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https://issues.apache.org/jira/browse/HDFS-7285?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14384743#comment-14384743
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Zhe Zhang commented on HDFS-7285:
---------------------------------
Thanks [~drankye] for the thoughts.
I just talked to some HIVE folks about the HDFS directory structure in their
typical workloads. In a nutshell, it looks like the following:
{code}
warehouse
/ \
db1 db2
/ \ / \
... ... table_1 table_2
/ | \
part_1 part_2 part_3 ...
{code}
Each DB table is represented as a directory (usually with huge fan-out), under
which each partition is stored as a file. Each partition maps to a fixed range
in the key space. I was told that it's quietly common to see skewed partitions.
A likely scenario is thousands of small partitions along with a few outliers
that are much larger than average. In the EC context, it indicates a potential
need for per-file policies (e.g. EC for large files, replication for small
files).
I still plan to look at a few more cases. At this stage, I think _extended
storage policy_ is a good term to use in our APIs (maybe we can abbreviate it
as {{XStoragePolicy}}).
> 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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