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https://issues.apache.org/jira/browse/HDFS-7285?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14302065#comment-14302065
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Zhe Zhang commented on HDFS-7285:
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bq. If we only use small fixed value, for example 64KB as the stripe cell size,
then for large file, we need much more ec block groups to store the entire file
than the number of blocks we need using replication way,
The number of block groups is actually unrelated to the cell size (e.g. 64KB).
For example, under a 6+3 schema, any file smaller than 9 blocks will have 1
block group.
A smaller cell size better handles small files. But data locality is degraded
-- for example, it might be hard to fit MapReduce records into 64KB cells.
> 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,
> HDFSErasureCodingDesign-20141028.pdf, HDFSErasureCodingDesign-20141217.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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