一、停歇分析
1.每日停息軌跡分析
val s9_every_day_stop_time=sql("select to_date(gps_time) as gps_t, count(*)*2/3600 as num_trajectory from trajectory where vme_id='S901100009' and speed<1 group by to_date(gps_time) order by to_date(gps_time) ")
//保存數(shù)據(jù)到本地
s9_every_day_stop_time.repartition(1).write.format("csv").save("file:/home/hadoop/mydata/s9_every_day_stop_time")
2.運(yùn)營(yíng)時(shí)間運(yùn)營(yíng)里程分析
val s9_operation= sql(" select a.gps_t, day(a.gps_t) as day,a.num_trajectory, a.num_car, a.avg_speed, a.num_trajectory*2/a.num_car/3600 as avg_day_operation_time, a.avg_speed* a.num_trajectory*2/a.num_car/1000 as avg_day_operation_distance from (select distinct to_date(gps_time) as gps_t, count(gps_time) as num_trajectory ,count(distinct vme_id) as num_car, avg(speed) avg_speed from trajectory where vme_id='S901100009' group by to_date(gps_time) order by gps_t) as a")
//保存數(shù)據(jù)到本地
s9_operation.repartition(1).write.format("csv").save("file:/home/hadoop/mydata/s9_operation")
3.作業(yè)時(shí)間作業(yè)里程分析
val s9_work = sql("select a.gps_t, day(a.gps_t) as day, a.num_trajectory, a.num_car, a.avg_speed, a.num_trajectory*2/a.num_car/3600 as avg_day_work_time, a.avg_speed* a.num_trajectory*2/a.num_car/1000 as avg_day_work_distance from (select distinct to_date(gps_time) as gps_t, count(gps_time) as num_trajectory ,count(distinct vme_id) as num_car, avg(speed) avg_speed from trajectory where vme_id='S901100009' and speed>1 and work_deep>300 group by to_date(gps_time) order by gps_t) as a")
//保存數(shù)據(jù)到本地
s9_work.repartition(1).write.format("csv").save("file:/home/hadoop/mydata/s9_work)
