python 读取parquet format 文心快码BaiduComate 在Python中读取Parquet格式的文件,通常可以使用pandas库或者pyarrow库。以下是一个详细的步骤说明,包含代码片段: 导入必要的Python库: 为了读取Parquet文件,你需要导入pandas库。如果Parquet文件是使用pyarrow或fastparquet引擎存储的,你可能还需要安装并导入这些库。不过,pandas...
https://arrow.apache.org/docs/python/parquet.html 回到顶部(Back to Top) 原理分析:Parquet文件格式( File Format) 文件格式: Block(HDFS块):指的是HDFS中的一个块,对于描述这种文件格式,其含义不变。该文件格式设计得能够在HDFS上良好运作。 文件(File):一个必须包含文件元数据的HDFS文件。实际上,它不需...
Parquet文件格式( File Format) 详细的文件格式参考文档:parquet.apache.org/docs Block(HDFS块):指的是HDFS中的一个块,对于描述这种文件格式,其含义不变。该文件格式设计得能够在HDFS上良好运作。 文件(File):一个必须包含文件元数据的HDFS文件。实际上,它不需要包含数据本身。 行组(Row group):数据在行方向的逻...
[pandas.read_parquet() - pandas官方文档]( [What is Parquet File Format? - Apache Parquet官方文档](
importpandasaspd# 读取Parquet文件defread_parquet_file(file_path):# 使用pandas的read_parquet方法读取文件df=pd.read_parquet(file_path)returndf# 示例调用file_path='data/example.parquet'data_frame=read_parquet_file(file_path)# 显示数据的前5行print(data_frame.head()) ...
<pyarrow._parquet.FileMetaData object at 0x145220990> created_by: parquet-cpp-arrow version 6.0.1 num_columns: 10 num_rows: 40000 num_row_groups: 1 format_version: 1.0 serialized_size: 5979 统计当前文件下parquet文件数据总行数 from pathlib import Path import pyarrow.parquet as pq file = Pa...
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.inferSchema(ParquetFileFormat.scala:241) at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:202) at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:...
[3] Wes McKinney, Extreme IO performance with parallel Apache Parquet in Python (2017) [4] Michael Berk, Demystifying the Parquet File Format (2022) [5] fastparquet源代码GitHub仓库原文标题:I spent 8 hours learning Parquet. Here’s whatI discovered ...
fastparquet is a python implementation of theparquet format, aiming integrate into python-based big data work-flows. It is used implicitly by the projects Dask, Pandas and intake-parquet. We offer a high degree of support for the features of the parquet format, and very competitive performance,...
:param filepath: target file location for parquet file. :param writer: ParquetWriter object to write pyarrow tables in parquet format. :return: ParquetWriter object. This can be passed in the subsequenct method calls to append DataFrame