Streaming Sui data with Goldsky

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Overview

Goldsky is a high-performance data indexing provider for Sui that makes it easy to extract, transform, and load on-chain data to power both application and analytics use cases via Mirror (real-time data replication pipelines).

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Scope

Goldsky has partnered with Sui to make our product available to the ecosystem and provide dedicated support for Sui data indexing. The full scope of our partnership (which products are enabled, what partner-exclusive benefit is available, and who this benefit is available to) is outlined below.

Where perks are available to projects specified by the chain ecosystem, please reach out to their developer relations team for an access code and link to private signup form. Where perks are openly available to all developers, please contact sales@goldsky.com to apply the applicable partnership perks to your project.

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Getting started

To use Goldsky, you’ll need to create an account, install the CLI, and log in.

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Mirror

Mirror pipelines allow users to replicate data into their own infrastructure (any of the supported sinks) in real time. The supported data sources are the following chain-level datasets: checkpoints, packages, transactions, epochs and events.

For a complete overview of how to deploy Mirror pipelines, including a video walkthrough, check the Create a Pipeline. Below, we will look at a high level into the different ways by which you can deploy Mirror pipelines; in specific, we’ll be streaming the sui.transactions chain-level dataset into a PostgreSQL database.

Pipelines can be deployed on Goldsky in 3 ways:

• Using the Pipeline Builder in the Goldsky dashboard:
  • Select Direct Indexing as data source filter on Sui and select Transactions as dataset.
  • Follow the default options in the next steps and choose your pre-configured sink.
  • Deploy pipeline.
• Using the interactive CLI:
  • Enter command goldsky pipeline create <pipeline-name>.
  • This will kick off a guided flow with the first step to choose the dataset type. Choose chain-level dataset.
  • Next, select Sui as chain and Raw Transactions as the dataset. We will process historical data so select Process all historical data.
  • When asked to choose another source, choose No
  • Add your pre-configured sink. In this example case, we chose PostgreSQL and as a next step we selected the database schema.
  • Pipeline will be deployed automatically.
• Using a pipeline configuration file:
  • This makes it easier to set up complex pipelines involving multiple sources, multiple sinks, and more complex, SQL-based transformations. For the full reference documentation on, click here.
  • As in the previous steps, we’ll be deploying a pipeline to stream Sui transactions. Unlike the other methods, we have added a transformation to only select specific data attributes from the whole dataset. This is the configuration file:

apiVersion: 3
name: sui-raw-transactions
status: ACTIVE
sources:
  sui_transactions:
    dataset_name: sui.transactions
    version: 1.0.0
    type: dataset
    start_at: earliest
transforms:
  select_relevant_fields:
    primary_key: tx_sequence_number
    sql: |
      SELECT
          tx_sequence_number,
          checkpoint_sequence_number,
          effects,
          sender_signed_data
      FROM
          sui_transactions
sinks:
  postgres_sui_transactions:
    type: postgres
    table: sui_transactions
    schema: public
    secret_name: <YOUR_SECRET_NAME>
    description: 'Postgres sink for: sui_transactions'
    from: sui_transactions

• Add your corresponding secret name and run goldsky pipeline apply sui-transactions.yaml to deploy the pipeline.

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Getting support

Can't find what you're looking for? Reach out to us at support@goldsky.com for help.