singa-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF subversion and git services (JIRA)" <>
Subject [jira] [Commented] (SINGA-97) SINGA-97 Add HDFS Store
Date Sat, 02 Jan 2016 15:20:40 GMT


ASF subversion and git services commented on SINGA-97:

Commit 9fbc8ee7aabbbdc2f76cdcccdf346e14d4544f1a in incubator-singa's branch refs/heads/master
from [~zhongle]
[;h=9fbc8ee ]

SINGA-97 Add HDFS Store

Modify compilation files. Now as a user, one can build SINGA with hdfs support by running:
	./configure --enable-hdfs --with-libhdfs=/PATH/TO/HDFS3
--with-libhdfs is optional as by default the path is /usr/local/.wq

> SINGA-97 Add HDFS Store 
> ------------------------
>                 Key: SINGA-97
>                 URL:
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: Anh Dinh
>            Assignee: Anh Dinh
> This ticket implements HDFS Store for reading data from HDFS. It complements the existing
CSV Store which reads data from CSV file. HDFS is the popular distributed file system with
high (sequential) I/O throughputs, thus supporting it is necessary in order for SINGA to scale.

> The implementation will extend singa::io::Store class which is declared in `singa/io/store.h`.
In particular, it will support the following I/O operations:
> + `bool Open(string& file, Mode mode)`
> + `bool Close()`
> + `bool Flush()`
> + `int Seek(int record_idx)`
> + `int Read(string *content)`
> + `int Write(string& content)`
> HDFS usage in SINGA is different to that in standard MapReduce applications. Specifically,
each SINGA worker may train on sequences of records which do not lie within block boundary,
whereas in MapReduce  each Mapper process a number of complete blocks.  In MapReduce, the
runtime engine may fetch and cache the entire block over the network, knowing that the block
will be processed entirely. In SINGA, such pre-fetching and caching strategy will be sub-optimal
because it wastes I/O and network bandwidth on data records which are not used. 
> We defer I/O optimization to a future ticket. 
> For implementation, we choose `libhdfs3` from Pivotal for HDFS implementation in C++.
This library is built natively for C++, hence it is more optimized and easier to deploy than
the original  `libhdfs` library that is shipped with Hadoop. Finally, we test the implementation
in a distributed environment set up from a number of  Docker containers (see SINGA-11). 

This message was sent by Atlassian JIRA

View raw message