当前位置：首页 > news >正文

Mysql入湖Iceberg

news 2026/5/12 15:26:42

Mysql入湖Iceberg

使用Scala实现Spark高可用集群读取Mysql数据写入Iceberg数据湖，数据存储于Hadoop高可用集群

Spark 3.3.3
Hadoop 3.3.6
Iceberg 1.3.0

代码

packagecom.czl.datalake.template.iceberg.mysqlimportorg.apache.spark.sql.SparkSessionobjectTest{defmain(args:Array[String]):Unit={//windows环境测试需要配置// System.setProperty("hadoop.home.dir", "D://hadoop3.3.0")// System.setProperty("HADOOP_USER_NAME", "czl")valspark=SparkSession.builder().appName("mysqlToIceberg").config("spark.sql.catalog.czlCatalog","org.apache.iceberg.spark.SparkCatalog").config("spark.sql.catalog.czlCatalog.type","hadoop")//hadoop文件系统路径.config("spark.sql.catalog.czlCatalog.warehouse","/data").getOrCreate()try{// 1. 读取MySQL数据valmysqlDF=spark.read.format("jdbc").option("url","jdbc:mysql://10.10.10.10:6033").option("driver","com.mysql.cj.jdbc.Driver").option("user","root").option("password","root")//库名.表名.option("dbtable","testDb.testTable").load()//写入Iceberg表mysqlDF.write.format("iceberg")//存储在hadoop上的，库名.表名.save("czlCatalog.testDb.testTable")}catch{casee:Exception=>e.printStackTrace()}finally{spark.stop()}}}

依赖参考

<?xml version="1.0" encoding="UTF-8"?><projectxmlns="http://maven.apache.org/POM/4.0.0"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"><parent><artifactId>dataLake-template-iceberg</artifactId><groupId>com.czl</groupId><version>1.0</version></parent><modelVersion>4.0.0</modelVersion><artifactId>dataLake-template-iceberg-spark-mysql</artifactId><properties><maven.compiler.source>8</maven.compiler.source><maven.compiler.target>8</maven.compiler.target></properties><dependencies><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>8.0.24</version></dependency><dependency><groupId>org.apache.spark</groupId><artifactId>spark-sql_2.12</artifactId><version>3.3.3</version></dependency><dependency><groupId>org.apache.iceberg</groupId><artifactId>iceberg-spark-runtime-3.3_2.12</artifactId><version>1.3.0</version></dependency></dependencies><build><plugins><plugin><groupId>org.scala-tools</groupId><artifactId>maven-scala-plugin</artifactId><version>2.15.2</version><executions><execution><goals><!--编译源码--><goal>compile</goal><!--编译测试源码--><goal>testCompile</goal></goals></execution></executions></plugin></plugins></build></project>

提示

core-site.xml,hdfs-site.xml文件放置在resources文件夹下，以便于识别到Hadoop集群
Spark高可用集群，每个节点上传mysql-connector-java-8.0.33.jar和iceberg-spark-runtime-3.3_2.12-1.3.0.jar这两个必须使用的依赖。

本地模式提交

./spark-submit --master local[*]--class com.czl.datalake.template.iceberg.mysql.Test /opt/dataLake-template-iceberg-spark-mysql-1.0.jar

集群模式提交，jar在本地

./spark-submit --master spark://node1:7077 --deploy-mode cluster --class com.czl.datalake.template.iceberg.mysql.Test /opt/dataLake-template-iceberg-spark-mysql-1.0.jar

集群模式提交，jar在Hadoop

./spark-submit --master spark://node1:7077 --deploy-mode cluster --class com.czl.datalake.template.iceberg.mysql.Test hdfs://ling//workspace/project/dataLake-template-iceberg-spark-mysql-1.0.jar

Yarn模式提交，jar在Hadoop

./spark-submit --masteryarn--deploy-mode cluster --class com.czl.datalake.template.iceberg.mysql.Test hdfs://ling//workspace/project/dataLake-template-iceberg-spark-mysql-1.0.jar

查看全文

http://www.jsqmd.com/news/99578/