跳转至
🎉 Apache Sedona 1.9.1 已正式发布!🗺️ 新增 Geography SQL 函数、Box2D 与 Box3D 类型、栅格 Python UDF 等。查看发布说明 →

Blog

Should You Use H3 for Geospatial Analytics? A Deep Dive with Apache Spark and Sedona

TL;DR The H3 spatial index provides a number of spatial functions and a consistent grid system for efficient data aggregation and visualization. H3 is an approximation that makes some computations run faster, but less accurately. Sedona supports H3 spatial index, but it's often preferable to use precise computations, especially when accuracy is important.

Welcome to the Apache Sedona Blog!

Welcome to the brand-new blog for Apache Sedona!

For several years, Apache Sedona has been the go-to open-source engine for processing massive geospatial datasets, extending Apache Spark to handle complex spatial operations with unparalleled speed and efficiency. Sedona's capabilities also extend beyond Spark, bringing spatial analytics to the Snowflake data warehouse with SedonaSnow and the real-time streaming engine Apache Flink with a Spatial SQL integration.