Hadoop官網翻譯之HDFS Users Guide

xiaoliuyiting發表於2019-01-01

原文：https://www.cnblogs.com/wcwen1990/p/6727397.html

HDFS Users Guide

Purpose

This document is a starting point for users working with Hadoop Distributed File System (HDFS) either as a part of a Hadoop cluster or as a stand-alone general purpose distributed file system. While HDFS is designed to “just work” in many environments, a working knowledge of HDFS helps greatly with configuration improvements and diagnostics on a specific cluster.

目的

本文件對於使用HDFS的使用者來說是一個起點，不管是作為Hadoop叢集的一部分還是一個獨立的通用的分散式檔案系統。雖然HDFS被設計在很多環境下工作，但是HDFS工作原理的支援將極大的幫助配置的調高和特定叢集的故障檢測。

Overview

HDFS is the primary distributed storage used by Hadoop applications. A HDFS cluster primarily consists of a NameNode that manages the file system metadata and DataNodes that store the actual data. The HDFS Architecture Guide describes HDFS in detail. This user guide primarily deals with the interaction of users and administrators with HDFS clusters. The HDFS architecture diagram depicts basic interactions among NameNode, the DataNodes, and the clients. Clients contact NameNode for file metadata or file modifications and perform actual file I/O directly with the DataNodes.

概覽

HDFS是Hadoop應用程式使用的主要的分散式儲存系統。一個HDFS叢集主要包括一個NameNode和多個DataNode，NameNode管理檔案系統後設資料，DataNode儲存真正的資料。HDFS的架構指南詳細地描述了HDFS。本使用者指南主要講述使用者和管理員與HDFS系統的互動。HDFS架構圖描繪了NameNode，DataNode和client之間的基本的互動。Client連線NameNode取得檔案後設資料或者檔案修改資訊，然後直接與DataNode執行真正的檔案I/O操作。

The following are some of the salient features that could be of interest to many users.

下面是一些可能引起很多使用者興趣的特性：

Hadoop, including HDFS, is well suited for distributed storage and distributed processing using commodity hardware. It is fault tolerant, scalable, and extremely simple to expand. MapReduce, well known for its simplicity and applicability for large set of distributed applications, is an integral part of Hadoop.
Hadoop，包括HDFS，非常適合用標準硬體進行分散式儲存和分散式處理。它具有容錯，可伸縮和及其簡單的擴容等特性。因其對於大量的分散式應用程式的簡單和高適用性而出名的MapReduce是Hadoop的一部分
HDFS is highly configurable with a default configuration well suited for many installations. Most of the time, configuration needs to be tuned only for very large clusters.
HDFS的預設配置適合大部分裝置。大多數情況下，配置只在非常大的叢集中時需要調優
Hadoop is written in Java and is supported on all major platforms.
Hadoop用java編寫，支援所有主流的平臺。
Hadoop supports shell-like commands to interact with HDFS directly.
Hadoop支援類shell的命令來與HDFS直接互動
The NameNode and Datanodes have built in web servers that makes it easy to check current status of the cluster.
NameNode和DataNode內建了web伺服器，使其更容易的檢查叢集當前的狀態。
New features and improvements are regularly implemented in HDFS. The following is a subset of useful features in HDFS:

新的特性和改進通常實現在HDFS中，下面是HDFS中的部分有用的特性：
- File permissions and authentication.
檔案許可權和認證
- Rack awareness: to take a node’s physical location into account while scheduling tasks and allocating storage.
機架感知：在排程任務和申請儲存的時候考慮到節點的物理位置
- Safemode: an administrative mode for maintenance.
安全模式：維護時的管理模式
- fsck: a utility to diagnose health of the file system, to find missing files or blocks.
fsck：一個檢測叢集檔案系統健康狀況的工具，可以找出丟失的檔案和Block。
- fetchdt: a utility to fetch DelegationToken and store it in a file on the local system.
fetchdt：一個獲取DelegationToken，然後儲存到本地檔案系統的工具。
- Balancer: tool to balance the cluster when the data is unevenly distributed among DataNodes.
Balancer：當資料不平均的分佈在DataNode時平衡叢集資料的工具。
- Upgrade and rollback: after a software upgrade, it is possible to rollback to HDFS’ state before the upgrade in case of unexpected problems.
Upgrade和rollback：在軟體升級之後，再遇到不可預測的問題的情況下，回滾回HDFS升級之前的狀態是可以的。
- Secondary NameNode: performs periodic checkpoints of the namespace and helps keep the size of file containing log of HDFS modifications within certain limits at the NameNode.
Secondary NameNode：週期性地執行namespace的檢查點，幫助保持NameNode中儲存HDFS的修改日誌的檔案的大小不超過某個範圍。
- Checkpoint node: performs periodic checkpoints of the namespace and helps minimize the size of the log stored at the NameNode containing changes to the HDFS. Replaces the role previously filled by the Secondary NameNode, though is not yet battle hardened. The NameNode allows multiple Checkpoint nodes simultaneously, as long as there are no Backup nodes registered with the system.
Checkpoint Node：週期性地執行namespace的檢查點操作，幫助減少儲存在NameNode的包含HDFS變化的日誌的大小。取代之前Secondary NameNode的角色，儘管還不是必須的。NameNode允許同時存在多個Checkpoint節點，只要系統中沒有BackUp節點的存在。
- Backup node: An extension to the Checkpoint node. In addition to checkpointing it also receives a stream of edits from the NameNode and maintains its own in-memory copy of the namespace, which is always in sync with the active NameNode namespace state. Only one Backup node may be registered with the NameNode at once.

BackUp節點：Checkpoint節點的擴充套件。除了checkpoint，它還從NameNode接收一個edit檔案流，在記憶體中維護他自己的namespace的copy，這個copy總是與NameNode節點上namespace的狀態同步。NameNode一次只能註冊一個BackUp節點。

Prerequisites

The following documents describe how to install and set up a Hadoop cluster:

Single Node Setup for first-time users.
Cluster Setup for large, distributed clusters.

The rest of this document assumes the user is able to set up and run a HDFS with at least one DataNode. For the purpose of this document, both the NameNode and DataNode could be running on the same physical machine.

基本條件

下面的文件描述瞭如何安裝和啟動一個Hadoop叢集：

Single Node Setup for first-time users.

Cluster Setup for large, distributed clusters.

本文件剩下的部分假設使用者已能夠建立和執行至少有一個DataNode節點的HDFS叢集。為了實現本文件的目的，NameNode和DataNode節點可以執行在一臺物理機器上。

Web Interface

NameNode and DataNode each run an internal web server in order to display basic information about the current status of the cluster. With the default configuration, the NameNode front page is at http://namenode-name:50070/. It lists the DataNodes in the cluster and basic statistics of the cluster. The web interface can also be used to browse the file system (using “Browse the file system” link on the NameNode front page).

Web介面

每一個NameNode和DataNode都執行一個內部的web伺服器，以展示關於叢集當前的狀態的基本的資訊。預設配置下，NameNode主頁面在http://namenode-name:50070/。它列出了叢集中所有的資料節點和叢集中基本統計資訊。這個web介面可以被用來瀏覽檔案系統（在NameNode的主頁上有“Browse the file system”的連結）。

Shell Commands

Hadoop includes various shell-like commands that directly interact with HDFS and other file systems that Hadoop supports. The command bin/hdfs dfs -help lists the commands supported by Hadoop shell. Furthermore, the command bin/hdfs dfs -help command-name displays more detailed help for a command. These commands support most of the normal files system operations like copying files, changing file permissions, etc. It also supports a few HDFS specific operations like changing replication of files. For more information see File System Shell Guide.

Shell 命令

Hadoop擁有各種類shell命令，能夠直接與HDFS和其他Hadoop支援的檔案系統進行互動。bin/hdfsdfs –help命令可以列出Hadoop shell支援的命令。而且bin/hdfs dfs -help command-name會列出一個命令更多的細節。這些命令支援大多數標準檔案系統操作，像複製檔案，修改檔案許可權等。它也支援一些HDFS特有的操作，像改變檔案副本個數。更多資訊盡在 File System Shell Guide。

DFSAdmin Command

The bin/hdfs dfsadmin command supports a few HDFS administration related operations. The bin/hdfs dfsadmin -help command lists all the commands currently supported. For e.g.:

-report: reports basic statistics of HDFS. Some of this information is also available on the NameNode front page.
-safemode: though usually not required, an administrator can manually enter or leave Safemode.
-finalizeUpgrade: removes previous backup of the cluster made during last upgrade.
-refreshNodes: Updates the namenode with the set of datanodes allowed to connect to the namenode. By default, Namenodes re-read datanode hostnames in the file defined by dfs.hosts, dfs.hosts.exclude Hosts defined in dfs.hosts are the datanodes that are part of the cluster. If there are entries in dfs.hosts, only the hosts in it are allowed to register with the namenode. Entries in dfs.hosts.exclude are datanodes that need to be decommissioned. Alternatively if dfs.namenode.hosts.provider.classname is set toorg.apache.hadoop.hdfs.server.blockmanagement.CombinedHostFileManager, all include and exclude hosts are specified in the JSON file defined by dfs.hosts. Datanodes complete decommissioning when all the replicas from them are replicated to other datanodes. Decommissioned nodes are not automatically shutdown and are not chosen for writing for new replicas.
-printTopology : Print the topology of the cluster. Display a tree of racks and datanodes attached to the tracks as viewed by the NameNode.

For command usage, see dfsadmin.

DFSAdmin Command

bin/hadoop dfsadmin命令支援一些HDFS管理相關的操作。bin/hadoopdfsadmin –help命令列出了當前支援的所有的命令，例如：

1. –report：報告HDFS基本的統計資訊。這些資訊中一些亦可以在NameNode主頁中檢視。

2. –safemode：雖然通常不需要，但是一個管理員可以手工的進入或者離開安全模式。

3. –finalizeUpgrade：移除最近的一次升級時先前叢集的備份。

4. –refreshNodes：更新namenode和多個連線到此NameNode的DataNode。NameNode重新讀取定義在dfs.hosts, dfs.hosts.exclude檔案中的DataNode的hostname。定義在dfs.hosts檔案中的主機是叢集中的datanode的部分。如果dfs.hosts中有條目，只有其中出現的主機才被允許註冊到NameNode。dfs.hosts.exclude中出現的條目是需要退役的DataNode。當這些節點上的副本在其他資料節點副本完成，這些DataNode完成退役。退役的節點不會自動關機，新的副本不會在選擇這些節點寫入。

5. printTopology：印表機群的拓撲。展示一個樹形的機架和依附於機架上的DataNode，就像在NameNode中看到的那樣。

更多命令的用法，看 dfsadmin。

Secondary NameNode

The NameNode stores modifications to the file system as a log appended to a native（本地的） file system file, edits. When a NameNode starts up, it reads HDFS state from an image file, fsimage, and then applies edits from the edits log file. It then writes new HDFS state to the fsimage and starts normal operation with an empty edits file. Since NameNode merges fsimage and edits files only during start up, the edits log file could get very large over time on a busy cluster. Another side effect of a larger edits file is that next restart of NameNode takes longer.

Secondary NameNode

NameNode儲存檔案系統的變化，新增這些資訊到本地檔案系統中的日誌檔案的末尾，這個日誌檔案是edits。當一個NameNode啟動，它從一個映象檔案fsimage中讀取HDFS的狀態，然後應用edits日誌檔案中的edits。然後將一個新的HDFS狀態寫到fsimage中，用一個新的空的edit檔案儲存正常的操作。因為NameNode只在啟動時合併fsimage和edit檔案，隨著時間推移，edit的日誌檔案可能在一個忙碌的叢集中變得非常大。大edit日誌檔案的另一個副作用是下一次NameNode的啟動將會花費更長的時間。

The secondary NameNode merges（合併） the fsimage and the edits log files periodically and keeps edits log size within a limit. It is usually run on a different machine than the primary NameNode since its memory requirements are on the same order as the primary NameNode.

Secondary NameNode週期性地合併fsimage和edit日誌檔案，保持日誌檔案的大小在一個範圍內。它通常執行在一個不同於NameNode的機器上，因為它的記憶體需求跟NameNode一樣。

The start of the checkpoint process on the secondary NameNode is controlled by two configuration parameters.

dfs.namenode.checkpoint.period, set to 1 hour by default, specifies the maximum delay between two consecutive checkpoints, and
dfs.namenode.checkpoint.txns, set to 1 million by default, defines the number of uncheckpointed transactions on the NameNode which will force an urgent checkpoint, even if the checkpoint period has not been reached.

Checkpoint程式在Secondary NameNode上的啟動被兩個配置引數管理：

1. dfs.namenode.checkpoint.period：預設設定為1小時，這個引數指定兩次連續的Checkpoint操作的最大間隔。

2. dfs.namenode.checkpoint.txns：預設設定為1百萬，這個引數定義了NameNode中沒有Checkpoint的事務的個數，如果超過這個個數，即使沒有到Checkpoint的時間，也會強制Checkpoint。

The secondary NameNode stores the latest checkpoint in a directory which is structured the same way as the primary NameNode’s directory. So that the check pointed image is always ready to be read by the primary NameNode if necessary.

For command usage, see secondarynamenode.

Secondary NameNode將最近的Checkpoint儲存到跟NameNode中一樣結構的目錄中。所以如果必要，被Checkpoint的image總是準備被NameNode讀取。

更多命令用法，看secondarynamenode。

Checkpoint Node

NameNode persists its namespace using two files: fsimage, which is the latest checkpoint of the namespace and edits, a journal (log) of changes to the namespace since the checkpoint. When a NameNode starts up, it merges the fsimage and edits journal to provide an up-to-date view of the file system metadata. The NameNode then overwrites fsimage with the new HDFS state and begins a new edits journal.

Checkpoint Node

NameNode用兩個檔案持久化它的namespace：fsimage和edits，fsimage是namespace的最近一次的Checkpoint，edits檔案是自Checkpoint後namespace的變化日誌。當NameNode啟動時，它合併fsimage和edits日誌檔案以提供一個檔案系統後設資料的最新的檢視。然後NameNode用新的HDFS狀態覆蓋fsimage，開起一個新的edits檔案。

The Checkpoint node periodically creates checkpoints of the namespace. It downloads fsimage and edits from the active NameNode, merges them locally, and uploads the new image back to the active NameNode. The Checkpoint node usually runs on a different machine than the NameNode since its memory requirements are on the same order as the NameNode. The Checkpoint node is started by bin/hdfs namenode -checkpoint on the node specified in the configuration file.

Checkpoint節點週期性的建立namespace的Checkpoint。它從active的NameNode下載fsimage和edits檔案，本地合併它們生成新的image，然後將新的image上傳回activeNameNode上。Checkpoint節點通常執行在不同於NameNode的機器上，因為它的記憶體需求跟NameNode一樣。Checkpoint節點在配置檔案中指定的節點上用bin/hdfs namenode –checkpoint啟動。

The location of the Checkpoint (or Backup) node and its accompanying web interface are configured via the dfs.namenode.backup.address and dfs.namenode.backup.http-address configuration variables.

Checkpoint（或Backup）節點和它通過dfs.namenode.backup.address 和dfs.namenode.backup.http-address配置的附帶的web介面。

The start of the checkpoint process on the Checkpoint node is controlled by two configuration parameters.

dfs.namenode.checkpoint.period, set to 1 hour by default, specifies the maximum delay between two consecutive checkpoints
dfs.namenode.checkpoint.txns, set to 1 million by default, defines the number of uncheckpointed transactions on the NameNode which will force an urgent checkpoint, even if the checkpoint period has not been reached.

Checkpoint節點上的checkpoint程式被兩個配置引數管理：

1. dfs.namenode.checkpoint.period：預設設定為1小時，這個引數指定兩次連續的Checkpoint操作的最大間隔。

2. dfs.namenode.checkpoint.txns：預設設定為1百萬，這個引數定義了NameNode中沒有Checkpoint的事務的個數，如果超過這個個數，即使沒有到Checkpoint的時間，也會強制Checkpoint。

The Checkpoint node stores the latest checkpoint in a directory that is structured the same as the NameNode’s directory. This allows the checkpointed image to be always available for reading by the NameNode if necessary. See Import checkpoint.

Multiple checkpoint nodes may be specified in the cluster configuration file.

For command usage, see namenode.

Checkpoint節點將最近的Checkpoint儲存到跟NameNode中一樣結構的目錄中。這使得必要時被checkpoint的image是可讀的。檢視Import checkpoint。

一個叢集中可以配置多個Checkpoint節點。

更多的命令用法，看 namenode。

Backup Node

The Backup node provides the same checkpointing functionality as the Checkpoint node, as well as maintaining an in-memory, up-to-date copy of the file system namespace that is always synchronized with the active NameNode state. Along with accepting a journal stream of file system edits from the NameNode and persisting this to disk, the Backup node also applies those edits into its own copy of the namespace in memory, thus creating a backup of the namespace.

The Backup node does not need to download fsimage and edits files from the active NameNode in order to create a checkpoint, as would be required with a Checkpoint node or Secondary NameNode, since it already has an up-to-date state of the namespace state in memory. The Backup node checkpoint process is more efficient as it only needs to save the namespace into the local fsimage file and reset edits.

As the Backup node maintains a copy of the namespace in memory, its RAM requirements are the same as the NameNode.

The NameNode supports one Backup node at a time. No Checkpoint nodes may be registered if a Backup node is in use. Using multiple Backup nodes concurrently will be supported in the future.

The Backup node is configured in the same manner as the Checkpoint node. It is started with bin/hdfs namenode -backup.

The location of the Backup (or Checkpoint) node and its accompanying web interface are configured via the dfs.namenode.backup.address and dfs.namenode.backup.http-address configuration variables.

Use of a Backup node provides the option of running the NameNode with no persistent storage, delegating all responsibility for persisting the state of the namespace to the Backup node. To do this, start the NameNode with the -importCheckpoint option, along with specifying no persistent storage directories of type edits dfs.namenode.edits.dir for the NameNode configuration.

For a complete discussion of the motivation behind the creation of the Backup node and Checkpoint node, see HADOOP-4539. For command usage, see namenode.

Backup節點

跟Checkpoint node差不多。

Import Checkpoint

The latest checkpoint can be imported to the NameNode if all other copies of the image and the edits files are lost. In order to do that one should:

Create an empty directory specified in the dfs.namenode.name.dir configuration variable;
Specify the location of the checkpoint directory in the configuration variable dfs.namenode.checkpoint.dir;
and start the NameNode with -importCheckpoint option.

The NameNode will upload the checkpoint from the dfs.namenode.checkpoint.dir directory and then save it to the NameNode directory(s) set in dfs.namenode.name.dir. The NameNode will fail if a legal image is contained in dfs.namenode.name.dir. The NameNode verifies that the image in dfs.namenode.checkpoint.dir is consistent, but does not modify it in any way.

For command usage, see namenode.

Import Checkpoint

如果NameNode中所有其他的image和edits檔案的copy都丟失了，最近的Checkpoint可以被import到NameNode中。為了可以import，你應該：

1.      在dfs.namenode.name.dir配置指定的path建立一個空的目錄。

2.      用dfs.namenode.checkpoint.dir指定Checkpoint目錄。

3.       用-importCheckpoint 選項啟動NameNode。

NameNode將從dfs.namenode.checkpoint.dir目錄中上傳Checkpoint，然後將它儲存到 dfs.namenode.name.dir設定的NameNode的目錄。如果在dfs.namenode.name.dir目錄中有一個合法的image，NameNode將會失敗。NameNode檢驗dfs.namenode.checkpoint.dir 的image是否一致，但是任何情況下都不會修改它。

更多命令用法，檢視namenode。

Balancer

HDFS data might not always be be placed uniformly across the DataNode. One common reason is addition of new DataNodes to an existing cluster. While placing new blocks (data for a file is stored as a series of blocks), NameNode considers various parameters before choosing the DataNodes to receive these blocks. Some of the considerations are:

Policy to keep one of the replicas of a block on the same node as the node that is writing the block.
Need to spread different replicas of a block across the racks so that cluster can survive loss of whole rack.
One of the replicas is usually placed on the same rack as the node writing to the file so that cross-rack network I/O is reduced.
Spread HDFS data uniformly across the DataNodes in the cluster.

Due to multiple competing considerations, data might not be uniformly placed across the DataNodes. HDFS provides a tool for administrators that analyzes block placement and rebalanaces data across the DataNode. A brief administrator’s guide for balancer is available at HADOOP-1652.

For command usage, see balancer.

HDFS資料可能不總是一致的被存放在DataNode中。一個常見的原因是新DataNode節點的增加。當存放新的Block（一個檔案的資料被存放為一些列的Block）時，NameNode考慮很多的引數在選擇接收這些Block的DataNode時。下面是一些考慮的因素：

1.      保持一個Block的多個副本中的一個與正在寫入的Block在一個節點上。

2.      需要將副本跨機架傳播，這樣叢集可以在整個機架淪陷時倖存。

3.      多個副本中的一個通常存放在跟正在寫入的檔案相同的機架上，這樣可以減少跨機架的網路I/O。

4.      一致的的在叢集中的DataNode之間傳播HDFS資料。

考慮到多個相互矛盾的因素，資料可能不一致的存放在DataNode中。HDFS提供了一個分析資料塊的位置和重新平衡DataNode中的資料的工具。HADOOP-1652中是一個簡短的rebalancer的管理員指南，pdf格式。

更多命令用法，看balancer。

Rack Awareness

A HDFS cluster can recognize the topology of racks where each nodes are put. It is important to configure this topology in order to optimize the data capacity and usage. For more detail, please check the rack awareness in common document.

Safemode

During start up the NameNode loads the file system state from the fsimage and the edits log file. It then waits for DataNodes to report their blocks so that it does not prematurely start replicating the blocks though enough replicas already exist in the cluster. During this time NameNode stays in Safemode. Safemode for the NameNode is essentially a read-only mode for the HDFS cluster, where it does not allow any modifications to file system or blocks. Normally the NameNode leaves Safemode automatically after the DataNodes have reported that most file system blocks are available. If required, HDFS could be placed in Safemode explicitly using bin/hdfs dfsadmin -safemode command. NameNode front page shows whether Safemode is on or off. A more detailed description and configuration is maintained as JavaDoc for setSafeMode().

Safemode

NameNode啟動是從fsimage和edits日誌檔案中載入檔案系統狀態。然後等待DataNode報告它們的Block，所以NameNode不過早的複製Block，可能叢集中有足夠的副本。在這段時間內，NameNode在safemode狀態。NameNode的Safemode本質上來說就是HDFS叢集的只讀模式，它不允許檔案系統或Block的任何修改。正常情況下，在DataNode報告它的大多數檔案系統的Block available之後，NameNode會自動的離開safemode模式。如果有必要，HDFS可以用bin/hadoop dfsadmin –safemode明確的進入safemode。

NameNode主頁展示了safemode開關狀態。更詳細的描述和配置在setSafeMode()的java doc中。

fsck

HDFS supports the fsck command to check for various inconsistencies. It it is designed for reporting problems with various files, for example, missing blocks for a file or under-replicated blocks. Unlike a traditional fsck utility for native file systems, this command does not correct the errors it detects. Normally NameNode automatically corrects most of the recoverable failures. By default fsck ignores open files but provides an option to select all files during reporting. The HDFS fsck command is not a Hadoop shell command. It can be run as bin/hdfs fsck. For command usage, see fsck. fsck can be run on the whole file system or on a subset of files.

Fsck

HDFS支援fsck命令來檢查各種不一致狀態。它被設定用來報告各種檔案的各種問題，例如，丟失一個檔案的某個Block或者正在複製的Block。不像針對本地檔案系統的傳統的fsck工具，這個命令不更正它檢測到的錯誤。正常情況下，NameNode自動更正大部分可恢復的失效。預設，fsck忽略開啟的檔案但是提供一個選項在報告時選擇所有的檔案。HDFS fsck命令不是Hadoop shell命令。它可以用bin/hadoop fsck執行。更多命令的用法，看fsck。Fsck可以執行在整個檔案系統或者所有檔案的子集。

fetchdt

HDFS supports the fetchdt command to fetch Delegation Token and store it in a file on the local system. This token can be later used to access secure server (NameNode for example) from a non secure client. Utility uses either RPC or HTTPS (over Kerberos) to get the token, and thus requires kerberos tickets to be present before the run (run kinit to get the tickets). The HDFS fetchdt command is not a Hadoop shell command. It can be run as bin/hdfs fetchdt DTfile. After you got the token you can run an HDFS command without having Kerberos tickets, by pointing HADOOP_TOKEN_FILE_LOCATION environmental variable to the delegation token file. For command usage, see fetchdt command.

Fetchdt

HDFS支援fetchdt命令來獲取 Delegation Token和將其儲存到本地檔案系統中。這個token之後可以被用來從一個不安全的客戶端訪問安全的服務（例如NameNode）。此工具使用RPC或者HTTPS（在Kerberos之上）來獲取token，因此需要ticket才能執行（執行kinit 命令可以得到ticket）。HDFSfetchdt命令不是Hadoop shell命令。它可以用bin/hadoop fetchdt DTfile執行。在你取得token之後，通過指定 HADOOP_TOKEN_FILE_LOCATION環境變數你可以不需要Kerberosticket就執行HDFS命令， HADOOP_TOKEN_FILE_LOCATION指定delegationtoken檔案的位置。更多命令用法，檢視 fetchdt命令。

Recovery Mode

Typically, you will configure multiple metadata storage locations. Then, if one storage location is corrupt, you can read the metadata from one of the other storage locations.

However, what can you do if the only storage locations available are corrupt? In this case, there is a special NameNode startup mode called Recovery mode that may allow you to recover most of your data.

You can start the NameNode in recovery mode like so: namenode -recover

When in recovery mode, the NameNode will interactively prompt you at the command line about possible courses of action you can take to recover your data.

If you don’t want to be prompted, you can give the -force option. This option will force recovery mode to always select the first choice. Normally, this will be the most reasonable choice.

Because Recovery mode can cause you to lose data, you should always back up your edit log and fsimage before using it.

Recovery Mode

通常情況下，你需要配置多個後設資料的儲存位置。然後，若果一個儲存位置崩潰，你可以從另一個其他的位置讀取後設資料。

但是，如果僅有的儲存崩潰，你能做啥呢？在這種情況下，有一個特殊的NameNode啟動模式，Recovery Mode，它允許你恢復你的大多數資料。

你可以用namenode –recover以recovery mode啟動NameNode。

在Recovery Mode時，NameNode將在命令列互動性地提示你可以恢復資料的可能的行動步驟。

如果你不希望被提示，你可以給 -force選項。這個選項將強制RecoveryMode總是選擇第一個選項。正常情況下，這將是最合理的選擇。

因為Recovery Mode可能使你丟失資訊，在使用它之前，你應該總是備份你的edit日誌和fsimage。

Upgrade and Rollback

When Hadoop is upgraded on an existing cluster, as with any software upgrade, it is possible there are new bugs or incompatible changes that affect existing applications and were not discovered earlier. In any non-trivial HDFS installation, it is not an option to loose any data, let alone to restart HDFS from scratch. HDFS allows administrators to go back to earlier version of Hadoop and rollback the cluster to the state it was in before the upgrade. HDFS upgrade is described in more detail in Hadoop Upgrade Wiki page. HDFS can have one such backup at a time. Before upgrading, administrators need to remove existing backup using bin/hadoop dfsadmin -finalizeUpgrade command. The following briefly describes the typical upgrade procedure:

Upgrade 和 Rollback

當Hadoop在一個已存在的叢集上被升級的時候，就像任何的軟體升級一樣，它可能有一些新的bug或者不相容的變化，這些bug和變化可能會影響已存在的應用程式，並且不能過早的發現。在任何重要的HDFS安裝中，丟失任何資料都是不允許的，更不用說HDFS重新啟動。HDFS允許管理員回滾回Hadoop升級之前的版本，將叢集回滾回升級之前的狀態。HDFS升級更多的細節在Hadoop Upgrade。這個時候，HDFS可以有這樣一個備份。在升級之前，管理員需要用bin/hadoop dfsadmin -finalizeUpgrade命令移除已經存在的備份。下面是對一個典型的升級過程簡短的描述：

Before upgrading Hadoop software, finalize if there an existing backup.
Stop the cluster and distribute new version of Hadoop.
Run the new version with -upgrade option (bin/start-dfs.sh -upgrade).
Most of the time, cluster works just fine. Once the new HDFS is considered working well (may be after a few days of operation), finalize the upgrade. Note that until the cluster is finalized, deleting the files that existed before the upgrade does not free up real disk space on the DataNodes
If there is a need to move back to the old version,

stop the cluster and distribute earlier version of Hadoop.
run the rollback command on the namenode (bin/hdfs namenode -rollback).
start the cluster with rollback option. (sbin/start-dfs.sh -rollback).

在升級Hadoop軟體之前，如果有一個已經存在的備份，finalize掉。dfsadmin -upgradeProgress狀態可以告訴我們叢集是否需要被finalize

停止叢集，分發新版本的Hadoop。

用bin/start-dfs.sh -upgrade執行新版本的hadoop

大多數情況下，叢集會很好的工作。一旦新HDFS被認為工作良好（可能是很多天的操作之後得出），finalize掉這個Upgrade。注意，直到叢集被finalize，刪除升級之前存在的檔案不會釋放DataNode上真正的儲存空間。

如果有需要回滾回舊版本，

停掉叢集，分發hadoop舊版本。

在namenode上執行rollback命令(bin/hdfs namenode -rollback)

用rollback選項啟動叢集，bin/start-dfs.sh –rollback。

When upgrading to a new version of HDFS, it is necessary to rename or delete any paths that are reserved in the new version of HDFS. If the NameNode encounters a reserved path during upgrade, it will print an error like the following:

/.reserved is a reserved path and .snapshot is a reserved path component in this version of HDFS. Please rollback and delete or rename this path, or upgrade with the -renameReserved [key-value pairs] option to automatically rename these paths during upgrade.

當升級到一個新版本的HDFS，有必要更改或刪除任何儲存在新版本中的路徑。如果升級期間，NameNode遇到一個存在的路徑，它將會列印像下面這樣的錯誤：

/.reserved is a reserved path and .snapshot is areserved path component in this version of HDFS. Please rollback and delete orrename this path, or upgrade with the -renameReserved [key-value pairs] optionto automatically rename these paths during upgrade.

Specifying -upgrade -renameReserved [optional key-value pairs] causes the NameNode to automatically rename any reserved paths found during startup. For example, to rename all paths named .snapshot to .my-snapshot and .reserved to .my-reserved, a user would specify -upgrade -renameReserved .snapshot=.my-snapshot,.reserved=.my-reserved

指定 -upgrade -renameReserved[optional key-value pairs]會使NameNode自動更改啟動過程中發現任何儲存的路徑。例如，更改所有的.snapshot命名的路徑為.my-snapshot，更改所有的.reserved路徑為.my-reserved，使用者也可以指定-upgrade -renameReserved.snapshot=.my-snapshot,.reserved=.my-reserved。

If no key-value pairs are specified with -renameReserved, the NameNode will then suffix reserved paths with .<LAYOUT-VERSION>.UPGRADE_RENAMED, e.g. .snapshot.-51.UPGRADE_RENAMED.

如果沒有key-value對用-renameReserved被指定，NameNode將新增字尾 .<LAYOUT-VERSION>.UPGRADE_RENAMED，例如， .snapshot.-51.UPGRADE_RENAMED。

There are some caveats to this renaming process. It’s recommended, if possible, to first hdfs dfsadmin -saveNamespace before upgrading. This is because data inconsistency can result if an edit log operation refers to the destination of an automatically renamed file.

Rename程式會有一些警告。建議，如果可能，升級之前先執行hdfs dfsadmin -saveNamespace。這是因為如果edit日誌操作涉及到自動修改過的檔案的話，資料會出現不一致的情況。

DataNode Hot Swap Drive

Datanode supports hot swappable drives. The user can add or replace HDFS data volumes without shutting down the DataNode. The following briefly describes the typical hot swapping drive procedure:

If there are new storage directories, the user should format them and mount them appropriately.

The user updates the DataNode configuration dfs.datanode.data.dir to reflect the data volume directories that will be actively in use.

The user runs dfsadmin -reconfig datanode HOST:PORT start to start the reconfiguration process. The user can use dfsadmin -reconfig datanode HOST:PORT status to query the running status of the reconfiguration task.

Once the reconfiguration task has completed, the user can safely umount the removed data volume directories and physically remove the disks.

File Permissions and Security

The file permissions are designed to be similar to file permissions on other familiar platforms like Linux. Currently, security is limited to simple file permissions. The user that starts NameNode is treated as the superuser for HDFS. Future versions of HDFS will support network authentication protocols like Kerberos for user authentication and encryption of data transfers. The details are discussed in the Permissions Guide.

檔案許可權和安全

檔案許可權的設計跟其他常見的平臺像linux是相似的。目前，安全僅限於簡單的檔案許可權。啟動NameNode的使用者被認為是HDFS的超級使用者。將來的HDFS版本將支援網路認證協議像Kerberos來支援使用者認證和資料傳輸加密。更詳細的討論在許可權指南。

Scalability

Hadoop currently runs on clusters with thousands of nodes. The PoweredBy Wiki page lists some of the organizations that deploy Hadoop on large clusters. HDFS has one NameNode for each cluster. Currently the total memory available on NameNode is the primary scalability limitation. On very large clusters, increasing average size of files stored in HDFS helps with increasing cluster size without increasing memory requirements on NameNode. The default configuration may not suite very large clusters. The FAQ Wiki page lists suggested configuration improvements for large Hadoop clusters.

Scalability

Hadoop目前可以執行在幾千個節點的叢集上。PoweredByWiki頁面上列出了一些部署hadoop大規模叢集的組織。HDFS在每個叢集中有一個NameNode。目前NameNode上總的記憶體是主要的擴充套件限制。在每一個大叢集上，增加儲存在HDFS中的檔案的大小有助於在不增加NameNode記憶體的情況下增加叢集儲存能力。預設的配置可能不適合非常大的叢集。FAQ Wiki頁面列出了對於大規模hadoop叢集的建議的配置提高。