fixes behaviour
when basebackup retured an error. Previously pageserver thread just
died.
* Remove "ancestor" file which previously contained ancestor id and
branch lsn. Currently the same data can be obtained from metadata file.
And just the way we handled ancestor file in the code introduced the
case when branching fails timeline directory is created but there is no data in it
except ancestor file. And this confused gc because it scans
directories. So it is better to just remove ancestor file and clean up
this timeline directory creation so it happens after all validity
checks have passed
The buffer cache is shared across all tenants, allowing memory to be
dynamically allocated where it's needed the most. The cache works on 8 kB
pages, and uses the clock algorithm for replacement policy; same as the
PostgreSQL buffer cache.
One peculiarity is that the materialized page versions can be looked up
by an inexact LSN, to find the latest page version with an LSN >= the
search key.
The code is structured to support caching other kinds of pages in the same
cache in the future, but with a different mapping key.
Co-authored-by: Patrick Insinger <patrick@zenith.tech>
Currently, whenever a page version is needed from an image or delta
layer, we open the file and read and parse the bookfile headers. That's
pretty expensive. To reduce the overhead, introduce a cache of open file
descriptors, and use that to cache the Book objects so that we don't need
to read the metadata on every access.
Adds simple global tracking of memory used by the in-memory layers. It's
very approximate, it doesn't take into account allocator, memory
fragmentation or many other things, but it's a good first step.
After storing a WAL record in the repository, the WAL receiver checks
if the global memory usage. If it's above a configurable threshold (hard
coded at 128 MB at the moment), it evicts a layer. The victim layer is
chosen by GClock algorithm, similar to that used in the Postgres buffer
cache.
This stops the page server from using an unbounded amount of memory. It's
pretty crude, the eviction and materializing and writing a layer to disk
happens now in the WAL receiver thread. It would be nice to move that
to a background thread, and it would be nice to have a smarter policy on
when to materialize a new image layer and when to just write out a delta
layer, and it would be nice to have more accurate accounting of memory.
But this should fix the most pressing OOM issues, and is a step in the
right direction.
Co-authored-by: Patrick Insinger <patrickinsinger@gmail.com>
- Change hardcoded OLDEST_INMEM_DISTANCE value to pageserver config option checkpoint_distance.
- Get rid of 'force' flag in checkpoint_internal(). Use checkpoint_distance=0 instead.
Support is done via pytest-xdist plugin.
To use the feature add -n<concurrency> to pytest invocation
e.g. pytest -n8 to run 8 tests in parallel.
Changes in code are mostly about ports assigning. Previously port for
pageserver was hardcoded without the ability to override through zenith
cli and ports for started compute nodes were calculated twice, in zenith
cli and in test code. Now zenith cli supports port arguments for
pageserver and compute nodes to be passed explicitly.
Tests are modified in such a way that each worker gets a non overlapping
port range which can be configured and now contains 100 ports. These
ports are distributed to test services (pageserver, wal acceptors,
compute nodes) so they can work independently.
This contains a lowest common denominator of pageserver and safekeeper log
initialisation routines. It uses daemonize flag to decide where to
stream log messages. In case daemonize is true log messages are
forwarded to file. Otherwise streaming to stdout is used. Usage of
stdout for log output is the default in docker side of things, so make
it easier to browse our logs via builtin docker commands.
Once upon a time, 'page_cache.rs' contained an actual page cache, but
it hasn't for a very long time. Rename to reflect what it actually does
these days.
Now that we only have one Repository implementation, no need for the
command-line options to choose it either. I'm removing these as a separate
commit to show what we will need to do if we add another Repository
implementation in the future (even though I don't foresee us doing that
any time soon)
The layered storage format is good enough that we don't need the rocksdb
implementation anymore. There are a lot of known issues but we'll keep
working on them.
This replaces the RocksDB based implementation with an approach using
"snapshot files" on disk, and in-memory btreemaps to hold the recent
changes.
This make the repository implementation a configuration option. You can
choose 'layered' or 'rocksdb' with "zenith init --repository-format=<format>"
The unit tests have been refactored to exercise both implementations.
'layered' is now the default.
Push/pull is not implemented. The 'test_history_inmemory' test has been
commented out accordingly. It's not clear how we will implement that
functionality; probably by copying the snapshot files directly.
Current state with authentication.
Page server validates JWT token passed as a password during connection
phase and later when performing an action such as create branch tenant
parameter of an operation is validated to match one submitted in token.
To allow access from console there is dedicated scope: PageServerApi,
this scope allows access to all tenants. See code for access validation in:
PageServerHandler::check_permission.
Because we are in progress of refactoring of communication layer
involving wal proposer protocol, and safekeeper<->pageserver. Safekeeper
now doesn’t check token passed from compute, and uses “hardcoded” token
passed via environment variable to communicate with pageserver.
Compute postgres now takes token from environment variable and passes it
as a password field in pageserver connection. It is not passed through
settings because then user will be able to retrieve it using pg_settings
or SHOW ..
I’ve added basic test in test_auth.py. Probably after we add
authentication to remaining network paths we should enable it by default
and switch all existing tests to use it.
The metrics are served by an http endpoint, which
is meant to be spawned in a new thread.
In the future the endpoint will provide more APIs,
but for the time being, we won't bother with proper routing.
This clarifies - I hope - the abstractions between Repository and
ObjectRepository. The ObjectTag struct was a mix of objects that could
be accessed directly through the public Timeline interface, and also
objects that were created and used internally by the ObjectRepository
implementation and not supposed to be accessed directly by the
callers. With the RelishTag separaate from ObjectTag, the distinction
is more clear: RelishTag is used in the public interface, and
ObjectTag is used internally between object_repository.rs and
object_store.rs, and it contains the internal metadata object types.
One awkward thing with the ObjectTag struct was that the Repository
implementation had to distinguish between ObjectTags for relations,
and track the size of the relation, while others were used to store
"blobs". With the RelishTags, some relishes are considered
"non-blocky", and the Repository implementation is expected to track
their sizes, while others are stored as blobs. I'm not 100% happy with
how RelishTag captures that either: it just knows that some relish
kinds are blocky and some non-blocky, and there's an is_block()
function to check that. But this does enable size-tracking for SLRUs,
allowing us to treat them more like relations.
This changes the way SLRUs are stored in the repository. Each SLRU
segment, e.g. "pg_clog/0000", "pg_clog/0001", are now handled as a
separate relish. This removes the need for the SLRU-specific
put_slru_truncate() function in the Timeline trait. SLRU truncation is
now handled by caling put_unlink() on the segment. This is more in
line with how PostgreSQL stores SLRUs and handles their trunction.
The SLRUs are "blocky", so they are accessed one 8k page at a time,
and repository tracks their size. I considered an alternative design
where we would treat each SLRU segment as non-blocky, and just store
the whole file as one blob. Each SLRU segment is up to 256 kB in size,
which isn't that large, so that might've worked fine, too. One reason
I didn't do that is that it seems better to have the WAL redo
routines be as close as possible to the PostgreSQL routines. It
doesn't matter much in the repository, though; we have to track the
size for relations anyway, so there's not much difference in whether
we also do it for SLRUs.
While working on this, I noticed that the CLOG and MultiXact redo code
did not handle wraparound correctly. We need to fix that, but for now,
I just commented them out with a FIXME comment.
- Add new subdir postgres_ffi/samples/ for config file samples.
- Don't copy wal to the new branch on zenith init or zenith branch.
- Import_timeline_wal on zenith init.
It was pretty cool, but no one used it, and it had gotten badly out of
date. The main interesting thing with it was to see some basic metrics
on the fly, while the page server is running, but the metrics collection
had been broken for a long time, too. Best to just remove it.
this patch adds support for tenants. This touches mostly pageserver.
Directory layout on disk is changed to contain new layer of indirection.
Now path to particular repository has the following structure: <pageserver workdir>/tenants/<tenant
id>. Tenant id has the same format as timeline id. Tenant id is included in
pageserver commands when needed. Also new commands are available in
pageserver: tenant_list, tenant_create. This is also reflected CLI.
During init default tenant is created and it's id is saved in CLI config,
so following commands can use it without extra options. Tenant id is also included in
compute postgres configuration, so it can be passed via ServerInfo to
safekeeper and in connection string to pageserver.
For more info see docs/multitenancy.md.
