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Implement more efficient oneof in-memory structure

Abierto
#72 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
30/100
Tipo de issue
Refactorización
Claridad
Necesita aclaración
Estado de actividad
Estancado
Stack tecnológico
go

Línea de trabajo

Start with the PointValue oneof representation and the SerializeNative, SerializeFromPdata, and related benchmarks shown in the issue. Compare possible approaches with govariant, then verify that the structure uses less memory without regressing serialization performance or behavior.

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

Descripción

Sorted convertors from pdata keep the data points in memory. This results in large number of PointValue oneof structs in-mem. oneof is currently implemented as a plain struct instead of an aliased union, which results in large memory consumption and slowdown in operation with the increase in number of oneof choices. This is for example what we observe when we add ExpHistogramValue to PointValue (without even having a single data point with ExpHistogramValue present in the dataset):

                                │   old.txt   │               new.txt               │
                                │   sec/op    │   sec/op     vs base                │
SerializeNative/STEF/none-10      3.752m ± 2%   4.356m ± 5%  +16.12% (p=0.000 n=10)
DeserializeNative/STEF/none-10    1.710m ± 0%   1.698m ± 0%   -0.68% (p=0.003 n=10)
SerializeFromPdata/STEF/none-10   87.02m ± 1%   90.25m ± 1%   +3.72% (p=0.001 n=10)
DeserializeToPdata/STEF/none-10   22.16m ± 1%   22.03m ± 1%        ~ (p=0.393 n=10)
geomean                           10.55m        11.01m        +4.43%

                                │   old.txt   │               new.txt               │
                                │  sec/point  │  sec/point   vs base                │
SerializeNative/STEF/none-10      56.12n ± 2%   65.16n ± 5%  +16.12% (p=0.000 n=10)
DeserializeNative/STEF/none-10    25.57n ± 0%   25.41n ± 0%   -0.66% (p=0.002 n=10)
SerializeFromPdata/STEF/none-10   1.302µ ± 1%   1.349µ ± 1%   +3.69% (p=0.001 n=10)
DeserializeToPdata/STEF/none-10   331.4n ± 1%   329.4n ± 1%        ~ (p=0.382 n=10)
geomean                           157.7n        164.7n        +4.42%

                                │   old.txt    │               new.txt                │
                                │     B/op     │     B/op      vs base                │
SerializeNative/STEF/none-10      3.521Mi ± 0%   3.515Mi ± 0%   -0.19% (p=0.000 n=10)
DeserializeNative/STEF/none-10    836.2Ki ± 0%   839.4Ki ± 0%   +0.38% (p=0.000 n=10)
SerializeFromPdata/STEF/none-10   124.6Mi ± 0%   141.2Mi ± 0%  +13.34% (p=0.000 n=10)
DeserializeToPdata/STEF/none-10   29.81Mi ± 0%   29.81Mi ± 0%   +0.01% (p=0.000 n=10)
geomean                           10.17Mi        10.50Mi        +3.23%

                                │   old.txt   │              new.txt               │
                                │  allocs/op  │  allocs/op   vs base               │
SerializeNative/STEF/none-10      2.773k ± 0%   2.802k ± 0%  +1.05% (p=0.000 n=10)
DeserializeNative/STEF/none-10    1.230k ± 0%   1.261k ± 0%  +2.52% (p=0.000 n=10)
SerializeFromPdata/STEF/none-10   256.3k ± 0%   256.3k ± 0%       ~ (p=0.100 n=10)
DeserializeToPdata/STEF/none-10   623.3k ± 0%   623.3k ± 0%  +0.00% (p=0.000 n=10)
geomean                           27.17k        27.41k       +0.89%

I confirmed that increase in serilization time is purely because of the increase of the size of the PointValue in-mem structure.

See if we can get inspiration from https://github.com/tigrannajaryan/govariant

Lenguaje dominante
Java
Estrellas
11
Forks
6
Merge medio
55 min
PR fusionados (30 d)
1

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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