Vrushali C commented on YARN-3134:

Hi [~gtCarrera9]

bq. in the current version I've not implemented isRelatedTo and relatesTo. I 
can certainly add this section if it's required for the performance benchmark.
Yes, I think for the PoC we should write everything that the TimelineEntity 
class has to the backend store. 

bq.  My current plan is to use the metrics precision table for aggregations, 
and just use the aggregated data for Phoenix SQL queries.
Okay, I see, (for my understanding) how would the query for say, a map task 
level metrics be? There won't be any aggregation at that level, no? 
Also I am wondering how this metrics timeseries information would be queried. 
Could you please explain how the timestamps are stored? 

> [Storage implementation] Exploiting the option of using Phoenix to access 
> HBase backend
> ---------------------------------------------------------------------------------------
>                 Key: YARN-3134
>                 URL: https://issues.apache.org/jira/browse/YARN-3134
>             Project: Hadoop YARN
>          Issue Type: Sub-task
>          Components: timelineserver
>            Reporter: Zhijie Shen
>            Assignee: Li Lu
>         Attachments: YARN-3134-040915_poc.patch, YARN-3134-041015_poc.patch, 
> YARN-3134-041415_poc.patch, YARN-3134-042115.patch, YARN-3134DataSchema.pdf
> Quote the introduction on Phoenix web page:
> {code}
> Apache Phoenix is a relational database layer over HBase delivered as a 
> client-embedded JDBC driver targeting low latency queries over HBase data. 
> Apache Phoenix takes your SQL query, compiles it into a series of HBase 
> scans, and orchestrates the running of those scans to produce regular JDBC 
> result sets. The table metadata is stored in an HBase table and versioned, 
> such that snapshot queries over prior versions will automatically use the 
> correct schema. Direct use of the HBase API, along with coprocessors and 
> custom filters, results in performance on the order of milliseconds for small 
> queries, or seconds for tens of millions of rows.
> {code}
> It may simply our implementation read/write data from/to HBase, and can 
> easily build index and compose complex query.

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