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Date: Wed, 1 Mar 2017 19:19:46 +0000 (UTC)
From: "Chris Douglas (JIRA)" <jira@apache.org>
To: hdfs-issues@hadoop.apache.org
Message-ID: <JIRA.12750341.1414155764000.34147.1488395986291@Atlassian.JIRA>
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Subject: [jira] [Commented] (HDFS-7285) Erasure Coding Support inside HDFS
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archived-at: Wed, 01 Mar 2017 19:19:52 -0000


    [ https://issues.apache.org/jira/browse/HDFS-7285?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15890845#comment-15890845 ] 

Chris Douglas commented on HDFS-7285:
-------------------------------------

That sounds exciting, [~sw0rdf1sh]. There's a wiki [here|https://wiki.apache.org/hadoop/HowToContribute] that describes the patch process. If you need help please don't hesitate to reach out on [hdfs-dev|http://hadoop.apache.org/mailing_lists.html#HDFS].

> Erasure Coding Support inside HDFS
> ----------------------------------
>
>                 Key: HDFS-7285
>                 URL: https://issues.apache.org/jira/browse/HDFS-7285
>             Project: Hadoop HDFS
>          Issue Type: New Feature
>            Reporter: Weihua Jiang
>            Assignee: Zhe Zhang
>             Fix For: 3.0.0-alpha1
>
>         Attachments: Compare-consolidated-20150824.diff, Consolidated-20150707.patch, Consolidated-20150806.patch, Consolidated-20150810.patch, ECAnalyzer.py, ECParser.py, fsimage-analysis-20150105.pdf, HDFS-7285-Consolidated-20150911.patch, HDFS-7285-initial-PoC.patch, HDFS-7285-merge-consolidated-01.patch, HDFS-7285-merge-consolidated-trunk-01.patch, HDFS-7285-merge-consolidated.trunk.03.patch, HDFS-7285-merge-consolidated.trunk.04.patch, HDFS-bistriped.patch, HDFS-EC-merge-consolidated-01.patch, HDFS-EC-Merge-PoC-20150624.patch, HDFSErasureCodingDesign-20141028.pdf, HDFSErasureCodingDesign-20141217.pdf, HDFSErasureCodingDesign-20150204.pdf, HDFSErasureCodingDesign-20150206.pdf, HDFSErasureCodingPhaseITestPlan.pdf, HDFSErasureCodingSystemTestPlan-20150824.pdf, HDFSErasureCodingSystemTestReport-20150826.pdf
>
>
> Erasure Coding (EC) can greatly reduce the storage overhead without sacrifice of data reliability, comparing to the existing HDFS 3-replica approach. For example, if we use a 10+4 Reed Solomon coding, we can allow loss of 4 blocks, with storage overhead only being 40%. This makes EC a quite attractive alternative for big data storage, particularly for cold data. 
> Facebook had a related open source project called HDFS-RAID. It used to be one of the contribute packages in HDFS but had been removed since Hadoop 2.0 for maintain reason. The drawbacks are: 1) it is on top of HDFS and depends on MapReduce to do encoding and decoding tasks; 2) it can only be used for cold files that are intended not to be appended anymore; 3) the pure Java EC coding implementation is extremely slow in practical use. Due to these, it might not be a good idea to just bring HDFS-RAID back.
> We (Intel and Cloudera) are working on a design to build EC into HDFS that gets rid of any external dependencies, makes it self-contained and independently maintained. This design lays the EC feature on the storage type support and considers compatible with existing HDFS features like caching, snapshot, encryption, high availability and etc. This design will also support different EC coding schemes, implementations and policies for different deployment scenarios. By utilizing advanced libraries (e.g. Intel ISA-L library), an implementation can greatly improve the performance of EC encoding/decoding and makes the EC solution even more attractive. We will post the design document soon. 


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