#account #bigtable #plugin #thread #service-account #solana #instance

solana-geyser-plugin-bigtable

The Solana AccountsDb plugin for Bigtable database

2 stable releases

1.10.31 Jul 30, 2022
1.10.5 Apr 9, 2022

#9 in #bigtable

Apache-2.0

89KB
2K SLoC

solana-geyser-plugin-bigtable

The solana-geyser-plugin-bigtable crate implements a plugin storing account, block, transaction data to a Bigtable database using the Geyser Plugin Framework.

Configuration File Format

The plugin is configured using the input configuration file. An example configuration file looks like the following:

{
    "libpath": "/solana/target/release/libsolana_geyser_plugin_bigtable.so",
	"credential_path": "/home/solana/geyser-big-table-creds.json",
	"instance": "geyser-bigtable",
	"threads": 80,
	"batch_size": 20,
	"panic_on_db_errors": true,
	"accounts_selector" : {
           "accounts" : ["*"]
    },
}

credential_path specifies the path of the Bigtable credential JSON file. Please refer to https://cloud.google.com/docs/authentication/getting-started on creating a service account key. It must be in the format specified by https://github.com/durch/rust-goauth. For example:

{
   "type": "service_account",
   "project_id": "dummy",
   "private_key_id": "dummy",
   "private_key": "-----BEGIN PRIVATE KEY-----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\n3osZlZTgx+pM3sO6ITV6U4ID2Q==\n-----END PRIVATE KEY-----\n",
   "client_email": "dummy@developer.gserviceaccount.com",
   "client_id": "dummy",
   "auth_uri": "https://accounts.google.com/o/oauth2/auth",
   "token_uri": "https://accounts.google.com/o/oauth2/token",
   "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
   "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/457015483506-compute%40developer.gserviceaccount.com"
}

The instance specifies the Bigtable instance name.

To improve the throughput to the database, the plugin supports connection pooling using multiple threads, each maintaining a connection to the PostgreSQL database. The count of the threads is controlled by the threads field. A higher thread count usually offers better performance.

To further improve performance when saving large numbers of accounts at startup, the plugin uses bulk inserts. The batch size is controlled by the batch_size parameter. This can help reduce the round trips to the database.

The panic_on_db_errors can be used to panic the validator in case of database errors to ensure data consistency.

Account Selection

The accounts_selector can be used to filter the accounts that should be persisted.

For example, one can use the following to persist only the accounts with particular Base58-encoded Pubkeys,

    "accounts_selector" : {
         "accounts" : ["pubkey-1", "pubkey-2", ..., "pubkey-n"],
    }

Or use the following to select accounts with certain program owners:

    "accounts_selector" : {
         "owners" : ["pubkey-owner-1", "pubkey-owner-2", ..., "pubkey-owner-m"],
    }

To select all accounts, use the wildcard character (*):

    "accounts_selector" : {
         "accounts" : ["*"],
    }

BigTable Setup

Development Environment

The Cloud BigTable emulator can be used during development/test. See https://cloud.google.com/bigtable/docs/emulator for general setup information.

Process:

  1. Make sure install GCP CLI, see https://cloud.google.com/sdk/docs/install-sdk.
  2. Install the Bigtable CLI CBT https://cloud.google.com/bigtable/docs/cbt-overview.
  3. Run gcloud beta emulators bigtable start in the background
  4. Run $(gcloud beta emulators bigtable env-init) to establish the BIGTABLE_EMULATOR_HOST environment variable
  5. Run ./scripts/init-bigtable.sh to configure the emulator
  6. Develop/test

Production Environment

Export a standard GOOGLE_APPLICATION_CREDENTIALS environment variable to your service account credentials. The project should contain a BigTable instance configured in the config file must have been initialized by running the ./init-bigtable.sh script.

Depending on what operation mode is required, either the https://www.googleapis.com/auth/bigtable.data or https://www.googleapis.com/auth/bigtable.data.readonly OAuth scope will be requested using the provided credentials.

Object Models

Account and slot metadata are supported with plan to support transaction data, block metadata and account secondary indexes.

The storage-proto contains the gRPC models for the objects. For example for accounts:

message account {
    bytes pubkey = 1;
    bytes owner = 2;
    uint64 lamports = 3;
    uint64 slot = 4;
    bool executable = 5;
    uint64 rent_epoch = 6;
    bytes data = 7;
    uint64 write_version = 8;
    UnixTimestamp updated_on = 9;
}

The following are the tables in the Postgres database

Table Description
account Account data
slot Slot metadata

The model data is encoded into binary format and then compressed using compress_best src/compression.rs.

Dependencies

~53–71MB
~1.5M SLoC