1. 问题描述
收集日志avro数据中有两个Map字段appInstall、appUse分别表示已安装的app、正在使用的app，且key值为app的名称，value值为app使用信息。现在要得到一份匹配上购物类app支付宝|京东|淘宝|天猫的用户名单；MapReduce 解决办法如下：
public static class M extends Mapper<String, Pair, String, Text> {
Text text = new Text();
@SuppressWarnings("unchecked")
@Override
protected void map(String key, Pair value, Context context) throws IOException, InterruptedException {
Map data = value.fields.data;
String dvc = data.get("dvc").toString();
Map<String, Object> appInstall = (Map<String, Object>) data.get("appInstall");
Map<String, Object> appUse = (Map<String, Object>) data.get("appUse");
for(String app: appInstall.keySet()) {
if(app.matches("支付宝|京东|淘宝|天猫")) {
text.set(appInstall.keySet().toString());
context.write(dvc, text);
return;
}
}
for(String app: appUse.keySet()) {
if(app.matches("支付宝|京东|淘宝|天猫")) {
text.set(appUse.keySet().toString());
context.write(dvc, text);
return;
}
}
}
}
但是，如果要匹配游戏类的app、金融类的app类呢？如果匹配关键词发生了变化呢？显然，我们应该将匹配关键词开放成API，可以自由地匹配正则表达式。这时，pig派上了用场。
2. Bag正则匹配
A = load '/<path>/<to>' using org.apache.pig.piggybank.storage.avro.AvroStorage();
B = foreach A generate value.fields.data#'dvc' as dvc, value.fields.data#'appInstall' as ins:map[], value.fields.data#'appUse' as use:map[];
C = foreach B generate dvc, KEYSET(ins) as insk, KEYSET(use) as usek;
在上述代码中，load 数据转换得到bag类型的app-set（insk与usek）；但是，应如何遍历bag中的tuple与正则表达式做匹配呢？答案是UDF。
Apache DataFu Pig 提供了丰富的UDF，其中关于bags的UDF可以参看这里。TupleFromBag 提供根据index从bag提取tuple，支持三个输入参数。依葫芦画瓢，遍历bag匹配正则表达式的UDF如下：
package com.pig.udf.bag;
public class BagMatchRegex extends FilterFunc {
@Override
public Boolean exec(Tuple tinput) throws IOException {
try{
DataBag samples = (DataBag) tinput.get(0);
String regex = (String) tinput.get(1);
for (Tuple tuple : samples) {
if(((String) tuple.get(0)).matches(regex)){
return true;
}
}
}
catch (Exception e) {
return false;
}
return false;
}
}
其中，FilterFunc为过滤UDF的基类，继承于EvalFunc<Boolean>，即exec(Tuple tinput)的返回值必为Boolean类型。bag正则匹配的pig脚本如下：
REGISTER ../piglib/udf-0.0.1-SNAPSHOT-jar-with-dependencies.jar
define BagMatchRegex com.pig.udf.bag.BagMatchRegex();
A = load '/user/../current/*.avro' using org.apache.pig.piggybank.storage.avro.AvroStorage();
B = foreach A generate value.fields.data#'dvc' as dvc, value.fields.data#'appInstall' as ins:map[], value.fields.data#'appUse' as use:map[];
C = foreach B generate dvc, KEYSET(ins) as insk, KEYSET(use) as usek;
D = filter C by BagMatchRegex(insk, '支付宝|京东|淘宝|天猫') or BagMatchRegex(usek, '支付宝|京东|淘宝|天猫');
3. 优化
还有没有可以做优化的地方呢？我们先来看看pig中的KEYSET实现：
package org.apache.pig.builtin;
public class KEYSET extends EvalFunc<DataBag> {
private static final TupleFactory TUPLE_FACTORY = TupleFactory.getInstance();
@SuppressWarnings("unchecked")
@Override
public DataBag exec(Tuple input) throws IOException {
if(input == null || input.size() == 0) {
return null;
}
Map<String, Object> m = null;
m = (Map<String, Object>)(input.get(0));
if(m == null) {
return null;
}
DataBag bag = new NonSpillableDataBag(m.size());
for (String s : m.keySet()) {
Tuple t = TUPLE_FACTORY.newTuple(s);
bag.add(t);
}
return bag;
}
...
}
需要指出的一点——pig的map数据类型是由Java类Map<String, Object>实现的。从KEYSET源码中可以看出在调用时已经将map遍历了一次，然后在调用BagMatchRegex时又需要将key-set的bag再遍历一次。其实，完全可以只用一次遍历做map-key值的正则匹配：
package com.pig.udf.map;
public class KeyMatchRegex extends FilterFunc {
@SuppressWarnings("unchecked")
@Override
public Boolean exec(Tuple input) throws IOException
{
try{
Map<String, Object> m = null;
m = (Map<String, Object>)(input.get(0));
String regex = (String) input.get(1);
for (String key : m.keySet()) {
if(key.matches(regex)){
return true;
}
}
}
catch (Exception e) {
return false;
}
return false;
}
}
如需转载，请注明作者及出处.
作者：Treant
出处：http://www.cnblogs.com/en-heng/
