6. HBase and MapReduce Integration
6.1 Integration with official HBase MapReduce
- View the HBase MapReduce task execution:
bin/hbase mapredcp;
- Import Environment Variables
- Provisional entry into force, at the command line to perform operations:
export HBASE_HOME=/opt/module/hbase-1.3.4;export HADOOP_HOME=/opt/module/hadoop-2.8.5;export HADOOP_CLASSPATH=${HBASE_HOME}/bin/hbase mapredcp;
- Permanent, in
/etc/profilethe configuration
export HBASE_HOME=/opt/module/hbase-1.3.4;export HADOOP_HOME=/opt/module/hadoop-2.8.5;- And
hadoop-env.shconfiguration:export HADOOP_CLASSPATH=$HADOOP_CLASSPATH:/opt/module/hbase/lib/*
- The official running MapReduce tasks
// ===== 案例一:统计Student表中有多少行数据 (`opt/module/hbase-1.3.4/` 目录下)
/opt/module/hadoop-2.8.5/bin/yarn jar ./lib/hbase-server-1.3.4.jar rowcounter student
// ===== 案例二:使用 MapReduce 将本地数据导入到 HBASE
// 1. 本地创建一个fruit.tsv文件
1001 Apple Red
1002 Pear Yellow
1003 Pineapple Yellow
// 2. 创建 HBase 表
create 'fruit','info'
// 3. 在 HDFS 中创建 input_fruit 文件夹并上传 fruit.tsv 文件
/opt/module/hadoop-2.8.5/bin/hdfs dfs -mkdir /input_fruit
/opt/module/hadoop-2.8.5/bin/hdfs dfs -put fruit.tsv /input_fruit/
// 4. 执行 MapReduce, 将 fruit.tsv 导入到 HBase 的 fruit 表中
/opt/module/hadoop-2.8.5/bin/yarn jar ./lib/hbase-server-1.3.4.jar importtsv -Dimporttsv.columns=HBASE_ROW_KEY,info:name,info:color fruit hdfs://IP地址/input_fruit
6.2 Custom HBase-MapReduce
- Demand: The fruit part of the data in the table, to move through the MR table fruit_mr
// 1. 创建 FruitMapper 类,用于读取 fruit 表中的数据
public class FruitMapper extends TableMapper<ImmutableBytesWritable, Put>{
@Override
protected void map(ImmutableBytesWritable key, Result value, Context context) throws IOException, InterruptedException {
// 创建put对象
Put put = new Put(key.get());
Cell[] cells = value.rawCells();
for(Cell cell : cells) {
if("name".equals(Bytes.toString(CellUtil.cloneQualifier(cell)))) {
put.add(cell);
}
}
context.write(key, put);
}
}
// 2. 创建 FruitReducer 类,用于写入
public class FruitReducer extends TableReducer<ImmutableBytesWritable, Put, NullWritable>{
@Override
protected void reduce(ImmutableBytesWritable key, Iterable<Put> values, Context context) throws IOException, InterruptedException {
for (Put value : values) {
context.write(NullWritable.get(), value);
}
}
}
// 3. 创建 FruitDriver 类,用于执行 mapper 和 reducer
public class FruitDriver extends Configuration implements Tool{
private Configuration configuration = null;
@Override
public void setConf(Configuration conf) {
this.configuration = conf;
}
@Override
public Configuration getConf() {
return configuration;
}
@Override
public int run(String[] args) throws Exception {
// 获取任务对象
Job job = Job.getInstance(configuration);
// 指定 Driver类
job.setJarByClass(FruitDriver.class);
// 指定 Mapper
TableMapReduceUtil.initTableMapperJob("fruit", new Scan(), FruitMapper.class, ImmutableBytesWritable.class, Put.class, job);
// 指定 Reducer
TableMapReduceUtil.initTableReducerJob("fruit_mr", FruitReducer.class, job);
// 提交
boolean result = job.waitForCompletion(true);
return result ? 0 : 1;
}
public static void main(String[] args) throws Exception {
Configuration configuration = HBaseConfiguration.create();
ToolRunner.run(configuration, new FruitDriver(), args);
}
}
// 4. 打成 fruit.jar包
// 5. HBase 中创建 fruit_mr 表
create 'fruit_mr','info'
// 6. 在 /opt/module/hbase 中执行:
/opt/module/hadoop-2.8.5/bin/yarn jar ./fruit.jar com.noodles.mr1.FruitDriver(Driver的类名)
6.3 Custom HBase-MapReduce2
- Requirements: realize the data is written to HDFS in HBase table
// 1. 创建 Mapper, 用于读取 HDFS 上的文件
public class HDFSMapper extends Mapper<LongWritable, Text, NullWritable, Put>{
@Override
protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, NullWritable, Put>.Context context)
throws IOException, InterruptedException {
// 获取一行数据
String line = value.toString();
// 切割
String[] split = line.split("\t");
// 封装 Put 对象
Put put = new Put(Bytes.toBytes(split[0]));
put.addColumn(Bytes.toBytes("info"), Bytes.toBytes("name"), Bytes.toBytes(split[1]));
put.addColumn(Bytes.toBytes("info"), Bytes.toBytes("color"), Bytes.toBytes(split[2]));
// 写出去
context.write(NullWritable.get(), put);
}
}
// 2. 创建 Reducer, 用于写入
public class HDFSReducer extends TableReducer<NullWritable, Put, NullWritable>{
@Override
protected void reduce(NullWritable key, Iterable<Put> values,
Reducer<NullWritable, Put, NullWritable, Mutation>.Context context) throws IOException, InterruptedException {
// 写出数据
for(Put value : values) {
context.write(NullWritable.get(), value);
}
}
}
// 3. 创建Driver
public class HDFSDriver extends Configuration implements Tool{
private Configuration configuration = null;
@Override
public void setConf(Configuration conf) {
this.configuration = conf;
}
@Override
public Configuration getConf() {
return configuration;
}
@Override
public int run(String[] args) throws Exception {
// 获取 Job 对象
Job job = Job.getInstance(configuration);
// 设置主类
job.setJarByClass(HDFSDriver.class);
// 设置 Mapper
job.setMapperClass(HDFSMapper.class);
job.setMapOutputKeyClass(NullWritable.class);
job.setMapOutputValueClass(Put.class);
// 设置 Reducer
TableMapReduceUtil.initTableReducerJob("fruit2", HDFSReducer.class, job);
// 设置输入路径
// import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
FileInputFormat.setInputPaths(job, args[0]);
// 提交
boolean result = job.waitForCompletion(true);
return result ? 0 : 1;
}
public static void main(String[] args) throws Exception {
Configuration configuration = HBaseConfiguration.create();
ToolRunner.run(configuration, new HDFSDriver(), args);
}
}
// 4. 打成 fruit.jar包
// 5. HBase 中创建 fruit2 表
create 'fruit2','info'
// 6. 在 /opt/module/hbase 中执行:
/opt/module/hadoop-2.8.5/bin/yarn jar ./fruit.jar com.noodles.mr2.HDFSDriver(Driver的类名) /input_fruit/fruit.tsv(文件路径)