跳至主要内容

将 Amazon Glue 与 ClickHouse 集成

Amazon Glue 是由 Amazon Web Services (AWS) 提供的完全托管的无服务器数据集成服务。它简化了发现、准备和转换数据以供分析、机器学习和应用程序开发的过程。

虽然目前还没有 Glue ClickHouse 连接器,但可以使用官方 JDBC 连接器连接并与 ClickHouse 集成。

import com.amazonaws.services.glue.util.Job
import com.amazonaws.services.glue.util.GlueArgParser
import com.amazonaws.services.glue.GlueContext
import org.apache.spark.SparkContext
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.DataFrame
import scala.collection.JavaConverters._
import com.amazonaws.services.glue.log.GlueLogger


// Initialize Glue job
object GlueJob {
def main(sysArgs: Array[String]) {
val sc: SparkContext = new SparkContext()
val glueContext: GlueContext = new GlueContext(sc)
val spark: SparkSession = glueContext.getSparkSession
val logger = new GlueLogger
import spark.implicits._
// @params: [JOB_NAME]
val args = GlueArgParser.getResolvedOptions(sysArgs, Seq("JOB_NAME").toArray)
Job.init(args("JOB_NAME"), glueContext, args.asJava)

// JDBC connection details
val jdbcUrl = "jdbc:ch://{host}:{port}/{schema}"
val jdbcProperties = new java.util.Properties()
jdbcProperties.put("user", "default")
jdbcProperties.put("password", "*******")
jdbcProperties.put("driver", "com.clickhouse.jdbc.ClickHouseDriver")

// Load the table from ClickHouse
val df: DataFrame = spark.read.jdbc(jdbcUrl, "my_table", jdbcProperties)

// Show the Spark df, or use it for whatever you like
df.show()

// Commit the job
Job.commit()
}
}

有关更多详细信息,请访问我们的 Spark 和 JDBC 文档