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https://issues.apache.org/jira/browse/HDFS-7285?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14702000#comment-14702000
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Zhe Zhang commented on HDFS-7285:
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Given the feedbacks from the common-dev [discussion |
http://mail-archives.apache.org/mod_mbox/hadoop-common-dev/201508.mbox/%3cCAGB5D2bPWeV2Hk+67=DamWpVfLTM6nkjb_wG3n4=wan890z...@mail.gmail.com%3e],
I think we should use "git merge" to sync HDFS-7285 branch with trunk now.
Please comment if you have any concern.
I will do the following before updating the main HDFS-7285 branch:
# Run "git merge" on current HDFS-7285 branch agains trunk, and add one merge
commit to resolve all conflicts so far
# Reuse the current HDFS-7285-merge branch to carry the merged result, and run
Jenkins
# Compare the merged result with the rebased result from [~vinayrpet] on
HDFS-7285-REBASE branch
If no major discrepancy is found, I will push the merged result to HDFS-7285
branch and delete the intermediate branches.
I apologize for not foreseeing the complexity and size of the EC branch at the
beginning of the project, and adjusting the git workflow accordingly. Hope we
have cleared confusions through the above discussions. Let me know if you still
have questions about the workflow.
> 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,
> Consolidated-20150806.patch, Consolidated-20150810.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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