java使用使用hudi-spark-client创建hudi表并写数据到hudi表中

在Java中使用Hudi的Spark客户端创建Hudi表并写入数据，你可以按照以下步骤进行操作：

1. 首先，确保你已经在项目中添加了Hudi和Spark依赖。你可以在pom.xml文件中添加以下依赖项：

<dependencies>
    <!-- Hudi -->
    <dependency>
        <groupId>org.apache.hudi</groupId>
        <artifactId>hudi-spark-bundle_2.12</artifactId>
        <version>0.9.0</version>
    </dependency>

    <!-- Spark -->
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.12</artifactId>
        <version>3.1.1</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.12</artifactId>
        <version>3.1.1</version>
    </dependency>
</dependencies>

2. 在Java中创建SparkSession对象：

import org.apache.spark.sql.SparkSession;

SparkSession spark = SparkSession.builder()
    .appName("HudiExample")
    .master("local[*]")  // 根据实际运行环境设置
    .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
    .getOrCreate();

3. 创建Hudi表，指定表名、表类型（如COPY_ON_WRITE或MERGE_ON_READ）、键名和分区列：

import org.apache.hudi.DataSourceWriteOptions;
import org.apache.hudi.HoodieDataSourceHelpers;
import org.apache.hudi.config.HoodieWriteConfig;

String tableName = "my_hudi_table";
String basePath = "/path/to/hudi_table";
String primaryKey = "id";
String partitionColumn = "date";

HoodieWriteConfig writeConfig = HoodieWriteConfig.newBuilder().withPath(basePath)
    .withSchema(HoodieDataSourceHelpers.createHoodieWriteSchema(schema))  // 设置数据模式
    .withParallelism(2, 2)  // 设置并行度
    .forTable(tableName)
    .withIndexConfig(HoodieIndexConfig.newBuilder().withIndexType(HoodieIndex.IndexType.BLOOM).build())  // 设置索引类型为Bloom
    .withCompactionConfig(HoodieCompactionConfig.newBuilder().archiveCommitsWith(30, TimeUnit.SECONDS).build())  // 设置30s内自动归档
    .build();

HoodieSparkEngineContext context = new HoodieSparkEngineContext(spark.sparkContext());
HoodieTableMetaClient metaClient = HoodieTableMetaClient.builder().setConf(spark.sparkContext().hadoopConfiguration())
    .setBasePath(basePath)
    .setLoadActiveTimelineOnLoad(true)
    .build();

HoodieTable table = HoodieSparkTable.create(writeConfig, context, metaClient);

4. 将数据写入Hudi表：

import org.apache.hudi.common.model.HoodieRecord;

// 创建要写入的数据集
List<HoodieRecord> records = Arrays.asList(
    new HoodieRecord(new HoodieKey("1", "2021-01-01"), data1),
    new HoodieRecord(new HoodieKey("2", "2021-01-02"), data2),
    new HoodieRecord(new HoodieKey("3", "2021-01-03"), data3)
);

JavaRDD<HoodieRecord> recordRDD = JavaSparkContext.fromSparkContext(spark.sparkContext()).parallelize(records);
String commitTime = HoodieTestUtils.makeNewCommitTime();
HoodieWriteClient<HoodieRecord> writeClient = new HoodieWriteClient<>(context, writeConfig);

writeClient.startCommit(commitTime);
writeClient.insert(recordRDD, commitTime);
writeClient.commit(commitTime, recordRDD);

以上是使用Hudi Spark客户端在Java中创建Hudi表并写入数据的基本步骤。请根据你的实际情况进行调整和扩展。