一、Mapjoin案例
1.需求：有两个文件，分别是订单表、商品表，
订单表有三个属性分别为订单时间、商品id、订单id（表示内容量大的表），
商品表有两个属性分别为商品id、商品名称（表示内容量小的表，用于加载到内存），
要求结果文件为在订单表中的每一行最后添加商品id对应的商品名称。
2.解决思路：
将商品表加载到内存中，然后再map方法中将订单表中的商品id对应的商品名称添加到该行的最后，不需要Reducer，并在Driver执行类中设置setCacheFile和numReduceTask。
3.代码如下：
public class CacheMapper extends Mapper<LongWritable, Text, Text, NullWritable>{
HashMap<String, String> pdMap = new HashMap<>();
//1.商品表加载到内存
protected void setup(Context context) throws IOException {
//加载缓存文件
BufferedReader br = new BufferedReader(new InputStreamReader(new FileInputStream("pd.txt"), "Utf-8"));
String line;
while(StringUtils.isNotEmpty(line = br.readLine()) ) {
//切分
String[] fields = line.split("\t");
//缓存
pdMap.put(fields[0], fields[1]);
}
br.close();
}
//2.map传输
@Override
protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, NullWritable>.Context context)
throws IOException, InterruptedException {
//获取数据
String line = value.toString();
//切割
String[] fields = line.split("\t");
//获取订单中商品id
String pid = fields[1];
//根据订单商品id获取商品名
String pName = pdMap.get(pid);
//拼接数据
line = line + "\t" + pName;
//输出
context.write(new Text(line), NullWritable.get());
}
}
public class CacheDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException, URISyntaxException {
// 1.获取job信息
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
// 2.获取jar包
job.setJarByClass(CacheDriver.class);
// 3.获取自定义的mapper与reducer类
job.setMapperClass(CacheMapper.class);
// 5.设置reduce输出的数据类型（最终的数据类型）
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(NullWritable.class);
// 6.设置输入存在的路径与处理后的结果路径
FileInputFormat.setInputPaths(job, new Path("c://table1029//in"));
FileOutputFormat.setOutputPath(job, new Path("c://table1029//out"));
//加载缓存商品数据
job.addCacheFile(new URI("file:///c:/inputcache/pd.txt"));
//设置一下reducetask的数量
job.setNumReduceTasks(0);
// 7.提交任务
boolean rs = job.waitForCompletion(true);
System.out.println(rs ? 0 : 1);
}
}
二、Reducejoin案例
1.需求：同上的两个数据文件，要求将订单表中的商品id替换成对应的商品名称。
2.解决思路：封装TableBean类，包含属性：时间、商品id、订单id、商品名称、flag（flag用来判断是哪张表），
使用Mapper读两张表，通过context对象获取切片对象，然后通过切片获取切片名称和路径的字符串来判断是哪张表，再将切片的数据封装到TableBean对象，最后以产品id为key、TableBean对象为value传输到Reducer端；
Reducer接收数据后通过flag判断是哪张表，因为一个reduce中的所有数据的key是相同的，将商品表的商品id和商品名称读入到一个TableBean对象中，然后将订单表的中的数据读入到TableBean类型的ArrayList对象中，然后将ArrayList中的每个TableBean的商品id替换为商品名称，然后遍历该数组以TableBean为key输出。
3.代码如下：
/**
* @author: PrincessHug
* @date: 2019/3/30, 2:37
* @Blog: https://www.cnblogs.com/HelloBigTable/
*/
public class TableBean implements Writable {
private String timeStamp;
private String productId;
private String orderId;
private String productName;
private String flag; public TableBean() {
} public String getTimeStamp() {
return timeStamp;
} public void setTimeStamp(String timeStamp) {
this.timeStamp = timeStamp;
} public String getProductId() {
return productId;
} public void setProductId(String productId) {
this.productId = productId;
} public String getOrderId() {
return orderId;
} public void setOrderId(String orderId) {
this.orderId = orderId;
} public String getProductName() {
return productName;
} public void setProductName(String productName) {
this.productName = productName;
} public String getFlag() {
return flag;
} public void setFlag(String flag) {
this.flag = flag;
} @Override
public void write(DataOutput out) throws IOException {
out.writeUTF(timeStamp);
out.writeUTF(productId);
out.writeUTF(orderId);
out.writeUTF(productName);
out.writeUTF(flag);
} @Override
public void readFields(DataInput in) throws IOException {
timeStamp = in.readUTF();
productId = in.readUTF();
orderId = in.readUTF();
productName = in.readUTF();
flag = in.readUTF();
} @Override
public String toString() {
return timeStamp + "\t" + productName + "\t" + orderId;
}
} public class TableMapper extends Mapper<LongWritable, Text,Text,TableBean> {
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//通过切片获取文件信息
FileSplit split = (FileSplit) context.getInputSplit();
String name = split.getPath().getName(); //获取一行数据、定义TableBean对象
String line = value.toString();
TableBean tb = new TableBean();
Text t = new Text(); //判断是哪一张表
if (name.contains("order.txt")){
String[] fields = line.split("\t");
tb.setTimeStamp(fields[0]);
tb.setProductId(fields[1]);
tb.setOrderId(fields[2]);
tb.setProductName("");
tb.setFlag("0");
t.set(fields[1]);
}else {
String[] fields = line.split("\t");
tb.setTimeStamp("");
tb.setProductId(fields[0]);
tb.setOrderId("");
tb.setProductName(fields[1]);
tb.setFlag("1");
t.set(fields[0]);
}
context.write(t,tb);
}
} public class TableReducer extends Reducer<Text,TableBean,TableBean, NullWritable> {
@Override
protected void reduce(Text key, Iterable<TableBean> values, Context context) throws IOException, InterruptedException {
//分别创建用来存储订单表和产品表的集合
ArrayList<TableBean> orderBean = new ArrayList<>();
TableBean productBean = new TableBean(); //遍历values，通过flag判断是产品表还是订单表
for (TableBean v:values){
if (v.getFlag().equals("0")){
TableBean tableBean = new TableBean();
try {
BeanUtils.copyProperties(tableBean,v);
} catch (IllegalAccessException e) {
e.printStackTrace();
} catch (InvocationTargetException e) {
e.printStackTrace();
}
orderBean.add(tableBean);
}else {
try {
BeanUtils.copyProperties(productBean,v);
} catch (IllegalAccessException e) {
e.printStackTrace();
} catch (InvocationTargetException e) {
e.printStackTrace();
}
}
}
//拼接表
for (TableBean ob:orderBean) {
ob.setProductName(productBean.getProductName());
context.write(ob,NullWritable.get());
}
}
} public class TableDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
//job信息
Configuration conf = new Configuration();
Job job = Job.getInstance(conf); //jar包
job.setJarByClass(TableDriver.class); //Mapper、Reducer
job.setMapperClass(TableMapper.class);
job.setReducerClass(TableReducer.class); //Mapper输出数据类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(TableBean.class); //Reducer输出数据类型
job.setOutputKeyClass(TableBean.class);
job.setOutputValueClass(NullWritable.class); //输入输出路径
FileInputFormat.setInputPaths(job,new Path("G:\\mapreduce\\reducejoin\\in"));
FileOutputFormat.setOutputPath(job,new Path("G:\\mapreduce\\reducejoin\\out")); //提交任务
if (job.waitForCompletion(true)){
System.out.println("运行完成！");
}else {
System.out.println("运行失败！");
}
}
}