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From "Zhe Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HDFS-7285) Erasure Coding Support inside HDFS
Date Fri, 04 Mar 2016 18:23:42 GMT

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

Zhe Zhang updated HDFS-7285:
----------------------------
    Release Note: 
<!-- markdown -->
HDFS now provides native support for erasure coding (EC) to store data more efficiently. Each
individual directory can be configured with an EC policy with command {{hdfs erasurecode -setPolicy}}.
When a file is created, it will inherit the EC policy from its nearest ancestor to determine
how its blocks are stored. Compared with 3-way replication, the default EC policy saves 50%
of storage space for configured directories, while tolerating more storage failures.

To support small files, the currently phase of HDFS-EC stores blocks in _striped_ layout,
where a logical file block is divided into small units (64KB by default) and distributed to
a set of {{DataNodes}}. This enables parallel I/O but also decreases data locality. Therefore,
the cluster environment and I/O workloads should be considered before configuring EC policies.

> 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
>
>         Attachments: Compare-consolidated-20150824.diff, Consolidated-20150707.patch,
Consolidated-20150806.patch, Consolidated-20150810.patch, ECAnalyzer.py, ECParser.py, 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-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, HDFSErasureCodingSystemTestPlan-20150824.pdf,
HDFSErasureCodingSystemTestReport-20150826.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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