[jira] [Issue Comment Deleted] (AIRAVATA-1646) [GSoC] Brainstorm Airavata Data Management Needs

["pankaj saha (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/AIRAVATA-1646?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

pankaj saha updated AIRAVATA-1646:
----------------------------------
    Comment: was deleted

(was: Hi Suresh,

one of the outcomes is a software pipeline. So, for application X, the recommended pipeline could be

input -> read from mongoDB
processing -> via MapReduce implementation (Hadoop)
ouput -> write to Cassandra

Thanks
Pankaj)

> [GSoC] Brainstorm Airavata Data Management Needs
> ------------------------------------------------
>
>                 Key: AIRAVATA-1646
>                 URL: https://issues.apache.org/jira/browse/AIRAVATA-1646
>             Project: Airavata
>          Issue Type: Brainstorming
>            Reporter: Suresh Marru
>              Labels: gsoc, gsoc2015,, mentor
>
> Currently Airavata focuses on Execution Management and the Registry Sub-System (with app, resource and experiment catalogs) capture metadata about applications and executions. There were few efforts (primarily from student projects) to explore this void. It will be good to concretely propose data management solutions to for input data registration, input and generated retrieval, data transfers and replication management. 
> Metadata Catalog: In addition current metadata management is based on shredding thrift data models into mysql/derby schema. This is described in [1]. We have discussed extensively on using Object Store data bases with a conclusion of understanding the requirements more systematically. A good stand alone task would be to understand current metadata management and propose alternative solutions with proof of concept implementations. Once the community is convinced, we can then plan on implementing them into production. 
> Provenance: Airavata could be enhanced to capture provenance to organize the data for reuse, discovery, comparison and sharing. This is a well explored field. There might be good compelling third party solutions. Especially it will be good to explore in the bigdata space and identify leverages (either concepts, or even better implementations).
> Auditing and Traceability:  As Airavata mediates executions on behalf of gateways, it has to strike a balance between abstracting the compute resource interactions at the same time providing transparent execution trace. This will bloat the amount of data to be catalogued. A good effort will be to understand the current extent of airavata audits and provide suggestions. 
> BigData Leverage: Airavata needs to leverage the influx of tools in this space. Any suggestions on relevant tools which will enhance Airavata experience will be a good fit. 
> [1] - https://cwiki.apache.org/confluence/display/AIRAVATA/Airavata+Data+Models+0.12
> [2] - http://markmail.org/thread/4lguliiktjohjmsd



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