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After this, a layer's start bound is always defined to be inclusive, and end bound exclusive. For example, if you have a layer in the range 100-200, that layer can be used for GetPage@LSN requests at LSN 100, 199, or anything in between. But for LSN 200, you need to look at the next layer (if one exists). This is one part of a fix for https://github.com/zenithdb/zenith/issues/517. After this, the page server shouldn't create layers for the same segment with the same LSN, which avoids the issue. However, the same thing would still happen, if you managed to create layers with same start LSN again. That could happen e.g. if you had two page servers running, or in some weird crash/restart scenario, or due to bugs or features added later. The next commit makes the layer map more robust, so that it tolerates that situation without deleting wrong files.
## Page server architecture
The Page Server has a few different duties:
- Respond to GetPage@LSN requests from the Compute Nodes
- Receive WAL from WAL safekeeper
- Replay WAL that's applicable to the chunks that the Page Server maintains
- Backup to S3
The Page Server consists of multiple threads that operate on a shared
repository of page versions:
| WAL
V
+--------------+
| |
| WAL receiver |
| |
+--------------+
+----+
+---------+ .......... | |
| | . . | |
GetPage@LSN | | . backup . -------> | S3 |
-------------> | Page | repository . . | |
| Service | .......... | |
page | | +----+
<------------- | |
+---------+ +--------------------+
| Checkpointing / |
| Garbage collection |
+--------------------+
Legend:
+--+
| | A thread or multi-threaded service
+--+
....
. . Component that we will need, but doesn't exist at the moment. A TODO.
....
---> Data flow
<---
Page Service
------------
The Page Service listens for GetPage@LSN requests from the Compute Nodes,
and responds with pages from the repository.
WAL Receiver
------------
The WAL receiver connects to the external WAL safekeeping service (or
directly to the primary) using PostgreSQL physical streaming
replication, and continuously receives WAL. It decodes the WAL records,
and stores them to the repository.
Repository
----------
The repository stores all the page versions, or WAL records needed to
reconstruct them. Each tenant has a separate Repository, which is
stored in the .zenith/tenants/<tenantid> directory.
Repository is an abstract trait, defined in `repository.rs`. It is
implemented by the LayeredRepository object in
`layered_repository.rs`. There is only that one implementation of the
Repository trait, but it's still a useful abstraction that keeps the
interface for the low-level storage functionality clean. The layered
storage format is described in layered_repository/README.md.
Each repository consists of multiple Timelines. Timeline is a
workhorse that accepts page changes from the WAL, and serves
get_page_at_lsn() and get_rel_size() requests. Note: this has nothing
to do with PostgreSQL WAL timeline. The term "timeline" is mostly
interchangeable with "branch", there is a one-to-one mapping from
branch to timeline. A timeline has a unique ID within the tenant,
represented as 16-byte hex string that never changes, whereas a
branch is a user-given name for a timeline.
Each repository also has a WAL redo manager associated with it, see
`walredo.rs`. The WAL redo manager is used to replay PostgreSQL WAL
records, whenever we need to reconstruct a page version from WAL to
satisfy a GetPage@LSN request, or to avoid accumulating too much WAL
for a page. The WAL redo manager uses a Postgres process running in
special zenith wal-redo mode to do the actual WAL redo, and
communicates with the process using a pipe.
Checkpointing / Garbage Collection
----------------------------------
Periodically, the checkpointer thread wakes up and performs housekeeping
duties on the repository. It has two duties:
### Checkpointing
Flush WAL that has accumulated in memory to disk, so that the old WAL
can be truncated away in the WAL safekeepers. Also, to free up memory
for receiving new WAL. This process is called "checkpointing". It's
similar to checkpointing in PostgreSQL or other DBMSs, but in the page
server, checkpointing happens on a per-segment basis.
### Garbage collection
Remove old on-disk layer files that are no longer needed according to the
PITR retention policy
TODO: Backup service
--------------------
The backup service is responsible for periodically pushing the chunks to S3.
TODO: How/when do restore from S3? Whenever we get a GetPage@LSN request for
a chunk we don't currently have? Or when an external Control Plane tells us?
TODO: Sharding
--------------------
We should be able to run multiple Page Servers that handle sharded data.