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    Data generation

    Generate test documents from 17 Faker categories, previewed before anything is written.

    Checked against v1.11.0 Updated
    The data generation dialog mapping fields to Faker categories, with a preview
    Test data · Fields mapped to Faker categories, previewed before writing
    • Visual schema builder for the generated document structure
    • Supported types: String, Number, Boolean, Date, ObjectId, Object (nested), Array (configurable length and element type)
    • Faker providers across 17 named categories: personal names, internet and email, location and address, phone numbers, company, commerce, finance, lorem ipsum, numbers and Booleans, dates and times, database ids, random data, images, vehicles, music, system and files, and Git
    • Four value modes per field: Faker, Literal, List (random from a set), and Range (numeric min/max with decimal places)
    • Per-field null probability from 0 to 100% for realistic sparse data
    • Seed the tree from a sampled collection and it keeps each field’s type: array element types, Long, Int32, Double, Decimal128, and fields only sometimes null
    • A field a unique index covers is generated so no two documents repeat a value, and a second run continues the series instead of replaying the first
    • A GeoJSON coordinates field is generated as the shape its own geometry needs, a pair for a Point, two for a LineString, a closed ring for a Polygon, so a 2dsphere index accepts it
    • Preview and copy a sample document before generating
    • Up to 100,000 documents per run on Pro, 500 on Free, with background progress