Pyarrow read parquet file. Once PyArrow is installed, we can use its parquet module to read parquet files. Oct 25, 2024 · It’s widely used for reading and writing Parquet files and works seamlessly with other Arrow libraries. . To read a flat column as dictionary-encoded pass the column name. Jul 13, 2017 · We must add some code to allow pyarrow to recognize the s3fs filesystem and add a shim / compatibility class to conform S3FS's slightly different filesystem API to pyarrow's. If given, Parquet binary columns will be read as this datatype. Sep 28, 2023 · One effective strategy to handle these challenges is to read and write Parquet files in smaller chunks using the PyArrow library. The parquet module provides a ParquetFile class that allows us to read metadata from a parquet file and access its individual columns. level2. Below is the code for the same: import fastparquet as fp. The choice between them depends on specific requirements: pyarrow: Offers a comprehensive set of features and is part of the broader Apache Arrow ecosystem. Let’s walk through how to use PyArrow to read and write Parquet files. We have been concurrently developing the C++ implementation of Apache Parquet, which includes a native, multithreaded C++ adapter to and from in-memory Arrow data. In this blog, we’ll explore the advantages of reading and writing Parquet files in chunks and provide a comprehensive guide on how to achieve this using PyArrow. Apache Arrow is an ideal in-memory transport layer for data that is being read or written with Parquet files. Feb 7, 2025 · Both pyarrow and fastparquet are great for handling Parquet files in Python. item. For nested types, you must pass the full column “path”, which could be something like level1. Refer to the Parquet file’s schema to obtain the paths. list. It is suitable for complex data processing tasks. I managed to get this working with the latest release of fastparquet & s3fs. ghwr ggi wzbn tfa dojtcm owfi eatigrh ugunf xhrcwlu tpxd