Native tuple sketch functions (tuple_*, Spark 4.2): audit the crate against Java and implement

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
12/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
java, rust, scala, spark
Área
data-engineering

Línea de trabajo

This is a multi-part audit and implementation across the Rust tuple feature of the datasketches crate and Comet's Spark expression support, so it is not a starting point. Begin with the Spark 4.2 tuple function definitions and the existing theta sketch expressions in the Comet source, then compare the crate's summary types and union/intersection policies against DataSketches-Java 6.2.0 fixtures. Done means each tuple_* function runs natively with a Spark fallback before 4.2, backed by committed fixtures and tests.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

area:aggregation area:expressions enhancement

What is the problem the feature request solves?

Part of #7397.

Spark 4.2 adds Tuple sketch functions: tuple_sketch_agg, tuple_union_agg, tuple_intersection_agg, the tuple_difference / tuple_union / tuple_intersection scalars, and tuple_sketch_estimate, tuple_sketch_summary and tuple_sketch_theta, each in integer and double summary variants. None of them run natively in Comet. The crate's tuple feature arrived in datasketches 0.4.0.

Describe the potential solution

  1. Score the family with suggest-native-expression first. This is the lowest priority of the four, because it only exists in the newest Spark version Comet supports.
  2. Do the theta work first, since a tuple sketch is a theta sketch with a summary attached and shares its hashing and set-operation behavior.
  3. Audit the crate's tuple feature against DataSketches-Java 6.2.0 using committed fixtures. The summary types and the policies that combine summaries on union and intersection need to match Spark's exactly, and the serialized summary format has to be readable in both directions.
  4. Implement, test and document as for the other families, with a fallback on Spark versions before 4.2.
Lenguaje dominante
Scala
Estrellas
1.3k
Forks
414
Merge medio
3 d 5 h
PR fusionados (30 d)
210

Preparar el entorno

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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