risingwavelabs/risingwave · error · GenDataFusionPlanError

Generating plan error

Error message

Generating plan error: {0}

What it means

The `Generating` variant of `GenDataFusionPlanError` wraps an underlying `RwError` produced while building the DataFusion `LogicalPlan` (e.g. schema/type conversion failures when mapping RisingWave fields to Arrow/DataFusion types). The message prefixes the wrapped error's display text.

Solutions

1. Inspect the wrapped source error (`RwError`) for the root cause and fix accordingly.
2. Check for unsupported column/expression types in the query and cast them to supported types.
3. Align the DataFusion dependency version with what the translation code expects.

Example fix

-- before
SELECT * FROM iceberg_tbl WHERE exotic_udb_col > 1; -- type fails DataFusion translation
-- after
SELECT * FROM iceberg_tbl WHERE CAST(exotic_col AS DOUBLE) > 1.0;

// pre-check column types are Arrow-representable before generating the plan
const bad = cols.filter(c => !ARROW_SUPPORTED_TYPES.has(c.type));
if (bad.length) throw new Error("columns unsupported by DataFusion: " + bad.map(c => c.name));

function isArrowRepresentable(rwType) { return ARROW_SUPPORTED_TYPES.has(rwType); }

match try_gen_datafusion_plan(&plan) {
    Err(GenDataFusionPlanError::Generating(src)) => {
        log::error!("datafusion plan generation failed: {src}"); // inspect wrapped RwError
    }
    r => r?,
}

When it happens

Trigger: Any failure inside DataFusion plan construction during `try_gen_datafusion_plan`: unsupported RisingWave data types with no Arrow equivalent, invalid expression translation, or DataFusion API errors while registering scans/projections.

Common situations: Iceberg tables with column types not representable in the expected Arrow/DataFusion schema; expression pushdown of functions DataFusion does not implement; version drift between the DataFusion dependency and the translation code.

Understand the failure class

Background: "query failed", "%w: SQL error" — wrapped database query errors in Go libraries explained — this error's family across 3 libraries.

Related errors

• Missing Iceberg Scan
• Unsupported Plan Node
• adlsgen2.authority_host does not parse as a URL
• adlsgen2.authority_host must not contain a path component
• adlsgen2.authority_host must not contain a query or fragment

AI-assisted analysis of risingwavelabs/risingwave@6469eb736d (2026-09-11). Data as JSON: /api/errors/6ef1e52968bef081. Report an issue: GitHub.

Appendix: source

Thrown at src/frontend/src/datafusion/execute/mod.rs:66

mod query_planner;

pub(crate) use memory_ctx::create_df_spillable_budget_ctx;
const DF_MANAGED_SPILL_DIR: &str = "df_batch_spill/";

#[derive(Clone)]
pub struct DfBatchQueryPlanResult {
    pub(crate) plan: Arc<LogicalPlan>,
    pub(crate) schema: RwSchema,
    pub(crate) stmt_type: StatementType,
}

#[derive(Debug, Error)]
pub enum GenDataFusionPlanError {
    #[error("Missing Iceberg Scan")]
    MissingIcebergScan,
    #[error("Unsupported Plan Node")]
    UnsupportedPlanNode,
    #[error("Generating plan error: {0}")]
    Generating(#[source] RwError),
}

pub fn try_gen_datafusion_plan(
    optimized_logical: &BatchOptimizedLogicalPlanRoot,
) -> Result<Arc<LogicalPlan>, GenDataFusionPlanError> {
    use crate::optimizer::DataFusionExecuteCheckerExt;

    let check_result = optimized_logical.plan.check_for_datafusion();
    if !check_result.have_iceberg_scan {
        return Err(GenDataFusionPlanError::MissingIcebergScan);
    }
    if !check_result.supported {
        return Err(GenDataFusionPlanError::UnsupportedPlanNode);
    }

    let plan = optimized_logical
        .gen_datafusion_logical_plan()

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