Getting data into datafusion is not well documented, especially using serde_json or serde data.

This example shows how to convert a serde_json::Value::Array into a datafusion DataFrame, manipulate the dataframe in datafusion, then convert it back to serde_json.

# Cargo.toml
datafusion = "47.0.0"
serde_arrow = { version = "0.13.3", features = ["arrow-55"] }
// `serde_json::Value`
let json = serde_json::json!([{
    "date": "2025-06-05",
    "test": "test",
    "price": 1.01,
}]);

let ctx = SessionContext::new();

let serde_json::Value::Array(json_array) = &json else {
    return Err(anyhow::anyhow!("Expected JSON array, got different type"));
};

if json_array.is_empty() {
    return Ok(Vec::new());
}

// Configure `TracingOptions` to allow null fields and coerce numbers
let tracing_options = TracingOptions::default()
    .allow_null_fields(true)
    .coerce_numbers(true);

// Get the schema from actual data, using samples, with `TracingOptions`
let fields = Vec::<FieldRef>::from_samples(json_array, tracing_options)?;

// Convert `serde_json::Value::Array` to `RecordBatch` using `serde_arrow`
let record_batch = serde_arrow::to_record_batch(&fields, &json_array)?;

// Create a DataFrame from the `RecordBatch`
let mut df = ctx.read_batch(record_batch)?;

// Add a new column `new_col` using DataFrame API
df = df.with_column("new_col", lit("test".to_string()))?;

// Execute the DataFrame query
let result_batches = df.collect().await?;

// Convert back to `serde_json` using `serde_arrow`
let all_json_values = result_batches
    .into_iter()
    .flat_map(|batch| {
        serde_arrow::from_record_batch(&batch).unwrap_or_else(|_| Vec::new())
    })
    .collect::<Vec<serde_json::Value>>();

#[derive(Default, Debug, Clone, Deserialize, Serialize)]
pub struct TestData {
    date: String,
    test: String,
    price: f64,
    new_col: String,
}

// Convert the `serde_json::Value` to Vec<TestData>
let test_data: Vec<TestData> =
    serde_json::from_value(serde_json::Value::Array(all_json_values))?;

assert_eq!(
    test_data,
    Vec![
        TestData {
            date: "2025-06-05".to_string(),
            test: "test".to_string(),
            price: 1.01,
            new_col: "test".to_string(),
        },
    ]
);