spark如何读写ozone？请写出详细代码案例，并写出maven依赖

Spark可以通过Hadoop的FileSystem API来读写Ozone，具体实现如下：

import org.apache.hadoop.fs.FileSystem
import org.apache.hadoop.fs.Path
import org.apache.hadoop.ozone.client.OzoneClient
import org.apache.hadoop.ozone.client.OzoneClientFactory
import org.apache.hadoop.ozone.client.OzoneBucket
import org.apache.hadoop.ozone.client.io.OzoneOutputStream
import org.apache.spark.rdd.RDD
import org.apache.spark.sql._
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types._

object SparkOzoneExample {
  def main(args: Array[String]): Unit = {

    // 初始化Ozone客户端
    val ozoneClient: OzoneClient = OzoneClientFactory.getClient
    val bucket: OzoneBucket = ozoneClient.getObjectStore.createBucket("mybucket")
    val volume: String = bucket.getVolumeName
    val bucketName: String = bucket.getName

    // 初始化SparkSession
    val spark = SparkSession.builder()
      .appName("SparkOzoneExample")
      .master("local[*]")
      .getOrCreate()

    // 读取Ozone中的文件
    val fileSystem: FileSystem = FileSystem.get(spark.sparkContext.hadoopConfiguration)
    val path: Path = new Path(s"o3://${volume}.${bucketName}/myFile")
    val file: RDD[String] = spark.sparkContext.textFile(path.toString)

    // 处理数据
    val data: DataFrame = spark.read.json(file)
    val result: DataFrame = data.groupBy("category").agg(sum("value"))

    // 写入Ozone中的文件
    val ozoneOutput: OzoneOutputStream = bucket.createKey("outputFile")
    result.write.json(ozoneOutput)
    ozoneOutput.close()

    // 关闭Ozone客户端
    ozoneClient.close()
  }
}

这里我们首先初始化了一个Ozone客户端，并创建了一个名为`mybucket`的桶。然后，我们使用Spark来读取Ozone中的文件，并对数据进行处理。最后，我们将处理结果写回到Ozone中的一个名为`outputFile`的文件中。

下面是pom.xml文件中需要添加的Maven依赖：

<dependency>
  <groupId>org.apache.hadoop</groupId>
  <artifactId>hadoop-ozone-client</artifactId>
  <version>0.5.0</version>
</dependency>
<dependency>
  <groupId>org.apache.hadoop</groupId>
  <artifactId>hadoop-common</artifactId>
  <version>3.2.0</version>
</dependency>
<dependency>
  <groupId>org.apache.hadoop</groupId>
  <artifactId>hadoop-hdfs</artifactId>
  <version>3.2.0</version>
</dependency>
<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-core_2.12</artifactId>
  <version>3.1.2</version>
</dependency>
<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-sql_2.12</artifactId>
  <version>3.1.2</version>
</dependency>