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The v0.14-alpha release focuses on enhancing accelerated dataset performance and data integrity, with support for configuring primary keys and indexes. Additionally, the GraphQL data connector been introduced, along with improved dataset registration and loading error information.

Highlights​

• Accelerated Datasets: Ensure data integrity using primary key and unique index constraints. Configure conflict handling to either upsert new data or drop it. Create indexes on frequently filtered columns for faster queries on larger datasets.

• GraphQL Data Connector: Initial support for using GraphQL as a data source.

Example Spicepod showing how to use primary keys and indexes with accelerated datasets:

datasets:
  - from: eth.blocks
    name: blocks
    acceleration:
      engine: duckdb # Use DuckDB acceleration engine
      primary_key: '(hash, timestamp)'
      indexes:
        number: enabled # same as `CREATE INDEX ON blocks (number);`
        '(number, hash)': unique # same as `CREATE UNIQUE INDEX ON blocks (number, hash);`
      on_conflict:
        '(hash, number)': drop # possible values: drop (default), upsert
        '(hash, timestamp)': upsert

Primary Keys, constraints, and indexes are currently supported when using SQLite, DuckDB, and PostgreSQL acceleration engines.

Learn more with the indexing quickstart and the primary key sample.

Read the Local Acceleration documentation.