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https://issues.apache.org/jira/browse/YARN-3134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14531398#comment-14531398
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Zhijie Shen commented on YARN-3134:
-----------------------------------
Some more comments:
1. Maybe it's better to commit the batch per entity. Otherwise, if one entity
has some I/O error, all entities in this write call will be failed?
{code}
186 storeMetrics(entity, currContext, conn);
187 }
188 ps.executeBatch();
189 conn.commit();
{code}
2. stmt doesn't need to be closed explicitly, but conn still does, right?
{code}
277 conn.commit();
278 } catch (SQLException se) {
279 LOG.error("Failed in init data " + se.getLocalizedMessage());
280 throw se;
281 }
{code}
3. Many of PhoenixTimelineWriterImpl private functions can be static.
bq. except for two points
I'm okay if we want to defer it as the future stabilization work.
> [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
> Labels: BB2015-05-TBR
> Attachments: SettingupPhoenixstorageforatimelinev2end-to-endtest.pdf,
> YARN-3134-040915_poc.patch, YARN-3134-041015_poc.patch,
> YARN-3134-041415_poc.patch, YARN-3134-042115.patch, YARN-3134-042715.patch,
> YARN-3134-YARN-2928.001.patch, YARN-3134-YARN-2928.002.patch,
> YARN-3134-YARN-2928.003.patch, YARN-3134-YARN-2928.004.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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