December 2025
Beginner to intermediate
325 pages
4h 23m
Chinese
Content preview from 使用 Apache Sedona 进行云原生地理空间分析 (Chinese Edition)
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第9章. 使用Apache Sedona与Cloud数据提供商
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您可将 Apache Sedona 与不同云供应商提供的众多软件即服务（SaaS）和平台即服务（PaaS）产品结合使用。 本章重点介绍Sedona与主流供应商的集成方案，包括Databricks、AWS EMR与Glue、Microsoft Fabric、GCP Dataproc及Wherobots Cloud。本章侧重于不同系统环境下的Apache Sedona安装与使用方法，但可根据核心系统划分为三类：
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Apache Spark
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Apache Flink
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Snowflake（SedonaSnow）
本书已系统阐述Apache Sedona Spark的基础原理，因此针对基于Apache Spark的产品，我们将重点聚焦于安装流程。 同时提供SedonaSnow和Wherobots的示例及功能对比。若您使用的系统基于Apache Spark或Flink却未找到安装流程，请查阅Apache Sedona官方文档。若官方文档仍缺失安装指南，可向Apache Sedona代码库提交问题报告，或遵循您所用系统的官方文档。
前提条件
唯一不变的是变化。每个系统都会随着时间演进。为确保您使用与我们相同的版本，本章示例采用以下版本：
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Apache Spark 3.5.x
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Scala 2.12
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Python 3.11
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Apache Sedona 1.8.0
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GeoTools 33.1
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Apache Flink 1.19.1
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Databricks 运行时 16.4 LTS
若尚未安装，请先在 Spark 集群上部署 Apache Sedona。随后需向 Apache Spark 应用程序添加两个 jar 文件。首个 jar 文件包含为 Apache Spark 提供的所有地理空间扩展逻辑，例如 KNN、空间分区、GeoParquet 读取器等：
org.apache.sedona:sedona-spark-shaded-{SPARK_V}_{SCALA_V}:jar:{SEDONA_V}
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SPARK_V是您使用的 Spark主版本号和次版本号，例如 3.5。 -
SCALA_V是您使用的 Scala 的主版本号.次版本号，例如 2.12。 -
SEDONA_V是您使用的 Sedona 的主版本号.次版本号.补丁版本号，例如 1.8.0。
因此，针对Spark 3.5、Scala 2.12和Sedona 1.8.0环境的jar文件路径示例如下：
org.apache.sedona:sedona-spark-shaded-3.5_2.12:jar:1.8.0
Apache Sedona使用的GeoTools实现几何运算（如的intersects算法）。因许可限制，我们无法直接将其包含在源代码中。此外，Apache Sedona需要修改版的GeoTools，因此将其作为独立于官方GeoTools的Maven工件管理。您需额外提供的jar文件为：
org.datasyslab:geotools-wrapper:jar:{SEDONA_V}-{GEOTOOLS_V}
-
SEDONA_V是您使用的 Sedona 的主版本号.次版本号.补丁版本号，例如 1.8.0。 -
GEOTOOLS_V是所用 GeoTools 的主版本号.次版本号 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.