ETL项目2:大数据清洗,处理:使用MapReduce进行离线数据分析并报表显示完整项目
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2022-03-24 12:47:29
ETL项目2:大数据清洗,处理:使用MapReduce进行离线数据分析并报表显示完整项目 思路同我之前的博客的思路 https://www.cnblogs.com/symkmk123/p/10197467.html 但是数据是从web访问的数据 avro第一次过滤 观察数据的格式,我们主要分析第四个 ......
etl项目2:大数据清洗,处理:使用mapreduce进行离线数据分析并报表显示完整项目
思路同我之前的博客的思路
但是数据是从web访问的数据
avro第一次过滤
观察数据的格式,我们主要分析第四个字段的数据.发现有.css , .jpg .png等等等无效的数据.
通过观察数据发现有效数据都不带 . , 所以第一次过滤写入avro总表里的数据一次过滤后的有效数据,不包含 .css , .jpg , .png 这样的数据
同时count持久化到mysql
orc1:海牛的topics 最受欢迎的top10
通过观察发现这个需求的有效url是 /topics/数字的 所以在第一次过滤的数据的基础上的正则就是
这种保留下来的也只是/topics/数字这种格式,方便用 hql统计结果
上代码
//text2avro package mrrun.hainiuetl; import java.io.ioexception; import java.text.parseexception; import java.text.simpledateformat; import java.util.date; import java.util.locale; import org.apache.avro.schema; import org.apache.avro.generic.genericdata; import org.apache.avro.generic.genericrecord; import org.apache.avro.mapred.avrokey; import org.apache.avro.mapreduce.avrojob; import org.apache.avro.mapreduce.avrokeyoutputformat; import org.apache.hadoop.conf.configuration; import org.apache.hadoop.io.longwritable; import org.apache.hadoop.io.nullwritable; import org.apache.hadoop.io.text; import org.apache.hadoop.mapreduce.counter; import org.apache.hadoop.mapreduce.countergroup; import org.apache.hadoop.mapreduce.counters; import org.apache.hadoop.mapreduce.job; import org.apache.hadoop.mapreduce.mapper; import org.apache.hadoop.mapreduce.lib.input.fileinputformat; import org.apache.hadoop.mapreduce.lib.output.fileoutputformat; import mrrun.base.basemr; public class text2avro extends basemr { public static schema schema = null; public static schema.parser parse = new schema.parser(); public static class text2avromapper extends mapper<longwritable, text, avrokey<genericrecord>, nullwritable> { @override protected void setup(mapper<longwritable, text, avrokey<genericrecord>, nullwritable>.context context) throws ioexception, interruptedexception { //根据user_install_status.avro文件内的格式,生成指定格式的schema对象 schema = parse.parse(text2avro.class.getresourceasstream("/hainiu.avro")); } @override protected void map(longwritable key, text value,context context) throws ioexception, interruptedexception { string line = value.tostring(); string[] splits = line.split("\001"); if(splits == null || splits.length != 10){ system.out.println("=============="); system.out.println(value.tostring()); context.getcounter("etl_err", "bad line num").increment(1l); return; } // system.out.println(util.getiparea("202.8.77.12")); string uip1 = splits[0]; string uip =iputil.getip(uip1); string datetime = splits[2]; stringbuilder sb=new stringbuilder(datetime); simpledateformat sdf=new simpledateformat("dd/mmm/yyyy:hh:mm:ss",locale.english); string sy=sb.tostring(); date mydate = null; try { mydate = sdf.parse(sy); } catch (parseexception e) { // todo auto-generated catch block e.printstacktrace(); } simpledateformat sdf2=new simpledateformat("yyyymmddhhmmss"); //system.out.println(mydate); string format = sdf2.format(mydate); //get /categories/8?filter=recent&page=12 http/1.1 string url1 = splits[3]; stringbuilder sb2=new stringbuilder(url1); string url = sb2.tostring(); string method=""; string top=""; string top1=""; string http=""; if(url!=null) { string[] s = url.split(" "); if(s.length==3) { method=s[0]; http=s[2]; top1=s[1]; if(top1.contains(".")) { context.getcounter("etl_err", "no line num").increment(1l); return; } else { top=top1; } } } string status1 = splits[4]; string status2 = splits[5]; string post = splits[6]; string from = splits[7]; string usagent1 = splits[8]; stringbuilder sb3=new stringbuilder(usagent1); string usagent = sb3.tostring(); //根据创建的schema对象,创建一行的对象 genericrecord record = new genericdata.record(text2avro.schema); record.put("uip", uip); record.put("datetime", format); record.put("method", method); record.put("http", http); record.put("top", top); record.put("from", from); record.put("status1", status1); record.put("status2", status2); record.put("post", post); record.put("usagent", usagent); context.getcounter("etl_good", "good line num").increment(1l); system.out.println(uip+" "+format+" "+top+" "+from+" "+post+" "+usagent+" "+status1+" "+status2+" "+http); context.write(new avrokey<genericrecord>(record), nullwritable.get()); } } @override public job getjob(configuration conf) throws ioexception { // // 开启reduce输出压缩 // conf.set(fileoutputformat.compress, "true"); // // 设置reduce输出压缩格式 // conf.set(fileoutputformat.compress_codec, snappycodec.class.getname()); job job = job.getinstance(conf, getjobnamewithtaskid()); job.setjarbyclass(text2avro.class); job.setmapperclass(text2avromapper.class); job.setmapoutputkeyclass(avrokey.class); job.setmapoutputvalueclass(nullwritable.class); // 无reduce job.setnumreducetasks(0); //设置输出的format job.setoutputformatclass(avrokeyoutputformat.class); //根据user_install_status.avro文件内的格式,生成指定格式的schema对象 schema = parse.parse(text2avro.class.getresourceasstream("/hainiu.avro")); //设置avro文件的输出 avrojob.setoutputkeyschema(job, schema); fileinputformat.addinputpath(job, getfirstjobinputpath()); fileoutputformat.setoutputpath(job, getjoboutputpath(getjobnamewithtaskid())); return job; } @override public string getjobname() { return "etltext2avro"; } }
//avro2orc_topic10 package mrrun.hainiuetl; import java.io.ioexception; import java.util.regex.matcher; import java.util.regex.pattern; import org.apache.avro.schema; import org.apache.avro.generic.genericrecord; import org.apache.avro.mapred.avrokey; import org.apache.avro.mapreduce.avrojob; import org.apache.avro.mapreduce.avrokeyinputformat; import org.apache.hadoop.conf.configuration; import org.apache.hadoop.hive.ql.io.orc.compressionkind; import org.apache.hadoop.hive.ql.io.orc.orcnewoutputformat; import org.apache.hadoop.io.nullwritable; import org.apache.hadoop.io.writable; import org.apache.hadoop.mapreduce.job; import org.apache.hadoop.mapreduce.mapper; import org.apache.hadoop.mapreduce.lib.input.fileinputformat; import org.apache.hadoop.mapreduce.lib.output.fileoutputformat; import mrrun.base.basemr; import mrrun.util.orcformat; import mrrun.util.orcutil; public class avro2orc_topic10 extends basemr { public static schema schema = null; public static schema.parser parse = new schema.parser(); public static class avro2orcmapper extends mapper<avrokey<genericrecord>, nullwritable, nullwritable, writable>{ orcutil orcutil = new orcutil(); @override protected void setup(context context) throws ioexception, interruptedexception { orcutil.setwriteorcinspector(orcformat.etlorcschema_topic10); } @override protected void map(avrokey<genericrecord> key, nullwritable value,context context) throws ioexception, interruptedexception { //得到一行的对象 genericrecord datum = key.datum(); string uip = (string) datum.get("uip"); string datetime = (string) datum.get("datetime"); //string method = (string) datum.get("method"); //string http = (string) datum.get("http"); string top1 = (string) datum.get("top"); string top=""; string regex="/topics/\\d+"; pattern pattern=pattern.compile(regex); matcher matcher=pattern.matcher(top1); if(matcher.find()) { top=matcher.group(); } else { context.getcounter("etl_err", "notopics line num").increment(1l); return; } //orcutil.addattr(uip,datetime,method,http,uid,country,status1,status2,usagent); orcutil.addattr(uip,datetime,top); writable w = orcutil.serialize(); context.getcounter("etl_good", "good line num").increment(1l); system.out.println(uip+" "+top); context.write(nullwritable.get(), w); } } @override public job getjob(configuration conf) throws ioexception { //关闭map的推测执行,使得一个map处理 一个region的数据 conf.set("mapreduce.map.spedulative", "false"); //设置orc文件snappy压缩 conf.set("orc.compress", compressionkind.snappy.name()); //设置orc文件 有索引 conf.set("orc.create.index", "true"); job job = job.getinstance(conf, getjobnamewithtaskid()); job.setjarbyclass(avro2orc_topic10.class); job.setmapperclass(avro2orcmapper.class); job.setmapoutputkeyclass(nullwritable.class); job.setmapoutputvalueclass(writable.class); // 无reduce job.setnumreducetasks(0); job.setinputformatclass(avrokeyinputformat.class); //根据user_install_status.avro文件内的格式,生成指定格式的schema对象 schema = parse.parse(avro2orc_topic10.class.getresourceasstream("/hainiu.avro")); avrojob.setinputkeyschema(job, schema); job.setoutputformatclass(orcnewoutputformat.class); fileinputformat.addinputpath(job, getfirstjobinputpath()); fileoutputformat.setoutputpath(job, getjoboutputpath(getjobnamewithtaskid())); return job; } @override public string getjobname() { return "etlavro2orc_topic10"; } }
//text2avrojob package mrrun.hainiuetl; import java.text.simpledateformat; import java.util.date; import org.apache.hadoop.conf.configuration; import org.apache.hadoop.conf.configured; import org.apache.hadoop.mapreduce.counter; import org.apache.hadoop.mapreduce.countergroup; import org.apache.hadoop.mapreduce.counters; import org.apache.hadoop.mapreduce.job; import org.apache.hadoop.mapreduce.lib.jobcontrol.controlledjob; import org.apache.hadoop.mapreduce.lib.jobcontrol.jobcontrol; import org.apache.hadoop.util.tool; import org.apache.hadoop.util.toolrunner; import mrrun.util.jobrunresult; import mrrun.util.jobrunutil; public class text2avrojob extends configured implements tool{ @override public int run(string[] args) throws exception { //获取configuration对象 configuration conf = getconf(); //创建任务链对象 jobcontrol jobc = new jobcontrol("etltext2avro"); text2avro avro = new text2avro(); //只需要赋值一次就行 avro.setconf(conf); controlledjob orccjob = avro.getcontrolledjob(); job job = orccjob.getjob(); job.waitforcompletion(true); jobrunresult result = jobrunutil.run(jobc); result.setcounters("etl1", orccjob.getjob().getcounters()); result.print(true); counters countermap = result.getcountermap("etl1"); countergroup group1 = countermap.getgroup("etl_good"); countergroup group2 = countermap.getgroup("etl_err"); counter good = group1.findcounter("good line num"); counter bad = group2.findcounter("bad line num"); system.out.println("\t\t"+good.getdisplayname()+" = "+good.getvalue()); system.out.println("\t\t"+bad.getdisplayname()+" = "+bad.getvalue()); system.out.println("=======+++++++++===="); date date=new date(); simpledateformat sdf3=new simpledateformat("yyyymmdd"); string format2 = sdf3.format(date); results results=new results(); long bad_num = bad.getvalue(); long good_num = good.getvalue(); long total_num=bad_num+good_num; results.setbad_num(bad_num); results.setgood_num(good_num); results.settotal_num(total_num); results.setday(format2); double d=bad_num*1.0/total_num*1.0; results.setbad_rate(d); system.out.println((double)((double)bad_num/(double)total_num)); dao dao=new dao(); if(dao.getday(format2)!=null) { results getday = dao.getday(format2); long bad_num2 = getday.getbad_num(); long good_num2 = getday.getgood_num(); long total_num2 = getday.gettotal_num(); getday.setday(format2); getday.setbad_num(bad_num2+bad_num); getday.setgood_num(good_num2+good_num); getday.settotal_num(total_num2+total_num); double badrate=(bad_num2+bad_num)*1.0/(total_num2+total_num)*1.0; getday.setbad_rate(badrate); dao.update(getday); } else { dao.insert(results); } jobc.addjob(orccjob); return 0; } public static void main(string[] args) throws exception { // -dtask.id=1226 -dtask.input.dir=/tmp/avro/input_hainiuetl -dtask.base.dir=/tmp/avro system.exit(toolrunner.run(new text2avrojob(), args)); } }
放一个
自动化脚本思路同第一个etl项目
直接放代码
yitiaolong.sh #!/bin/bash source /etc/profile mmdd=`date -d 1' days ago' +%m%d` yymm=`date -d 1' days ago' +%y%m` dd=`date -d 1' days ago' +%d` /usr/local/hive/bin/hive -e "use suyuan09;alter table etlavrosy add if not exists partition(month='${yymm}',day='${dd}');" /usr/local/hive/bin/hive -e "use suyuan09;alter table hainiuetltopics10_orc add if not exists partition(month='${yymm}',day='${dd}');" /usr/local/hive/bin/hive -e "use suyuan09;alter table hainiuetlcategories10_orc add if not exists partition(month='${yymm}',day='${dd}');" /usr/local/hive/bin/hive -e "use suyuan09;alter table hainiuetlspider_orc add if not exists partition(month='${yymm}',day='${dd}');" /usr/local/hive/bin/hive -e "use suyuan09;alter table hainiuetlip_orc add if not exists partition(month='${yymm}',day='${dd}');" /usr/local/hive/bin/hive -e "use suyuan09;alter table hainiuetlindex5_orc add if not exists partition(month='${yymm}',day='${dd}');" #3-4运行mr hdfs_path1=/user/hainiu/data/hainiuetl/input/${yymm}/${dd} avro_path1=/user/suyuan09/hainiuetl/hainiuavro/${yymm}/${dd} `/usr/local/hadoop/bin/hadoop jar /home/suyuan09/etl/hainiu/jar/181210_hbase-1.0.0-symkmk123.jar etltext2avro -dtask.id=${mmdd} -dtask.input.dir=${hdfs_path1} -dtask.base.dir=${avro_path1}` #orctopics10mr.sh avro_path2=/user/suyuan09/hainiuetl/hainiuavro/${yymm}/${dd}/etltext2avro_${mmdd}/part-*.avro orc_path2=/user/suyuan09/hainiuetl/orctopics10/${yymm}/${dd} `/usr/local/hadoop/bin/hadoop jar /home/suyuan09/etl/hainiu/jar/181210_hbase-1.0.0-symkmk123.jar etlavro2orc_topic10 -dtask.id=${mmdd} -dtask.input.dir=${avro_path2} -dtask.base.dir=${orc_path2}` #orccategories10mr.sh avro_path3=/user/suyuan09/hainiuetl/hainiuavro/${yymm}/${dd}/etltext2avro_${mmdd}/part-*.avro orc_path3=/user/suyuan09/hainiuetl/orccategories10/${yymm}/${dd} `/usr/local/hadoop/bin/hadoop jar /home/suyuan09/etl/hainiu/jar/181210_hbase-1.0.0-symkmk123.jar etlavro2orc_categories10 -dtask.id=${mmdd} -dtask.input.dir=${avro_path3} -dtask.base.dir=${orc_path3}` #orcspidermr.sh avro_path4=/user/suyuan09/hainiuetl/hainiuavro/${yymm}/${dd}/etltext2avro_${mmdd}/part-*.avro orc_path4=/user/suyuan09/hainiuetl/orcspider/${yymm}/${dd} `/usr/local/hadoop/bin/hadoop jar /home/suyuan09/etl/hainiu/jar/181210_hbase-1.0.0-symkmk123.jar etlavro2orc_spider -dtask.id=${mmdd} -dtask.input.dir=${avro_path4} -dtask.base.dir=${orc_path4}` #orcipmr.sh avro_path5=/user/suyuan09/hainiuetl/hainiuavro/${yymm}/${dd}/etltext2avro_${mmdd}/part-*.avro orc_path5=/user/suyuan09/hainiuetl/orcip/${yymm}/${dd} `/usr/local/hadoop/bin/hadoop jar /home/suyuan09/etl/hainiu/jar/181210_hbase-1.0.0-symkmk123.jar etlavro2orc_ip -dtask.id=${mmdd} -dtask.input.dir=${avro_path5} -dtask.base.dir=${orc_path5}` #orcindex5mr.sh avro_path6=/user/suyuan09/hainiuetl/hainiuavro/${yymm}/${dd}/etltext2avro_${mmdd}/part-*.avro orc_path6=/user/suyuan09/hainiuetl/orcindex5/${yymm}/${dd} `/usr/local/hadoop/bin/hadoop jar /home/suyuan09/etl/hainiu/jar/181210_hbase-1.0.0-symkmk123.jar etlavro2orc_index5 -dtask.id=${mmdd} -dtask.input.dir=${avro_path6} -dtask.base.dir=${orc_path6}` #把orc挪到分区目录 #orc2etl.sh /usr/local/hadoop/bin/hadoop fs -cp hdfs://ns1/user/suyuan09/hainiuetl/orctopics10/${yymm}/${dd}/etlavro2orc_topic10_${mmdd}/part-* hdfs://ns1/user/suyuan09/etlorc/hainiuetltopics10_orc/month=${yymm}/day=${dd} /usr/local/hadoop/bin/hadoop fs -cp hdfs://ns1/user/suyuan09/hainiuetl/orccategories10/${yymm}/${dd}/etlavro2orc_categories10_${mmdd}/part-* hdfs://ns1/user/suyuan09/etlorc/hainiuetlcategories10_orc/month=${yymm}/day=${dd} /usr/local/hadoop/bin/hadoop fs -cp hdfs://ns1/user/suyuan09/hainiuetl/orcspider/${yymm}/${dd}/etlavro2orc_spider_${mmdd}/part-* hdfs://ns1/user/suyuan09/etlorc/hainiuetlspider_orc/month=${yymm}/day=${dd} /usr/local/hadoop/bin/hadoop fs -cp hdfs://ns1/user/suyuan09/hainiuetl/orcindex5/${yymm}/${dd}/etlavro2orc_index5_${mmdd}/part-* hdfs://ns1/user/suyuan09/etlorc/hainiuetlindex5_orc/month=${yymm}/day=${dd} /usr/local/hadoop/bin/hadoop fs -cp hdfs://ns1/user/suyuan09/hainiuetl/orcip/${yymm}/${dd}/etlavro2orc_ip_${mmdd}/part-* hdfs://ns1/user/suyuan09/etlorc/hainiuetlip_orc/month=${yymm}/day=${dd} #自动从hive到mysql脚本 #hive2data.sh /usr/local/hive/bin/hive -e "use suyuan09;select t.top,t.num from(select top,count(*) num from hainiuetlindex5_orc group by top) t sort by t.num desc limit 5;" > /home/suyuan09/etl/hainiu/orc2mysql/myindex5${yymmdd} /usr/local/hive/bin/hive -e "use suyuan09;select t.top,t.num from(select top,count(*) num from hainiuetltopics10_orc group by top) t sort by t.num desc limit 10;" > /home/suyuan09/etl/hainiu/orc2mysql/mytopics10${yymmdd} /usr/local/hive/bin/hive -e "use suyuan09;select t.top,t.num from(select top,count(*) num from hainiuetlcategories10_orc group by top) t sort by t.num desc limit 10;" > /home/suyuan09/etl/hainiu/orc2mysql/mycategories10${yymmdd} /usr/local/hive/bin/hive -e "use suyuan09;select t.uip,t.num from(select uip,count(*) num from hainiuetlip_orc group by uip) t sort by t.num desc;" > /home/suyuan09/etl/hainiu/orc2mysql/myip${yymmdd} /usr/local/hive/bin/hive -e "use suyuan09;select t.usagent,t.num from(select usagent,count(*) num from hainiuetlspider_orc group by usagent) t sort by t.num desc;" > /home/suyuan09/etl/hainiu/orc2mysql/myspider${yymmdd} #data->mysql脚本 #data2mysql.sh #mysql -h 172.33.101.123 -p 3306 -u tony -pyourpassword -d yourdbname <<eof /bin/mysql -h192.168.88.195 -p3306 -uhainiu -p12345678 -dhainiutest <<eof load data local infile "/home/suyuan09/etl/hainiu/orc2mysql/mytopics10${yymmdd}" into table suyuan09_etl_orctopics10mysql fields terminated by '\t'; load data local infile "/home/suyuan09/etl/hainiu/orc2mysql/mycategories10${yymmdd}" into table suyuan09_etl_orccategories10mysql fields terminated by '\t'; load data local infile "/home/suyuan09/etl/hainiu/orc2mysql/myindex5${yymmdd}" into table suyuan09_etl_orcindex5mysql fields terminated by '\t'; load data local infile "/home/suyuan09/etl/hainiu/orc2mysql/myspider${yymmdd}" into table suyuan09_etl_orcspidermysql fields terminated by '\t'; load data local infile "/home/suyuan09/etl/hainiu/orc2mysql/myip${yymmdd}" into table suyuan09_etl_orcipmysql fields terminated by '\t'; eof
报表展示
其中 mysql没有自带排序函数,自己写一个
热力图参考之前我之前的博客 其中之前是用 c# 写的,这里用java + spring 改写一下
思路看之前的博客这里放代码
经纬度转换类:lngandlatutil
package suyuan.web; import java.io.bufferedreader; import java.io.ioexception; import java.io.inputstreamreader; import java.io.unsupportedencodingexception; import java.net.malformedurlexception; import java.net.url; import java.net.urlconnection; public class lngandlatutil { public object[] getcoordinate(string addr) throws ioexception { string lng = null;// 经度 string lat = null;// 纬度 string address = null; try { address = java.net.urlencoder.encode(addr, "utf-8"); } catch (unsupportedencodingexception e1) { e1.printstacktrace(); } string key = "你的秘钥"; string url = string.format("http://api.map.baidu.com/geocoder?address=%s&output=json&key=%s", address, key); url myurl = null; urlconnection httpsconn = null; try { myurl = new url(url); } catch (malformedurlexception e) { e.printstacktrace(); } inputstreamreader insr = null; bufferedreader br = null; try { httpsconn = (urlconnection) myurl.openconnection();// 不使用代理 if (httpsconn != null) { insr = new inputstreamreader(httpsconn.getinputstream(), "utf-8"); br = new bufferedreader(insr); string data = null; int count = 1; while ((data = br.readline()) != null) { if (count == 5) { try{ lng = (string) data.subsequence(data.indexof(":") + 1, data.indexof(","));// 经度 count++; } catch(stringindexoutofboundsexception e) { e.printstacktrace(); } } else if (count == 6) { lat = data.substring(data.indexof(":") + 1);// 纬度 count++; } else { count++; } } } } catch (ioexception e) { e.printstacktrace(); } finally { if (insr != null) { insr.close(); } if (br != null) { br.close(); } } return new object[] { lng, lat }; } }
ipdto:(数据库映射类)
package suyuan.entity; public class ipdto { public string top; public integer num; public string gettop() { return top; } public void settop(string top) { this.top = top; } public integer getnum() { return num; } public void setnum(integer num) { this.num = num; } }
ip:(热力图json类)
package suyuan.entity; public class ip { public string lng ; public string lat ; public int count ; public string getlng() { return lng; } public void setlng(string lng) { this.lng = lng; } public string getlat() { return lat; } public void setlat(string lat) { this.lat = lat; } public int getcount() { return count; } public void setcount(int count) { this.count = count; } }
dao层转换方法
public list<ip> getip() throws sqlexception { list<ipdto> ipdto = null; list<ip> iplist=new arraylist<ip>(); // 编写sql语句 string sql = "select top,num from `suyuan09_etl_orcipmysql`"; // 占位符赋值? // 执行 ipdto = qr.query(sql, new beanlisthandler<ipdto>(ipdto.class)); for(ipdto ips: ipdto) { ip ip=new ip(); integer num = ips.getnum(); string top = ips.gettop(); // 封装 lngandlatutil getlatandlngbybaidu = new lngandlatutil(); object[] o = null; try { o = getlatandlngbybaidu.getcoordinate(top); } catch (ioexception e) { // todo auto-generated catch block e.printstacktrace(); } ip.setlng(string.valueof(o[0])); ip.setlat(string.valueof(o[1])); ip.setcount(num); iplist.add(ip); } // 返回 return iplist; }
控制器调用返回json:
@requestmapping("/getip") public @responsebody list<ip> getip()throws exception{ return studentservice.getip(); }
jsp页面显示:
<%@ page language="java" import="java.util.*" pageencoding="utf-8"%> <%@ taglib uri="http://java.sun.com/jsp/jstl/core" prefix="c"%> <%@ taglib uri="http://java.sun.com/jsp/jstl/fmt" prefix="fmt"%> <!doctype html> <html> <head > <meta charset="utf-8"> <script type="text/javascript" src="http://api.map.baidu.com/api?v=2.0&ak=1freir62vfboc2vgrbnragyutlkgoiih"></script> <script type="text/javascript" src="http://api.map.baidu.com/library/heatmap/2.0/src/heatmap_min.js"></script> <script type="text/javascript" src="${pagecontext.request.contextpath}/js/jquery-1.9.1.js"></script> <title></title> <style type="text/css"> ul,li{list-style: none;margin:0;padding:0;float:left;} html{height:100%} body{height:100%;margin:0px;padding:0px;font-family:"微软雅黑";} #container{height:700px;width:100%;} #r-result{width:100%;} </style> </head> <body> <form id="form1" runat="server"> <div> <div id="container"></div> <div id="r-result"> <input type="button" onclick="openheatmap();" value="显示热力图"/><input type="button" onclick="closeheatmap();" value="关闭热力图"/> </div> </div> </form> </body> </html> <script type="text/javascript"> var map = new bmap.map("container"); // 创建地图实例 var point = new bmap.point(118.906886, 31.895532); map.centerandzoom(point, 15); // 初始化地图,设置中心点坐标和地图级别 map.enablescrollwheelzoom(); // 允许滚轮缩放 if (!issupportcanvas()) { alert('热力图目前只支持有canvas支持的浏览器,您所使用的浏览器不能使用热力图功能~') } heatmapoverlay = new bmaplib.heatmapoverlay({ "radius": 20 }); map.addoverlay(heatmapoverlay); heatmapoverlay.setdataset({ data: function () { var serie = []; $.ajax({ url: "${pagecontext.request.contextpath}/getip", datatype: "json", async: false, success: function (datajson) { for (var i = 0; i < datajson.length; i++) { var item = { //name: res.data.titlelist7[i], //value: randomdata() lat: datajson[i].lat, lng: datajson[i].lng, count: datajson[i].count }; serie.push(item); } } }); return serie; } (), max: 100 }); //是否显示热力图 function openheatmap() { heatmapoverlay.show(); } function closeheatmap() { heatmapoverlay.hide(); } closeheatmap(); function setgradient() { /*格式如下所示: { 0:'rgb(102, 255, 0)', .5:'rgb(255, 170, 0)', 1:'rgb(255, 0, 0)' }*/ var gradient = {}; var colors = document.queryselectorall("input[type='color']"); colors = [].slice.call(colors, 0); colors.foreach(function (ele) { gradient[ele.getattribute("data-key")] = ele.value; }); heatmapoverlay.setoptions({ "gradient": gradient }); } //判断浏览区是否支持canvas function issupportcanvas() { var elem = document.createelement('canvas'); return !!(elem.getcontext && elem.getcontext('2d')); } </script>
图表也参考我之前的博客
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