Polars 是一个用 Rust 编写的高性能 DataFrame 库，提供了一种快速、内存高效的替代 pandas 方案。 Polars 与 mssql-python 驱动结合使用后，您可以： 直接将SQL查询结果加载到Polars DataFrames中。 使用 Apache Arrow 进行从 Microsoft SQL 零复制的数据传输。 高效地将 Polars 数据帧写 ...

SPyQL 是一个命令行数据查询工具，用类 SQL 语法配合 Python 表达式，让你一句话就能完成 CSV 转 JSON、JSON 爆炸展开（EXPLODE）、导入 SQL 数据库 等数据格式转换任务。它高速且内存高效，GB 级数据也能流畅处理。本教程带你从零上手 SPyQL 数据格式转换，看完即可 ...

本教程介绍如何开发和部署您的第一个 ETL（提取、转换和加载）管道，以使用 Apache Spark 进行数据编排。 尽管本教程使用 Databricks 全用途计算，但如果为工作区启用了无服务器计算，也可以使用无服务器计算。 你也可以使用Lakeflow 管道构建 ETL 管道，它可管理 ...

An interactive dashboard showing how the United States has generated its electricity, month by month, from 2001 through the U.S. Energy Information Administration's (EIA) latest forecast, with an AI ...

A data engineering project demonstrating two approaches to building data pipelines: ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) using the Titanic dataset, Python, MySQL, and SQL.

You do most of your data work in Python and Spark: pipelines, training runs, feature-engineering scripts, batch jobs on a schedule. The code lives in a project on your laptop, in Git, with a ...

BigQuery ObjectRef is now GA. Combine unstructured data with Gemini to build powerful multimodal analytics and conversational agents using SQL.

Two things are true about Python: It’s the most popular programming language in the world, and it’s the most common companion language for Go developers. How do we know that? From the Developer ...

Learn how to pair DuckDB with AWS Glue 6.0 to run SQL-centric ETL on a single worker, reading Parquet from Amazon S3 and writing Apache Iceberg tables to Amazon S3 Tables. This post walks through a ...

Our team of talented Data Research Engineers works hand-in-hand with the QR teams to design the most insightful queries. In addition, they closely work with business operations and QRs in order to ...