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https://issues.apache.org/jira/browse/HDFS-7285?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14357832#comment-14357832
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Jing Zhao commented on HDFS-7285:
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Thanks for the summary, Zhe!
One question for the EC policy or EC ZONE is that whether we allow users to
change the policy/schema of a file/dir. Currently for storage policy like COLD,
WARM, and HOT, users can change a file/directory's policy and this change will
be applied to new created/appended data, and can be enforced on existing files
later by external tools like Mover. This lazy enforcement semantic also applies
to renamed files.
However, for EC, since whether a file is EC'ed and its EC schema directly
determines its read/write/append pattern, things become different and more
complicated. If we allow changing the EC schema associated with a directory, we
need to make sure for all the files inside its old EC schema can be found,
which means we may need to associate the schema directly on the files or even
blocks (which can be inefficient). And then how to handle new appended data and
file rename also becomes challenge. If we disallow the schema changing or
renaming across directories with different EC policies, in the end we may have
a design like EC ZONE.
> 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: ECAnalyzer.py, ECParser.py, HDFS-7285-initial-PoC.patch,
> HDFSErasureCodingDesign-20141028.pdf, HDFSErasureCodingDesign-20141217.pdf,
> HDFSErasureCodingDesign-20150204.pdf, HDFSErasureCodingDesign-20150206.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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