apache / apache/parquet-java

Improve performance when filters in RowGroupFilter can match exactly

Abierto
#1,655 0 comentarios 0 reacciones 0 asignados Ver en GitHub
Component: Parquet Priority: Major Type: enhancement
Lenguaje dominante
Java
Estrellas
3.1k
Forks
1.6k
Merge medio
3 d 12 h
PR fusionados (30 d)
33

Descripción

If we can accurately judge by the minMax status, we don’t need to load the dictionary from filesystem and compare one by one anymore.

Similarly , Bloomfilter needs to load from filesystem, it may costs time and memory. If we can exactly determine the existence/nonexistence of the value from minMax or dictionary filters , then we can avoid using Bloomfilter to Improve performance.

For example,
1. read data greater than `x1` in the block, if minMax in status is all greater than `{}x1{`}, then we don't need to read dictionary and compare one by one.
1. If we already have page dictionaries and have compared one by one, we don't need to read BloomFilter and compare.

**Reporter**: [Mars](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=miracle) / @yabola
**Assignee**: [Mars](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=miracle) / @yabola

**Note**: *This issue was originally created as [PARQUET-2237](https://issues.apache.org/jira/browse/PARQUET-2237). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*

Guía de contribución

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Línea de trabajo

Start by locating RowGroupFilter and tracing how minMax, page dictionaries, and Bloomfilter are evaluated. Confirm how exact minMax or dictionary results can skip later filesystem reads, then verify the behavior and performance with the relevant existing checks; the issue names no files or tests, so those must be identified first.

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

Evaluación

Stack tecnológico
java
Área
data-engineering
Tipo de issue
Nueva funcionalidad
Dificultad
4/5
Tiempo estimado
3-5 días
Estado de actividad
Estancado
Claridad
Bastante claro
Aptitud para principiantes
35/100

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