大数据应用之HBase数据插入性能优化实测教程

时间:2021-02-21 00:26:11

引言:

  大家在使用HBase的过程中,总是面临性能优化的问题,本文从HBase客户端参数设置的角度,研究HBase客户端数据批量插入性能优化的问题。事实胜于雄辩,数据比理论更有说服力,基于此,作者设计了这么一个HBase数据插入性能优化实测实验,希望大家用自己的服务器跑出的结果,给自己一个值得信服的结论。

一、客户单优化参数

  1.Put List Size
  HBase的Put支持单条插入,也支持批量插入。

  2. AutoFlush  
  AutoFlush指的是在每次调用HBase的Put操作,是否提交到HBase Server。 默认是true,每次会提交。如果此时是单条插入,就会有更多的IO,从而降低性能

  3.Write Buffer Size
  Write Buffer Size在AutoFlush为false的时候起作用,默认是2MB,也就是当插入数据超过2MB,就会自动提交到Server

  4.WAL
  WAL是Write Ahead Log的缩写,指的是HBase在插入操作前是否写Log。默认是打开,关掉会提高性能,但是如果系统出现故障(负责插入的Region Server  挂掉),数据可能会丢失。

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参数

默认值

说明

JVM Heap Size

平台不同值不同自行设置

AutoFlush

True

默认逐条提交

Put List Size

1

支持逐条和批量

Write Buffer Size

2M

与autoflush配合使用

Write Ahead Log

True

默认开启,需要手动关闭

二、源码程序

 import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Random; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.HColumnDescriptor;
import org.apache.hadoop.hbase.HTableDescriptor;
import org.apache.hadoop.hbase.KeyValue;
import org.apache.hadoop.hbase.MasterNotRunningException;
import org.apache.hadoop.hbase.ZooKeeperConnectionException;
import org.apache.hadoop.hbase.client.Delete;
import org.apache.hadoop.hbase.client.Get;
import org.apache.hadoop.hbase.client.HBaseAdmin;
import org.apache.hadoop.hbase.client.HTable;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.ResultScanner;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.util.Bytes; /*
* -------优化案例说明------------
* 1.优化参数1:Autoflush 默认关闭,需要手动开启
* 2.优化参数2:put list size 支持单条与批量
* 3.优化参数3:JVM heap size 默认值是平台而不同,需要手动设置
* 4.优化参数4:Write Buffer Size 默认值2M
* 5.优化参数5:Write Ahead Log 默认开启,需要手动关闭
* */ public class TestInsert {
static Configuration hbaseConfig = null; public static void main(String[] args) throws Exception {
Configuration HBASE_CONFIG = new Configuration();
HBASE_CONFIG.set("hbase.master", "192.168.230.133:60000");
HBASE_CONFIG.set("hbase.zookeeper.quorum", "192.168.230.133");
HBASE_CONFIG.set("hbase.zookeeper.property.clientPort", "2181");
hbaseConfig = HBaseConfiguration.create(HBASE_CONFIG);
//关闭wal,autoflush,writebuffer = 24M
insert(false,false,1024*1024*24);
//开启AutoFlush,writebuffer = 0
insert(false,true,0);
//默认值,全部开启
insert(true,true,0);
} private static void insert(boolean wal,boolean autoFlush,long writeBuffer)
throws IOException {
String tableName="etltest";
HBaseAdmin hAdmin = new HBaseAdmin(hbaseConfig);
if (hAdmin.tableExists(tableName)) {
hAdmin.disableTable(tableName);
hAdmin.deleteTable(tableName);
} HTableDescriptor t = new HTableDescriptor(tableName);
t.addFamily(new HColumnDescriptor("f1"));
t.addFamily(new HColumnDescriptor("f2"));
t.addFamily(new HColumnDescriptor("f3"));
t.addFamily(new HColumnDescriptor("f4"));
hAdmin.createTable(t);
System.out.println("table created"); HTable table = new HTable(hbaseConfig, tableName);
table.setAutoFlush(autoFlush);
if(writeBuffer!=0){
table.setWriteBufferSize(writeBuffer);
}
List<Put> lp = new ArrayList<Put>();
long all = System.currentTimeMillis(); System.out.println("start time = "+all);
int count = 20000;
byte[] buffer = new byte[128];
Random r = new Random();
for (int i = 1; i <= count; ++i) {
Put p = new Put(String.format("row d",i).getBytes());
r.nextBytes(buffer);
p.add("f1".getBytes(), null, buffer);
p.add("f2".getBytes(), null, buffer);
p.add("f3".getBytes(), null, buffer);
p.add("f4".getBytes(), null, buffer);
p.setWriteToWAL(wal);
lp.add(p);
if(i%1000 == 0){
table.put(lp);
lp.clear();
}
} System.out.println("WAL="+wal+",autoFlush="+autoFlush+",buffer="+writeBuffer+",count="+count);
long end = System.currentTimeMillis();
System.out.println("total need time = "+ (end - all)*1.0/1000+"s"); System.out.println("insert complete"+",costs:"+(System.currentTimeMillis()-all)*1.0/1000+"ms");
}
}

三、集群配置

3.1 服务器硬件配置清单

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序号

节点名称

CUP

内存

硬盘

带宽

1

HMaster

2

HregionServer1

3

HregionServer2

4

5

6

7

3.2 客户端硬件配置清单

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设备

节点名称

Cpu

内存

硬盘

带宽

四、测试报告

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数据量

JVM

AutoFlush

Put List Size

WriteBufferSize

WAL

耗时

1000

512m

false

1000

1024*1024*24

false

2000

5000

10000

20000

50000

100000

200000

500000

100000

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