Crate parquet

This crate contains the official Native Rust implementation of Apache Parquet, part of the Apache Arrow project. The crate provides a number of APIs to read and write Parquet files, covering a range of use cases.

Please see the parquet crates.io page for feature flags and tips to improve performance.

Format Overview

Parquet is a columnar format, which means that unlike row formats like CSV, values are iterated along columns instead of rows. Parquet is similar in spirit to Arrow, but focuses on storage efficiency whereas Arrow prioritizes compute efficiency.

Parquet files are partitioned for scalability. Each file contains metadata, along with zero or more “row groups”, each row group containing one or more columns. The APIs in this crate reflect this structure.

Data in Parquet files is strongly typed and differentiates between logical and physical types (see schema). In addition, Parquet files may contain other metadata, such as statistics, which can be used to optimize reading (see file::metadata). For more details about the Parquet format itself, see the Parquet spec

APIs

This crate exposes a number of APIs for different use-cases.

Metadata and Schema

The schema module provides APIs to work with Parquet schemas. The file::metadata module provides APIs to work with Parquet metadata.

Reading and Writing Arrow (arrow feature)

The arrow module supports reading and writing Parquet data to/from Arrow RecordBatches. Using Arrow is simple and performant, and allows workloads to leverage the wide range of data transforms provided by the arrow crate, and by the ecosystem of Arrow compatible systems.

Most users will use ArrowWriter for writing and ParquetRecordBatchReaderBuilder for reading.

Lower level APIs include ArrowColumnWriter for writing using multiple threads, and RowFilter to apply filters during decode.

async Reading and Writing Arrow (async feature)

The async_reader and async_writer modules provide async APIs to read and write RecordBatches asynchronously.

Most users will use AsyncArrowWriter for writing and ParquetRecordBatchStreamBuilder for reading. When the object_store feature is enabled, ParquetObjectReader provides efficient integration with object storage services such as S3 via the object_store crate, automatically optimizing IO based on any predicates or projections provided.

Read/Write Parquet Directly

Workloads needing finer-grained control, or to avoid a dependence on arrow, can use the APIs in file directly. These APIs are harder to use as they directly use the underlying Parquet data model, and require knowledge of the Parquet format, including the details of Dremel record shredding and Logical Types.

Modules

arrow

API for reading/writing Arrow RecordBatches and Arrays to/from Parquet Files.

basic

Contains Rust mappings for Thrift definition. Refer to parquet.thrift file to see raw definitions.

bloom_filter

Bloom filter implementation specific to Parquet, as described in the spec.

column

Low level column reader and writer APIs.

data_type

Data types that connect Parquet physical types with their Rust-specific representations.

errors

Common Parquet errors and macros.

file

APIs for reading parquet data.

format

Automatically generated code from the Parquet thrift definition.

record

Contains record-based API for reading Parquet files.

schema

Parquet schema definitions and methods to print and parse schema.

thrift

Custom thrift definitions

utf8

check_valid_utf8 validation function