启动

zookeeper----》hadoop----》hbase

创建hbase表student

create 'student' ，'info'

添加数据

put 'student' ，'1' ，'info:name','James'

put 'student' ，'1' ，'info:age','23'

put 'student' ，'1' ，'info:gender','F'

put 'student' ，'2' ，'info:name','Smith'

put 'student' ，'2' ，'info:age','24'

put 'student' ，'2' ，'info:gender','M'

根据rowkey查询一条记录

get 'student','1'

读取hbase数据，在mycode目录下创建SparkOperateHBase.py文件，添加如下代码

#!/usr/bin/env python3

from pyspark import SparkConf,SparkContext

conf = SparkConf().setMaster('local').setAppName("ReadHBase")
sc = SparkContext(conf = conf)
host = 'localhost'
table = 'student'
conf = {"hbase.zookeeper.quorum": host,"hbase.mapreduce.inputtable": table}
keyConv = "org.apache.spark.examples.pythonconverters.ImmutableBytesWritableToStringConverter"
valueConv="org.apache.spark.examples.pythonconverters,HBaseResultToStringConverter"
hbase_rdd=sc.newAPIHadoopRDD("org.apache.hadoop.hbase.mapreduce.TableInputFormat","org.apache.hadoop.hbase.io.ImmutableBytesWritable","org.apache.hadoop.hbase.client.Result",keyConverter=keyConv,valueConverter=valueConv,conf=conf)
count=hbase_rdd.count()
hbase_rdd.cache()
output=hbase_rdd.collect()
for(k,v) in output:
        print(k,v)

运行程序

./spark-submit /usr/local/software/spark/mycode/SparkOperateHBase.py

把spark读取hbase的支持jar包导入spark的jars目录下 

cp /usr/local/software/hbase/hbase-2.4.9/lib/hbase*.jar   /usr/local/software/spark/spark-3.0.3-bin-hadoop2.7/tars

再次运行

缺少把HBase数据转换成python可读数据的jar包 

在spark jars目录下新建hbase目录

mkdir hbase

下载转换包到spark   的jars/hbase目录下

wget https://repo.typesafe.com/typesafe/maven-releases/org/apache/spark/spark-examples_2.11/1.6.0-typesafe-001/spark-examples_2.11-1.6.0-typesafe-001.jar

配置spark-env.sh

export SPARK_DIST_CLASSPATH=$(/usr/local/software/hadoop/hadoop-3.3.0/bin/hadoop classpath):$(/usr/local/software/hbase/hbase-2.4.9/bin/hbase classpath):/usr/local/software/spark/spark-3.0.3-bin-hadoop2.7/jars/hbase/*

再次运行

启动HBase

再次运行

 

 读取成功！

写入

在spark/mycode目录下新建文件SparkWriteHBase.py,代码如下：

#!/usr/bin/env python3

from pyspark import SparkConf,SparkContext

conf = SparkConf().setMaster('local').setAppName("WriteHBase")
sc = SparkContext(conf = conf)
host = 'localhost'

table = 'student'
keyConv = "org.apache.spark.examples.pythonconverters.StringToImmutableBytesWritableConverter"
valueConv="org.apache.spark.examples.pythonconverters.StringListToPutConverter"
conf = {"hbase.zookeeper.quorum": host,"hbase.mapred.outputtable": table,"mapreduce.outputformat.class":"org.apache.hadoop.hbase.mapreduce.TableOutputFormat","mapreduce.job.output.key.class":"org.apache.hadoop.hbase.io.ImmutableBytesWritable","mapreduce.job.output.value.class":"org.apache.hadoop.io.Writable"}

rawData=['3,info,name,Rongcheng','3,info,gender,M','3,info,age,26','4,info,name,Guanhua','4,info,gender,M','4,info,age,27']
sc.parallelize(rawData).map(lambda x: (x[0],x.split(','))).saveAsNewAPIHadoopDataset(conf=conf,keyConverter=keyConv,valueConverter=valueConv)

执行程序，报如下错误：

这里是因为上面导入的spark-examples_2.11-1.6.0-typesafe-001.jar与当前的hbase版本兼容，因为hbase2.x之后的版本Put类中的add()方法被调整成了addColumn(),导致调用时找不到对应的方法。

这个需要自行下载Spark的1.6版本的源码，修改后重新编译打包

 替换原来的spark-examples_2.11-1.6.0-typesafe-001.jar即可

继续执行程序，

然后进入hbase shell界面，

[hadoop@master bin]$ ./hbase shell

scan 'student' 会看到数据3,4会被写入。

hbase:002:0> scan 'student'
ROW                         COLUMN+CELL                                                                 
 1                          column=info:age, timestamp=2022-03-24T21:57:49.420, value=23                
 1                          column=info:gender, timestamp=2022-03-24T21:57:39.878, value=F              
 1                          column=info:name, timestamp=2022-03-24T21:57:20.047, value=Xueqian          
 2                          column=info:age, timestamp=2022-03-24T21:58:23.296, value=24                
 2                          column=info:gender, timestamp=2022-03-24T21:58:40.337, value=M              
 2                          column=info:name, timestamp=2022-03-24T21:58:10.985, value=Weiliang         
 3                          column=info:age, timestamp=2022-03-26T21:39:28.041, value=26                
 3                          column=info:gender, timestamp=2022-03-26T21:39:28.041, value=M              
 3                          column=info:name, timestamp=2022-03-26T21:39:28.041, value=Rongcheng        
 4                          column=info:age, timestamp=2022-03-26T21:39:28.041, value=27                
 4                          column=info:gender, timestamp=2022-03-26T21:39:28.041, value=M              
 4                          column=info:name, timestamp=2022-03-26T21:39:28.041, value=Guanhua          
4 row(s)