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https://issues.apache.org/jira/browse/HBASE-13071?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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stack updated HBASE-13071:
--------------------------
Release Note:
Motivation
A pipelined scan API is introduced for speeding up applications that combine
massive data traversal with compute-intensive processing. Traditional HBase
scans save network trips through prefetching the data to the client side cache.
However, they prefetch synchronously: the fetch request to regionserver is
invoked only when the entire cache is consumed. This leads to a stop-and-wait
access pattern, in which the client stalls until the next chunk of data is
fetched. Applications that do significant processing can benefit from
background data prefetching, which eliminates this bottleneck. The pipelined
scan implementation overlaps the cache population at the client side with
application processing. Namely, it issues a new scan RPC when the iteration
retrieves 50% of the cache. If the application processing (that is, the time
between invocations of next()) is substantial, the new chunk of data will be
available before the previous one is exhausted, and the client will not
experience any delay. Ideally, the prefetch and the processing times should be
balanced.
API and Configuration
Asynchronous scanning can be configured either globally for all tables and
scans, or on per-scan basis via a new Scan class API.
* Configuration in hbase-site.xml - hbase.client.scanner.async.prefetch,
default false:
{code}
<property>
<name>hbase.client.scanner.async.prefetch</name>
<value>true</value>
</property>
{code}
* API - Scan#setAsyncPrefetch(boolean)
{code}
Scan scan = new Scan();
scan.setCaching(1000);
scan.getMaxResultSize(BIG_SIZE);
scan.setAsyncPrefetch(true);
...
ResultScanner scanner = table.getScanner(scan);
{code}
Implementation Notes
Pipelined scan is implemented by a new ClientAsyncPrefetchScanner class, which
is fully API-compatible with the synchronous ClientSimpleScanner.
ClientAsyncPrefetchScanner is not instantiated in case of small (Scan#setSmall)
and reversed (Scan#setReversed) scanners. The application is responsible for
setting the prefetch size in a way that the prefetch time and the processing
times are balanced. Note that due to double buffering, the client side cache
can use twice as much memory as the synchronous scanner.
> Hbase Streaming Scan Feature
> ----------------------------
>
> Key: HBASE-13071
> URL: https://issues.apache.org/jira/browse/HBASE-13071
> Project: HBase
> Issue Type: New Feature
> Reporter: Eshcar Hillel
> Assignee: Eshcar Hillel
> Attachments: 99.eshcar.png, HBASE-13071_98_1.patch,
> HBASE-13071_trunk_1.patch, HBASE-13071_trunk_10.patch,
> HBASE-13071_trunk_2.patch, HBASE-13071_trunk_3.patch,
> HBASE-13071_trunk_4.patch, HBASE-13071_trunk_5.patch,
> HBASE-13071_trunk_6.patch, HBASE-13071_trunk_7.patch,
> HBASE-13071_trunk_8.patch, HBASE-13071_trunk_9.patch,
> HBASE-13071_trunk_rebase_1.0.patch, HBASE-13071_trunk_rebase_2.0.patch,
> HBaseStreamingScanDesign.pdf, HbaseStreamingScanEvaluation.pdf,
> HbaseStreamingScanEvaluationwithMultipleClients.pdf, Releasenote-13071.txt,
> gc.delay.png, gc.eshcar.png, gc.png, hits.delay.png, hits.eshcar.png,
> hits.png, latency.delay.png, latency.png, network.png
>
>
> A scan operation iterates over all rows of a table or a subrange of the
> table. The synchronous nature in which the data is served at the client side
> hinders the speed the application traverses the data: it increases the
> overall processing time, and may cause a great variance in the times the
> application waits for the next piece of data.
> The scanner next() method at the client side invokes an RPC to the
> regionserver and then stores the results in a cache. The application can
> specify how many rows will be transmitted per RPC; by default this is set to
> 100 rows.
> The cache can be considered as a producer-consumer queue, where the hbase
> client pushes the data to the queue and the application consumes it.
> Currently this queue is synchronous, i.e., blocking. More specifically, when
> the application consumed all the data from the cache --- so the cache is
> empty --- the hbase client retrieves additional data from the server and
> re-fills the cache with new data. During this time the application is blocked.
> Under the assumption that the application processing time can be balanced by
> the time it takes to retrieve the data, an asynchronous approach can reduce
> the time the application is waiting for data.
> We attach a design document.
> We also have a patch that is based on a private branch, and some evaluation
> results of this code.
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