Native SQL Support

Algeon selects supported whole relational DataFusion physical-plan candidates for cuDF execution. Support is capability-first: every operator, expression, type, and source in the exact physical candidate must have a native kernel with matching semantics. Memory is not a support criterion; an admitted query runs inside its granted cap and fails with a typed allocation error if it exceeds it. This page is a practical map, not a substitute for validating a production query with algeon_explain_coverage.

Relational plan shapes

Area	Native forms
Sources	Local and S3 object-store Parquet, plus resolved Iceberg Parquet data files; projected columns, row-group selection, partition columns, reader predicates, scan limits, and position deletes when their contracts are supported.
Row operations	Filters, projections, stable or unstable sorts, LIMIT/OFFSET, and schema-compatible UNION ALL.
Aggregation	Global and grouped aggregation, admitted grouping sets, aggregate filters, and partial/final state when the state is explicitly modeled.
Windows	rank, row_number, lag, lead, whole-partition aggregate windows, and cumulative sum/min/max over ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW. rank, lag, and lead require ORDER BY; row_number does not.
Joins	Equi joins and admitted residual/keyless forms for inner, outer, semi, anti, mark, and cross joins. Build side, output projection, key types, and residual expressions can narrow an otherwise supported join kind.
Graph	cuGraph table functions are a separate GPU execution domain. See the cuGraph SQL API for the function-level contract.

When a relational candidate is not supported, or an enabled cost rule does not select it, the executable DataFusion baseline remains in place. Every Iceberg table uses the unified provider: its scan wrapper retains an executable iceberg-datafusion CPU delegate unless native lowering replaces the wrapper. Runtime errors after native execution starts are terminal and do not replay on CPU.

Expressions and scalar functions

Native filter and projection expressions include columns and literals, arithmetic and comparisons, boolean logic, null tests, supported casts, case-sensitive LIKE, literal IN lists, CASE, and string-to-integer TRY_CAST.

The supported DataFusion scalar-function names are:

Family	Functions and important limits
Strings	substring/substr, lower, upper, trim/btrim, ltrim, rtrim, contains, starts_with, ends_with, character_length/length, regexp_replace, and concat. A substring start and optional length must be literal integers with start >= 1 and length >= 0. Pattern, trim, and replacement arguments that define the other operations must be literals.
Numeric	abs, sqrt, and round; round accepts an optional literal integer scale.
Nulls	nullif for compatible native types.
Temporal	date_part/extract for admitted date/timestamp fields, date_trunc for day through microsecond units on timezone-free timestamps, and to_timestamp_seconds for supported integer inputs.

Exact dtype rules still apply and are owned by Data Type Support. In short: timezone-aware timestamps, the basic-list carry matrix, the numeric FixedSizeList<T, D> matrix, and the narrow-decimal carry matrix are carry types: they can be selected and returned unchanged but are not valid expression values, keys, sort or partition values, or aggregate and window inputs. Each matrix on that page states what the output schema preserves.

Aggregates

Native aggregate functions are sum, min, max, count, avg, median, stddev/stddev_samp, stddev_pop, var/variance/var_samp/var_sample, and var_pop/var_population. COUNT(DISTINCT expression) is supported; other distinct aggregates are not. Ordered aggregate arguments are not supported.

Aggregate mode matters. AVG uses explicit sum/count state for partial/final execution. Median is single-stage, and plans that mix median with floating statistical aggregates are rejected.

Floating statistical aggregates (stddev and var variants) run under the GPU-tolerant policy by default, so their results can differ from DataFusion. The exact-host policy matches DataFusion but supports fewer group-key and aggregate types. See statistical_aggregate_execution_mode in configuration.

Source boundaries

Parquet is the native data-file format. Iceberg planning may use REST or Glue catalogs, but data execution still resolves to Parquet source facts. Position deletes are applied natively; equality deletes and delete vectors are rejected. Schema evolution, field-id remapping, source credentials, and remote read capability are validated before execution.

For ad-hoc SQL, validate against the same catalog and server configuration that will execute the query:

SELECT row_kind,
       gpu_path,
       candidate_shape,
       reason_code,
       remedy_code,
       remedy,
       coverage_json
FROM algeon_explain_coverage('
  SELECT l_returnflag, sum(l_quantity)
  FROM lineitem
  WHERE l_shipdate >= DATE ''1996-01-01''
  GROUP BY l_returnflag
  ORDER BY l_returnflag
');

The summary row reports gpu_path: native, partial_native, cpu, or rejected. Candidate rows make the stable reason and remedy first-class columns; coverage_json on the summary retains projected candidate source-capability and cost evidence, plus runtime and configuration evidence. Flight SQL users can write EXPLAIN GPU <query> for the identical schema without escaping the query into a SQL literal. Read runtime_caveats too: admission, data-dependent memory, and device-side graph validation are execution-time contracts.