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Principle:Apache Paimon Predicate and Projection Filtering

From Leeroopedia


Knowledge Sources
Domains Data_Lake, Distributed_Computing
Last Updated 2026-02-07 00:00 GMT

Overview

Mechanism for reducing data volume through row-level filtering (predicates) and column-level selection (projections) before distributed processing.

Description

Predicate and projection filtering optimizes distributed data processing by pushing filter conditions and column selections down to the storage layer. PredicateBuilder constructs typed filter conditions (equality, comparison, range, membership) that are evaluated at the file and partition level during scan planning. Column projection restricts which columns are read from storage, reducing I/O and memory usage. These optimizations are especially impactful in distributed settings where reducing data transfer between nodes is critical for performance.

Key capabilities include:

  • Row-level predicates: equality, comparison, range, membership, null checks, and string pattern matching
  • Logical combinators: AND and OR composition of multiple predicates
  • Column projection: restrict output to only the needed columns
  • Pushdown optimization: filters applied at scan planning time, before data leaves storage

Usage

Use this principle whenever reading from large tables with known filter conditions or when only a subset of columns is needed. Apply before creating distributed datasets to minimize network transfer.

Theoretical Basis

Predicate pushdown leverages manifest-level statistics (min/max per column per file) to skip entire files. Column projection avoids reading unnecessary columns from columnar file formats. Together they implement the selection and projection operators from relational algebra at the physical storage level.

The optimization hierarchy is:

  1. Partition pruning - eliminates entire partitions based on partition key predicates
  2. File pruning - skips files whose column statistics (min/max) exclude all matching rows
  3. Column pruning - reads only required columns from the columnar format (ORC/Parquet)
  4. Row filtering - applies remaining predicates on materialized rows

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