hbase compression benchmark

hbase compression benchmark

Author: sel-fish
Date: 2016/05/16

Background

  • Use hbase to store cold data. In the meantime, provide realtime search service
  • Less disk space is better. To achieve that target, I need to open compression in hbase and erasure code in hdfs
  • The result I can get from google is too old, like 3 or 4 years ago

Compression Algorithm

create 'table1', {NAME => 'cf', COMPRESSION => ‘ZLIB'}, {SPLITS => (1..n_splits).map {|i| "user#{1000+i*(9999-1000)/n_splits}"}}

ERROR: Compression ZLIB is not supported. Use one of LZ4 SNAPPY LZO GZ NONE

As I tried to use ZLIB as my compression alg, I got such error. I hope to test all those options, but I choose SNAPPY/GZ/NONE first to get an optional solution ASAP.

  • NONE
  • SNAPPY
  • GZ

First

I use YCSB to insert 1000000 rows to 'table1', each of them has 8 fields, and the length of field is 256 Bytes. Thus, every row is 2 Kilobytes.
The following is my YCSB workload.
So, the total size of user data is 100000 * 2 KB = 2 Gigabytes

recordcount=1000000
operationcount=5000000
workload=com.yahoo.ycsb.workloads.CoreWorkload
fieldlength=256
fieldcount=8

readallfields=true

readproportion=1
updateproportion=0
scanproportion=0
insertproportion=0

requestdistribution=zipfian

columnfamily=cf
table=table1

The command I use to create table with compression GZ :

n_splits = 40

create 'table1', {NAME => 'cf', COMPRESSION => ‘GZ'}, {SPLITS => (1..n_splits).map {|i| "user#{1000+i*(9999-1000)/n_splits}"}}

with None :

n_splits = 40

create 'table1', {NAME => 'cf'}, {SPLITS => (1..n_splits).map {|i| "user#{1000+i*(9999-1000)/n_splits}"}}

The result I got is :

| CompressionAlg |DFS used|Storage amplification factor|
|----------|:------:|
|NONE|15.21 GB|7.1|
|GZ|12.66 GB|6.3|

So confused about that result, even I have 3 replications in dfs, that's far more beyond acceptable.
I wonder maybe my data is too small and the meta info ocuppy a lot of space.

I got the following questions in my mind:

  1. after I inserted 1M rows with no compression, the dfs used is only 7G, but after I disable the table and restart hbase, the usage grows to 15.22G
  2. after I drop the table, the usage not release until a period of time passed
  3. why the storage amplification factor so big

Hope that I can get the answer.

Second

As I increased my row counts to 10000000, this problem exists as well, so I started to wonder maybe I shouldn't control the split..

$ du -sh hbase
42G hbase

DFS Used: 124.5 GB (3.46%)

restart test, create table without pre split :

create 'table1', {NAME => 'cf'}

Problem still exists. Then I directly test dd on hdfs :

dd if=/dev/zero bs=1024 count=1000000 of=file_1GB

The usage is precisely 3GB. So I think that's a problem inside hbase, nothing to do with dfs.

But after a very long period of time :

$ du -sh hbase
2.4G    hbase

DFS Used: 7.13 GB (0.2%)

So maybe I should wait for a while after insert ?

create 'table1', {NAME => 'cf', COMPRESSION => 'GZ'}

Right after inserted rows, got the usage :

[fenqi@guomai031119 /home/fenqi/hdfs_mount_point] 13:40
$ du -sh hbase/
6.8G    hbase/

[fenqi@guomai031119 /home/fenqi/hdfs_mount_point] 13:40
$ cd hbase/

[fenqi@guomai031119 /home/fenqi/hdfs_mount_point/hbase] 13:40
$ du -sh *
1.5G    archive
3.1G    data
0       hbase.id
0       hbase.version
7.0K    MasterProcWALs
2.1G    oldWALs
244M    WALs

Then, it seems some data move from 'data' to 'archive' :

3.4G    archive
1.6G    data
0       hbase.id
0       hbase.version
4.0K    MasterProcWALs
2.1G    oldWALs
244M    WALs
$ du -sh hbase/
1.9G    hbase/

DFS Used: 5.86 GB (0.16%)

Continue with snappy :

create 'table1', {NAME => 'cf', COMPRESSION => 'SNAPPY'}

But the disk usage is as same as when use no compresssion :

$ du -sh hbase/
2.2G    hbase/

DFS Used: 6.85 GB (0.19%)

| CompressionAlg |DFS used|Storage amplification factor|
|----------|:------:|
|NONE|7.43 GB|3.7|
|GZ|5.86 GB|2.9|
|SNAPPY|6.85 GB|3.4|

以上

最后编辑于
©著作权归作者所有,转载或内容合作请联系作者
  • 序言:七十年代末,一起剥皮案震惊了整个滨河市,随后出现的几起案子,更是在滨河造成了极大的恐慌,老刑警刘岩,带你破解...
    沈念sama阅读 203,324评论 5 476
  • 序言:滨河连续发生了三起死亡事件,死亡现场离奇诡异,居然都是意外死亡,警方通过查阅死者的电脑和手机,发现死者居然都...
    沈念sama阅读 85,303评论 2 381
  • 文/潘晓璐 我一进店门,熙熙楼的掌柜王于贵愁眉苦脸地迎上来,“玉大人,你说我怎么就摊上这事。” “怎么了?”我有些...
    开封第一讲书人阅读 150,192评论 0 337
  • 文/不坏的土叔 我叫张陵,是天一观的道长。 经常有香客问我,道长,这世上最难降的妖魔是什么? 我笑而不...
    开封第一讲书人阅读 54,555评论 1 273
  • 正文 为了忘掉前任,我火速办了婚礼,结果婚礼上,老公的妹妹穿的比我还像新娘。我一直安慰自己,他们只是感情好,可当我...
    茶点故事阅读 63,569评论 5 365
  • 文/花漫 我一把揭开白布。 她就那样静静地躺着,像睡着了一般。 火红的嫁衣衬着肌肤如雪。 梳的纹丝不乱的头发上,一...
    开封第一讲书人阅读 48,566评论 1 281
  • 那天,我揣着相机与录音,去河边找鬼。 笑死,一个胖子当着我的面吹牛,可吹牛的内容都是我干的。 我是一名探鬼主播,决...
    沈念sama阅读 37,927评论 3 395
  • 文/苍兰香墨 我猛地睁开眼,长吁一口气:“原来是场噩梦啊……” “哼!你这毒妇竟也来了?” 一声冷哼从身侧响起,我...
    开封第一讲书人阅读 36,583评论 0 257
  • 序言:老挝万荣一对情侣失踪,失踪者是张志新(化名)和其女友刘颖,没想到半个月后,有当地人在树林里发现了一具尸体,经...
    沈念sama阅读 40,827评论 1 297
  • 正文 独居荒郊野岭守林人离奇死亡,尸身上长有42处带血的脓包…… 初始之章·张勋 以下内容为张勋视角 年9月15日...
    茶点故事阅读 35,590评论 2 320
  • 正文 我和宋清朗相恋三年,在试婚纱的时候发现自己被绿了。 大学时的朋友给我发了我未婚夫和他白月光在一起吃饭的照片。...
    茶点故事阅读 37,669评论 1 329
  • 序言:一个原本活蹦乱跳的男人离奇死亡,死状恐怖,灵堂内的尸体忽然破棺而出,到底是诈尸还是另有隐情,我是刑警宁泽,带...
    沈念sama阅读 33,365评论 4 318
  • 正文 年R本政府宣布,位于F岛的核电站,受9级特大地震影响,放射性物质发生泄漏。R本人自食恶果不足惜,却给世界环境...
    茶点故事阅读 38,941评论 3 307
  • 文/蒙蒙 一、第九天 我趴在偏房一处隐蔽的房顶上张望。 院中可真热闹,春花似锦、人声如沸。这庄子的主人今日做“春日...
    开封第一讲书人阅读 29,928评论 0 19
  • 文/苍兰香墨 我抬头看了看天上的太阳。三九已至,却和暖如春,着一层夹袄步出监牢的瞬间,已是汗流浃背。 一阵脚步声响...
    开封第一讲书人阅读 31,159评论 1 259
  • 我被黑心中介骗来泰国打工, 没想到刚下飞机就差点儿被人妖公主榨干…… 1. 我叫王不留,地道东北人。 一个月前我还...
    沈念sama阅读 42,880评论 2 349
  • 正文 我出身青楼,却偏偏与公主长得像,于是被迫代替她去往敌国和亲。 传闻我的和亲对象是个残疾皇子,可洞房花烛夜当晚...
    茶点故事阅读 42,399评论 2 342

推荐阅读更多精彩内容