Files
neon/compute_tools
Christian Schwarz 450be26bbb fast imports: initial Importer and Storage changes (#9218)
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Co-authored-by: Stas Kelvic <stas@neon.tech>

# Context

This PR contains PoC-level changes for a product feature that allows
onboarding large databases into Neon without going through the regular
data path.

# Changes

This internal RFC provides all the context
* https://github.com/neondatabase/cloud/pull/19799

In the language of the RFC, this PR covers

* the Importer code (`fast_import`) 
* all the Pageserver changes (mgmt API changes, flow implementation,
etc)
* a basic test for the Pageserver changes

# Reviewing

As acknowledged in the RFC, the code added in this PR is not ready for
general availability.
Also, the **architecture is not to be discussed in this PR**, but in the
RFC and associated Slack channel instead.

Reviewers of this PR should take that into consideration.
The quality bar to apply during review depends on what area of the code
is being reviewed:

* Importer code (`fast_import`): practically anything goes
* Core flow (`flow.rs`):
* Malicious input data must be expected and the existing threat models
apply.
* The code must not be safe to execute on *dedicated* Pageserver
instances:
* This means in particular that tenants *on other* Pageserver instances
must not be affected negatively wrt data confidentiality, integrity or
availability.
* Other code: the usual quality bar
* Pay special attention to correct use of gate guards, timeline
cancellation in all places during shutdown & migration, etc.
* Consider the broader system impact; if you find potentially
problematic interactions with Storage features that were not covered in
the RFC, bring that up during the review.

I recommend submitting three separate reviews, for the three high-level
areas with different quality bars.


# References

(Internal-only)

* refs https://github.com/neondatabase/cloud/issues/17507
* refs https://github.com/neondatabase/company_projects/issues/293
* refs https://github.com/neondatabase/company_projects/issues/309
* refs https://github.com/neondatabase/cloud/issues/20646

---------

Co-authored-by: Stas Kelvich <stas.kelvich@gmail.com>
Co-authored-by: Heikki Linnakangas <heikki@neon.tech>
Co-authored-by: John Spray <john@neon.tech>
2024-11-22 22:47:06 +00:00
..
2023-10-18 16:42:22 +03:00
2024-03-20 17:10:46 -05:00

Compute node tools

Postgres wrapper (compute_ctl) is intended to be run as a Docker entrypoint or as a systemd ExecStart option. It will handle all the Neon specifics during compute node initialization:

  • compute_ctl accepts cluster (compute node) specification as a JSON file.
  • Every start is a fresh start, so the data directory is removed and initialized again on each run.
  • Next it will put configuration files into the PGDATA directory.
  • Sync safekeepers and get commit LSN.
  • Get basebackup from pageserver using the returned on the previous step LSN.
  • Try to start postgres and wait until it is ready to accept connections.
  • Check and alter/drop/create roles and databases.
  • Hang waiting on the postmaster process to exit.

Also compute_ctl spawns two separate service threads:

  • compute-monitor checks the last Postgres activity timestamp and saves it into the shared ComputeNode;
  • http-endpoint runs a Hyper HTTP API server, which serves readiness and the last activity requests.

If AUTOSCALING environment variable is set, compute_ctl will start the vm-monitor located in [neon/libs/vm_monitor]. For VM compute nodes, vm-monitor communicates with the VM autoscaling system. It coordinates downscaling and requests immediate upscaling under resource pressure.

Usage example:

compute_ctl -D /var/db/postgres/compute \
            -C 'postgresql://cloud_admin@localhost/postgres' \
            -S /var/db/postgres/specs/current.json \
            -b /usr/local/bin/postgres

State Diagram

Computes can be in various states. Below is a diagram that details how a compute moves between states.

%% https://mermaid.js.org/syntax/stateDiagram.html
stateDiagram-v2
  [*] --> Empty : Compute spawned
  Empty --> ConfigurationPending : Waiting for compute spec
  ConfigurationPending --> Configuration : Received compute spec
  Configuration --> Failed : Failed to configure the compute
  Configuration --> Running : Compute has been configured
  Empty --> Init : Compute spec is immediately available
  Empty --> TerminationPending : Requested termination
  Init --> Failed : Failed to start Postgres
  Init --> Running : Started Postgres
  Running --> TerminationPending : Requested termination
  TerminationPending --> Terminated : Terminated compute
  Failed --> [*] : Compute exited
  Terminated --> [*] : Compute exited

Tests

Cargo formatter:

cargo fmt

Run tests:

cargo test

Clippy linter:

cargo clippy --all --all-targets -- -Dwarnings -Drust-2018-idioms

Cross-platform compilation

Imaging that you are on macOS (x86) and you want a Linux GNU (x86_64-unknown-linux-gnu platform in rust terminology) executable.

Using docker

You can use a throw-away Docker container (rustlang/rust image) for doing that:

docker run --rm \
    -v $(pwd):/compute_tools \
    -w /compute_tools \
    -t rustlang/rust:nightly cargo build --release --target=x86_64-unknown-linux-gnu

or one-line:

docker run --rm -v $(pwd):/compute_tools -w /compute_tools -t rust:latest cargo build --release --target=x86_64-unknown-linux-gnu

Using rust native cross-compilation

Another way is to add x86_64-unknown-linux-gnu target on your host system:

rustup target add x86_64-unknown-linux-gnu

Install macOS cross-compiler toolchain:

brew tap SergioBenitez/osxct
brew install x86_64-unknown-linux-gnu

And finally run cargo build:

CARGO_TARGET_X86_64_UNKNOWN_LINUX_GNU_LINKER=x86_64-unknown-linux-gnu-gcc cargo build --target=x86_64-unknown-linux-gnu --release