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From "Kevin Ratnasekera (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (GORA-413) Support creation of dynamic columns within Gora datastore mapping designs
Date Thu, 02 May 2019 08:55:00 GMT

     [ https://issues.apache.org/jira/browse/GORA-413?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Kevin Ratnasekera updated GORA-413:
-----------------------------------
    Fix Version/s:     (was: 0.9)
                   1.0

> Support creation of dynamic columns within Gora datastore mapping designs
> -------------------------------------------------------------------------
>
>                 Key: GORA-413
>                 URL: https://issues.apache.org/jira/browse/GORA-413
>             Project: Apache Gora
>          Issue Type: New Feature
>          Components: gora-hbase
>    Affects Versions: 0.6
>            Reporter: Lewis John McGibbney
>            Priority: Major
>             Fix For: 1.0
>
>
> The conversation taking place on [dynamically generating HBase columns|http://www.mail-archive.com/dev%40gora.apache.org/msg05754.html]
has raised an issue that new functionality needs to be added in order to achieve this.
> The main driver for this issue coming to light is that Chukwa logs need to dynamically
create many many columns over time directly dependent on the number of data chunks we get.
Each data chunk has a [Sequence ID], this sequenceID should be the column name.
> The table design will look like this
> {code}
> Row Key: [Invert Date]:[Data Type]:[Primary Key]
> Column Family: log
> Column Name: [Sequence ID]
> Timestamp: [log entry timestamp]
> Example:
> Row Key: 2132013102:TT:host1.example.com
> Column Family: log
> Column Name: 1230
> Cell Value: 2013-01-23 12:01:30 INFO This is a log entry.
> Timestamp: 1358942490
> {code}
> The inverted date allow the table to be partitioned by hour or day of the month or month
more easily.
> The usage of column name for consecutive sequence to allow fast retrieval in a linear
scan. This format is typically good for retrieve a hour worth of logs fast for a node. Hence,
if we are doing batch scanning of the table in a rolling window via map reduce job at every
hour interval, we get a even spread the work load to multiple map reduce tasks.



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