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https://issues.apache.org/jira/browse/HBASE-23887?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17127551#comment-17127551
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Danil Lipovoy commented on HBASE-23887:
---------------------------------------
Another one test - I wanted to see how to will work auto-scaling when we have
changing load. So I run this scenario
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 5 -p fieldcount=1 -p operationcount=40000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 15 -p fieldcount=1 -p operationcount=60000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 5 -p fieldcount=1 -p operationcount=40000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 5 -p fieldcount=1 -p operationcount=40000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 20 -p fieldcount=1 -p operationcount=50000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 5 -p fieldcount=1 -p operationcount=20000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 5 -p fieldcount=1 -p operationcount=10000 -s -t &
sleep 100
nohup bin/ycsb run hbase2 -cp ~/hbase_conf -P workloads/select_u -p table=tbl4
-p columnfamily=cf -threads 10 -p fieldcount=1 -p operationcount=60000 -s -t &
with param:
hbase.lru.cache.heavy.eviction.count.limit = 100000 ( = disable the feature)
Then I set:
hbase.lru.cache.heavy.eviction.count.limit = 0
And have done almost the same scenario just set "sleep 50" because it works
faster. The results:
!wave.png!
!image-2020-06-07-12-07-30-307.png!
How it looks in the log:
BlockCache evicted (MB): 0, overhead (%): -100, heavy eviction counter: 0,
current caching DataBlock (%): 100
BlockCache evicted (MB): 0, overhead (%): -100, heavy eviction counter: 0,
current caching DataBlock (%): 100
BlockCache evicted (MB): 0, overhead (%): -100, heavy eviction counter: 0,
current caching DataBlock (%): 100
BlockCache evicted (MB): 5472, overhead (%): 2636, heavy eviction counter: 1,
current caching DataBlock (%): 85 < test begin
BlockCache evicted (MB): 6498, overhead (%): 3149, heavy eviction counter: 2,
current caching DataBlock (%): 70
BlockCache evicted (MB): 5017, overhead (%): 2408, heavy eviction counter: 3,
current caching DataBlock (%): 55
BlockCache evicted (MB): 3990, overhead (%): 1895, heavy eviction counter: 4,
current caching DataBlock (%): 40
BlockCache evicted (MB): 2623, overhead (%): 1211, heavy eviction counter: 5,
current caching DataBlock (%): 28
BlockCache evicted (MB): 2166, overhead (%): 983, heavy eviction counter: 6,
current caching DataBlock (%): 19
BlockCache evicted (MB): 1254, overhead (%): 527, heavy eviction counter: 7,
current caching DataBlock (%): 14
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 8,
current caching DataBlock (%): 13
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 9,
current caching DataBlock (%): 13
BlockCache evicted (MB): 114, overhead (%): -43, heavy eviction counter: 9,
current caching DataBlock (%): 18
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 10,
current caching DataBlock (%): 17
BlockCache evicted (MB): 342, overhead (%): 71, heavy eviction counter: 11,
current caching DataBlock (%): 17
BlockCache evicted (MB): 342, overhead (%): 71, heavy eviction counter: 12,
current caching DataBlock (%): 17
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 13,
current caching DataBlock (%): 17
BlockCache evicted (MB): 114, overhead (%): -43, heavy eviction counter: 13,
current caching DataBlock (%): 22
BlockCache evicted (MB): 798, overhead (%): 299, heavy eviction counter: 14,
current caching DataBlock (%): 20
BlockCache evicted (MB): 684, overhead (%): 242, heavy eviction counter: 15,
current caching DataBlock (%): 18
BlockCache evicted (MB): 570, overhead (%): 185, heavy eviction counter: 16,
current caching DataBlock (%): 17
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 17,
current caching DataBlock (%): 16
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 18,
current caching DataBlock (%): 16
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 19,
current caching DataBlock (%): 16
BlockCache evicted (MB): 114, overhead (%): -43, heavy eviction counter: 19,
current caching DataBlock (%): 21
BlockCache evicted (MB): 684, overhead (%): 242, heavy eviction counter: 20,
current caching DataBlock (%): 19
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 21,
current caching DataBlock (%): 18
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 22,
current caching DataBlock (%): 17
BlockCache evicted (MB): 342, overhead (%): 71, heavy eviction counter: 23,
current caching DataBlock (%): 17
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 24,
current caching DataBlock (%): 17
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 25,
current caching DataBlock (%): 17
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 26,
current caching DataBlock (%): 17
BlockCache evicted (MB): 114, overhead (%): -43, heavy eviction counter: 26,
current caching DataBlock (%): 22
BlockCache evicted (MB): 684, overhead (%): 242, heavy eviction counter: 27,
current caching DataBlock (%): 20
BlockCache evicted (MB): 570, overhead (%): 185, heavy eviction counter: 28,
current caching DataBlock (%): 19
BlockCache evicted (MB): 570, overhead (%): 185, heavy eviction counter: 29,
current caching DataBlock (%): 18
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 30,
current caching DataBlock (%): 17
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 31,
current caching DataBlock (%): 16
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 32,
current caching DataBlock (%): 16
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 33,
current caching DataBlock (%): 16
BlockCache evicted (MB): 114, overhead (%): -43, heavy eviction counter: 33,
current caching DataBlock (%): 21
BlockCache evicted (MB): 684, overhead (%): 242, heavy eviction counter: 34,
current caching DataBlock (%): 19
BlockCache evicted (MB): 684, overhead (%): 242, heavy eviction counter: 35,
current caching DataBlock (%): 17
BlockCache evicted (MB): 456, overhead (%): 128, heavy eviction counter: 36,
current caching DataBlock (%): 16
BlockCache evicted (MB): 342, overhead (%): 71, heavy eviction counter: 37,
current caching DataBlock (%): 16
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 38,
current caching DataBlock (%): 16
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 39,
current caching DataBlock (%): 16
BlockCache evicted (MB): 114, overhead (%): -43, heavy eviction counter: 39,
current caching DataBlock (%): 21
BlockCache evicted (MB): 684, overhead (%): 242, heavy eviction counter: 40,
current caching DataBlock (%): 19
BlockCache evicted (MB): 228, overhead (%): 14, heavy eviction counter: 41,
current caching DataBlock (%): 19
BlockCache evicted (MB): 0, overhead (%): -100, heavy eviction counter: 0,
current caching DataBlock (%): 100 < finish
BlockCache evicted (MB): 0, overhead (%): -100, heavy eviction counter: 0,
current caching DataBlock (%): 100
Looks all is fine. Can we merge PR?
> BlockCache performance improve by reduce eviction rate
> ------------------------------------------------------
>
> Key: HBASE-23887
> URL: https://issues.apache.org/jira/browse/HBASE-23887
> Project: HBase
> Issue Type: Improvement
> Components: BlockCache, Performance
> Reporter: Danil Lipovoy
> Priority: Minor
> Attachments: 1582787018434_rs_metrics.jpg,
> 1582801838065_rs_metrics_new.png, BC_LongRun.png,
> BlockCacheEvictionProcess.gif, cmp.png, evict_BC100_vs_BC23.png,
> eviction_100p.png, eviction_100p.png, eviction_100p.png, gc_100p.png,
> graph.png, image-2020-06-07-08-11-11-929.png,
> image-2020-06-07-08-19-00-922.png, image-2020-06-07-12-07-24-903.png,
> image-2020-06-07-12-07-30-307.png, read_requests_100pBC_vs_23pBC.png,
> requests_100p.png, requests_100p.png, requests_new2_100p.png,
> requests_new_100p.png, scan.png, wave.png
>
>
> Hi!
> I first time here, correct me please if something wrong.
> I want propose how to improve performance when data in HFiles much more than
> BlockChache (usual story in BigData). The idea - caching only part of DATA
> blocks. It is good becouse LruBlockCache starts to work and save huge amount
> of GC.
> Sometimes we have more data than can fit into BlockCache and it is cause a
> high rate of evictions. In this case we can skip cache a block N and insted
> cache the N+1th block. Anyway we would evict N block quite soon and that why
> that skipping good for performance.
> Example:
> Imagine we have little cache, just can fit only 1 block and we are trying to
> read 3 blocks with offsets:
> 124
> 198
> 223
> Current way - we put the block 124, then put 198, evict 124, put 223, evict
> 198. A lot of work (5 actions).
> With the feature - last few digits evenly distributed from 0 to 99. When we
> divide by modulus we got:
> 124 -> 24
> 198 -> 98
> 223 -> 23
> It helps to sort them. Some part, for example below 50 (if we set
> *hbase.lru.cache.data.block.percent* = 50) go into the cache. And skip
> others. It means we will not try to handle the block 198 and save CPU for
> other job. In the result - we put block 124, then put 223, evict 124 (3
> actions).
> See the picture in attachment with test below. Requests per second is higher,
> GC is lower.
>
> The key point of the code:
> Added the parameter: *hbase.lru.cache.data.block.percent* which by default =
> 100
>
> But if we set it 1-99, then will work the next logic:
>
>
> {code:java}
> public void cacheBlock(BlockCacheKey cacheKey, Cacheable buf, boolean
> inMemory) {
> if (cacheDataBlockPercent != 100 && buf.getBlockType().isData())
> if (cacheKey.getOffset() % 100 >= cacheDataBlockPercent)
> return;
> ...
> // the same code as usual
> }
> {code}
>
> Other parameters help to control when this logic will be enabled. It means it
> will work only while heavy reading going on.
> hbase.lru.cache.heavy.eviction.count.limit - set how many times have to run
> eviction process that start to avoid of putting data to BlockCache
> hbase.lru.cache.heavy.eviction.bytes.size.limit - set how many bytes have to
> evicted each time that start to avoid of putting data to BlockCache
> By default: if 10 times (100 secunds) evicted more than 10 MB (each time)
> then we start to skip 50% of data blocks.
> When heavy evitions process end then new logic off and will put into
> BlockCache all blocks again.
>
> Descriptions of the test:
> 4 nodes E5-2698 v4 @ 2.20GHz, 700 Gb Mem.
> 4 RegionServers
> 4 tables by 64 regions by 1.88 Gb data in each = 600 Gb total (only FAST_DIFF)
> Total BlockCache Size = 48 Gb (8 % of data in HFiles)
> Random read in 20 threads
>
> I am going to make Pull Request, hope it is right way to make some
> contribution in this cool product.
>
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