Java API操作Hdfs的示例详解
目录
- 1.遍历当前目录下所有文件与文件夹
- 2.遍历所有文件
- 3.创建文件夹
- 4.删除文件夹
- 5.上传文件
- 6.下载文件
1.遍历当前目录下所有文件与文件夹
可以使用listStatus方法实现上述需求。
listStatus方法签名如下
/** * List the statuses of the files/directories in the given path if the path is * a directory. * * @param f given path * @return the statuses of the files/directories in the given patch * @throws FileNotFoundException when the path does not exist; * IOException see specific implementation */ public abstract FileStatus[] listStatus(Path f) throws FileNotFoundException, IOException;
可以看出listStatus只需要传入参数Path即可,返回的是一个FileStatus的数组。
而FileStatus包含有以下信息
/** Interface that represents the client side information for a file. */ @InterfaceAudience.Public @InterfaceStability.Stable public class FileStatus implements Writable, Comparable { private Path path; private long length; private boolean isdir; private short block_replication; private long blocksize; private long modification_time; private long access_time; private FsPermission permission; private String owner; private String group; private Path symlink; ....
从FileStatus中不难看出,包含有文件路径,大小,是否是目录,block_replication, blocksize…等等各种信息。
import org.apache.hadoop.fs.{FileStatus, FileSystem, Path} import org.apache.spark.sql.SparkSession import org.apache.spark.{SparkConf, SparkContext} import org.slf4j.LoggerFactory object HdfsOperation { val logger = LoggerFactory.getLogger(this.getClass) def tree(sc: SparkContext, path: String) : Unit = { val fs = FileSystem.get(sc.hadoopConfiguration) val fsPath = new Path(path) val status = fs.listStatus(fsPath) for(filestatus:FileStatus <- status) { logger.error("getPermission is: {}", filestatus.getPermission) logger.error("getOwner is: {}", filestatus.getOwner) logger.error("getGroup is: {}", filestatus.getGroup) logger.error("getLen is: {}", filestatus.getLen) logger.error("getModificationTime is: {}", filestatus.getModificationTime) logger.error("getReplication is: {}", filestatus.getReplication) logger.error("getBlockSize is: {}", filestatus.getBlockSize) if (filestatus.isDirectory) { val dirpath = filestatus.getPath.toString logger.error("文件夹名字为: {}", dirpath) tree(sc, dirpath) } else { val fullname = filestatus.getPath.toString val filename = filestatus.getPath.getName logger.error("全部文件名为: {}", fullname) logger.error("文件名为: {}", filename) } } } }
如果判断fileStatus是文件夹,则递归调用tree方法,达到全部遍历的目的。
2.遍历所有文件
上面的方法是遍历所有文件以及文件夹。如果只想遍历文件,可以使用listFiles方法。
def findFiles(sc: SparkContext, path: String) = { val fs = FileSystem.get(sc.hadoopConfiguration) val fsPath = new Path(path) val files = fs.listFiles(fsPath, true) while(files.hasNext) { val filestatus = files.next() val fullname = filestatus.getPath.toString val filename = filestatus.getPath.getName logger.error("全部文件名为: {}", fullname) logger.error("文件名为: {}", filename) logger.error("文件大小为: {}", filestatus.getLen) } }
/** * List the statuses and block locations of the files in the given path. * * If the path is a directory, * if recursive is false, returns files in the directory; * if recursive is true, return files in the subtree rooted at the path. * If the path is a file, return the file's status and block locations. * * @param f is the path * @param recursive if the subdirectories need to be traversed recursively * * @return an iterator that traverses statuses of the files * * @throws FileNotFoundException when the path does not exist; * IOException see specific implementation */ public RemoteIterator<LocatedFileStatus> listFiles( final Path f, final boolean recursive) throws FileNotFoundException, IOException { ...
从源码可以看出,listFiles 返回一个可迭代的对象RemoteIterator<LocatedFileStatus>
,而listStatus返回的是个数组。同时,listFiles返回的都是文件。
3.创建文件夹
def mkdirToHdfs(sc: SparkContext, path: String) = { val fs = FileSystem.get(sc.hadoopConfiguration) val result = fs.mkdirs(new Path(path)) if (result) { logger.error("mkdirs already success!") } else { logger.error("mkdirs had failed!") } }
4.删除文件夹
def deleteOnHdfs(sc: SparkContext, path: String) = { val fs = FileSystem.get(sc.hadoopConfiguration) val result = fs.delete(new Path(path), true) if (result) { logger.error("delete already success!") } else { logger.error("delete had failed!") } }
5.上传文件
def uploadToHdfs(sc: SparkContext, localPath: String, hdfsPath: String): Unit = { val fs = FileSystem.get(sc.hadoopConfiguration) fs.copyFromLocalFile(new Path(localPath), new Path(hdfsPath)) fs.close() }
6.下载文件
def downloadFromHdfs(sc: SparkContext, localPath: String, hdfsPath: String) = { val fs = FileSystem.get(sc.hadoopConfiguration) fs.copyToLocalFile(new Path(hdfsPath), new Path(localPath)) fs.close() }
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