Junping Du commented on YARN-3134:

I would like to raise an important issue for reusing JDBC connections in 
It sounds like we only release/close these JDBC connections until the writer 
get stopped. Given the writer's lifecycle is the same as 
TimelineCollectorManager (at current design which could be changed due to 
discussions above) which means it almost the same as RM or NM. It also means we 
don't close/release any JDBC connections in the whole lifecycle of NM/RM. It 
doesn't sounds right as the resource of JDBC connections is pretty expensive 
and very limited (in traditional DB case), phoenix could be better as the 
client only server for local node. However, it could still be expensive when 
large app number especially for RMTimelineCollectorManager.  
In addition, sounds like our cache the connection per thread is also 
problematic: these threads are coming from each collectors, we cache them in a 
Hashmap which could live forever that could affect the GC of these collectors 
even these collectors should be removed when application get finished.    

> [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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