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https://issues.apache.org/jira/browse/HDFS-15202?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17054897#comment-17054897
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Danil Lipovoy edited comment on HDFS-15202 at 3/9/20, 1:32 PM:
---------------------------------------------------------------
Done more tests. There were test via HBase. More clean just read direct:
{code:java}
conf.set("dfs.client.read.shortcircuit", "true");
conf.set("dfs.client.read.shortcircuit.buffer.size", "65536"); // by default 1
Mb and it is bad for performance. By the way maybe decrease default value too?
conf.set("dfs.client.short.circuit.num", num); // from 1 to 10
...
FSDataInputStream in = fileSystem.open(path);
for (int i = 0; i < count; i++) {
position += 65536;
if (position > 900000000)
position = 0L;
int res = in.read(position, byteBuffer, 0, 65536);
}
{code}
This code is executed in separate threads and we will increase the number of
simultaneously reading files (from 10 to 200 - the horizontal axis) and the
number of caches (from 1 to 10 - lines). The vertical axis shows the
acceleration that gives an increase in SSC relative to the case when there is
only one cache.
!hdfs_scc_test_full-cycle.png!
!HDFS_CPU_full_cycle.png!
was (Author: pustota):
Done more tests. There were test via HBase. More clean just read direct:
{code:java}
conf.set("dfs.client.read.shortcircuit", "true");
conf.set("dfs.client.read.shortcircuit.buffer.size", "65536"); // by default 1
Mb and it is too much
conf.set("dfs.client.short.circuit.num", num); // from 1 to 10
...
FSDataInputStream in = fileSystem.open(path);
for (int i = 0; i < count; i++) {
position += 65536;
if (position > 900000000)
position = 0L;
int res = in.read(position, byteBuffer, 0, 65536);
}
{code}
This code is executed in separate threads and we will increase the number of
simultaneously reading files (from 10 to 200 - the horizontal axis) and the
number of caches (from 1 to 10 - lines). The vertical axis shows the
acceleration that gives an increase in SSC relative to the case when there is
only one cache.
!hdfs_scc_test_full-cycle.png!
!HDFS_CPU_full_cycle.png!
> HDFS-client: boost ShortCircuit Cache
> -------------------------------------
>
> Key: HDFS-15202
> URL: https://issues.apache.org/jira/browse/HDFS-15202
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: dfsclient
> Environment: 4 nodes E5-2698 v4 @ 2.20GHz, 700 Gb Mem.
> 8 RegionServers (2 by host)
> 8 tables by 64 regions by 1.88 Gb data in each = 900 Gb total
> Random read in 800 threads via YCSB and a little bit updates (10% of reads)
> Reporter: Danil Lipovoy
> Assignee: Danil Lipovoy
> Priority: Minor
> Attachments: HDFS_CPU_full_cycle.png, cpu_SSC.png, cpu_SSC2.png,
> hdfs_cpu.png, hdfs_reads.png, hdfs_scc_3_test.png,
> hdfs_scc_test_full-cycle.png, locks.png, requests_SSC.png
>
>
> ТотI want to propose how to improve reading performance HDFS-client. The
> idea: create few instances ShortCircuit caches instead of one.
> The key points:
> 1. Create array of caches (set by
> clientShortCircuitNum=*dfs.client.short.circuit.num*, see in the pull
> requests below):
> {code:java}
> private ClientContext(String name, DfsClientConf conf, Configuration config) {
> ...
> shortCircuitCache = new ShortCircuitCache[this.clientShortCircuitNum];
> for (int i = 0; i < this.clientShortCircuitNum; i++) {
> this.shortCircuitCache[i] = ShortCircuitCache.fromConf(scConf);
> }
> {code}
> 2 Then divide blocks by caches:
> {code:java}
> public ShortCircuitCache getShortCircuitCache(long idx) {
> return shortCircuitCache[(int) (idx % clientShortCircuitNum)];
> }
> {code}
> 3. And how to call it:
> {code:java}
> ShortCircuitCache cache =
> clientContext.getShortCircuitCache(block.getBlockId());
> {code}
> The last number of offset evenly distributed from 0 to 9 - that's why all
> caches will full approximately the same.
> It is good for performance. Below the attachment, it is load test reading
> HDFS via HBase where clientShortCircuitNum = 1 vs 3. We can see that
> performance grows ~30%, CPU usage about +15%.
> Hope it is interesting for someone.
> Ready to explain some unobvious things.
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