文章目录
PV 值:page view
页面浏览量或点击量，是衡量一个网站或网页用户访问量。具体的说，PV 值就是所有访问者在 24 小时（0 点到 24 点）内看了某个网站多少个页面或某个网页多少次。PV 是指页面刷新的次数，每一次页面刷新，就算做一次 PV 流量。
代码逻辑
- 取网址链接mapToPair 产生(网址链接,1)的tuple
- reduceByKey
- foreach打印
SparkConf conf = new SparkConf();
conf.setMaster("local").setAppName("PV");
JavaSparkContext context = new JavaSparkContext(conf);
JavaRDD<String> lineRDD = context.textFile("./data/pvuvdata");
lineRDD.mapToPair(new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String line) throws Exception {
String string = line.split("\t")[5];
return new Tuple2<>(string,1);
}
}).reduceByKey(new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer v1, Integer v2) throws Exception {
return v1+v2;
}
}).foreach(new VoidFunction<Tuple2<String, Integer>>() {
@Override
public void call(Tuple2<String, Integer> stringIntegerTuple2) throws Exception {
System.out.println("网址"+stringIntegerTuple2);
}
});
lineRDD.mapToPair(new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String line) throws Exception {
String string = line.split("\t")[5];
return new Tuple2<>(string,1);
}
}).groupByKey().foreach(new VoidFunction<Tuple2<String, Iterable<Integer>>>() {
@Override
public void call(Tuple2<String, Iterable<Integer>> s) throws Exception {
int count = 0 ;
Iterator<Integer> iterator = s._2.iterator();
while (iterator.hasNext()){
count ++;
}
System.out.println("url : "+ s._1 + " value " + count);
}
}); SparkConf conf = new SparkConf();
conf.setMaster("local").setAppName("PV");
JavaSparkContext context = new JavaSparkContext(conf);
JavaRDD<String> lineRDD = context.textFile("./data/pvuvdata");
lineRDD.mapToPair(new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String line) throws Exception {
String string = line.split("\t")[5];
return new Tuple2<>(string,1);
}
}).reduceByKey(new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer v1, Integer v2) throws Exception {
return v1+v2;
}
}).foreach(new VoidFunction<Tuple2<String, Integer>>() {
@Override
public void call(Tuple2<String, Integer> stringIntegerTuple2) throws Exception {
System.out.println("网址"+stringIntegerTuple2);
}
});
Map<String, Object> map = lineRDD.mapToPair(new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String line) throws Exception {
String string = line.split("\t")[5];
return new Tuple2<>(string, 1);
}
}).countByKey();
for (String key : map.keySet()){
System.out.println("key : "+ key + " value :" + map.get(key));
}UV （unique visitor ）即独立访客数
指访问某个站点或点击某个网页的同 不同 IP 地址的人数。在同一天内，UV 只记录第一次进入网站的具有独立IP 的访问者，在同一天内再次访问该网站则不计数。UV 提供了一定时间内不同观众数量的统计指标，而没有反应出网站的全面活动
SparkConf conf = new SparkConf();
conf.setMaster("local").setAppName("TestUV");
JavaSparkContext context = new JavaSparkContext(conf);
JavaRDD<String> lineRDD = context.textFile("./data/pvuvdata");
JavaPairRDD<String, Iterable<String>> rdd1 = lineRDD.mapToPair(new PairFunction<String, String, String>() {
@Override
public Tuple2<String, String> call(String s) throws Exception {
String url = s.split("\t")[5];
String ip = s.split("\t")[0];
return new Tuple2<>(url, ip);
}
}).groupByKey();
rdd1.foreach(new VoidFunction<Tuple2<String, Iterable<String>>>() {
@Override
public void call(Tuple2<String, Iterable<String>> t) throws Exception {
HashSet<Object> set = new HashSet<>();
Iterator<String> iterator = t._2.iterator();
while (iterator.hasNext()){
set.add(iterator.next());
}
System.out.println(" key : "+t._1+ " value :"+set.size());
}
}); SparkConf conf = new SparkConf();
conf.setMaster("local").setAppName("TestUV");
JavaSparkContext context = new JavaSparkContext(conf);
JavaRDD<String> lineRDD = context.textFile("./data/pvuvdata");
Map<String, Object> map = lineRDD.mapToPair(new PairFunction<String, String, String>() {
@Override
public Tuple2<String, String> call(String s) throws Exception {
String url = s.split("\t")[5];
String ip = s.split("\t")[0];
return new Tuple2<>(url, ip);
}
}).distinct().countByKey();
for (String key : map.keySet()){
System.out.println(" key : "+ key+ " value: "+ map.get(key));
}
