> ## Documentation Index
> Fetch the complete documentation index at: https://private-7c7dfe99-mintlify-fbfa8bee.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> Apache Spark 与 ClickHouse 简介

# 集成 Apache Spark 与 ClickHouse

export const ClickHouseSupportedBadge = () => {
  return <div className="ClickHouseSupportedBadge">
            <div className="ClickHouseSupportedIcon">
                <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
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                </svg>
            </div>
            支持 ClickHouse
        </div>;
};

[Apache Spark](https://spark.apache.org/) 是一个多语言引擎，可在单节点机器或集群上执行数据工程、数据科学和机器学习工作。

连接 Apache Spark 和 ClickHouse 主要有两种方式：

1. [Spark Connector](/zh/integrations/connectors/data-ingestion/apache-spark/spark-native-connector) - Spark Connector 实现了 `DataSourceV2`，并提供自己的 Catalog
   管理功能。目前，这是集成 ClickHouse 与 Spark 的推荐方式。
2. [Spark JDBC](/zh/integrations/connectors/data-ingestion/apache-spark/spark-jdbc) - 使用 [JDBC 数据源](https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html) 来集成 Spark 和 ClickHouse。

<br />

这两种方案都已成功通过测试，并与多种 API 完全兼容，包括 Java、Scala、PySpark 和 Spark SQL。

<div id="spark-runtime-environment">
  ### Spark 运行时环境
</div>

<div id="standard-spark-runtime">
  #### 标准 Spark 运行时环境
</div>

Spark Connector 可在与上游 Apache Spark 运行时高度一致的环境中直接使用，例如 Amazon EMR 或基于 Kubernetes 的 Spark 部署环境。

<div id="managed-spark-platforms">
  #### 托管 Spark 平台
</div>

[AWS Glue](/zh/integrations/connectors/data-ingestion/AWS/glue) 和 [Databricks](/zh/integrations/connectors/data-ingestion/apache-spark/databricks) 等平台会引入额外的抽象层以及特定环境下的行为差异。
虽然核心集成方式不变，但它们可能需要专门的配置和设置步骤。详情请参阅相应的文档页面。