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From "Zhe Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HDFS-7285) Erasure Coding Support inside HDFS
Date Tue, 07 Jul 2015 23:45:11 GMT

     [ https://issues.apache.org/jira/browse/HDFS-7285?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Zhe Zhang updated HDFS-7285:
----------------------------
    Attachment: Consolidated-20150707.patch

I finished a complete pass of the patch (both {{main}} and {{test}} codes) and pushed to my
github [repo | https://github.com/zhe-thoughts/hadoop/tree/HDFS-EC-Merge]. Also uploading
the consolidated patch (renaming it again and hoping Jenkins applies it against trunk instead
of our branch). 

I made some minor adjustments to the list of sub patches:
{code}
1. HADOOP-COMMON side support for codec calculations
2. Support Erasure Coding Zones.
3. Extend BlockInfo to handle striped block groups.
4. Allocate and manage striped blocks in NameNode blockmanagement module.
5. BlockPlacementPolicies for erasure coding
6. Create LocatedStripedBlock abstraction to represent striped block groups.
7. Distribute recovery work for striped blocks to DataNode.
8. Add striped block support in INodeFile.
9. Client side support
10. Datanode support
11. Change fsck to support EC files
12. Support striped block groups in fsimage and edit logs
13. Balancer and mover support for striped block groups
14. Additional unit tests for erasure coding
{code}
I also cherry-picked the 2 new patches from HDFS-7285 branch.

I created separate Jenkins builds for sub patches 1~4. Most tests passed. The remaining handful
of failures seem to be resulted from the patch splitting (they pass in the final consolidated
patch).

So *sub patches 1~4* are ready for reviews. Any comments and suggestions are much appreciated.
In particular, sub patch 3 has the new implementation of {{BlockInfoStriped}} which has not
been reviewed in the branch.

> 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
>         Attachments: Consolidated-20150707.patch, ECAnalyzer.py, ECParser.py, 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-EC-Merge-PoC-20150624.patch, HDFS-EC-merge-consolidated-01.patch,
HDFS-bistriped.patch, HDFSErasureCodingDesign-20141028.pdf, HDFSErasureCodingDesign-20141217.pdf,
HDFSErasureCodingDesign-20150204.pdf, HDFSErasureCodingDesign-20150206.pdf, HDFSErasureCodingPhaseITestPlan.pdf,
fsimage-analysis-20150105.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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