使用SQL实现车流量的计算的示例代码

目录

• 卡口转换率
• 1、查出每个地区下每个路段下的车流量
• 2、通过错位连接获取每辆车的行车记录
• 3、获取行车过程中的车辆数
• 4、获取每个卡口的总车辆数
• 5、求出卡口之间的转换率

卡口转换率

将数据导入hive，通过SparkSql编写sql,实现不同业务的数据计算实现，主要讲述车辆卡口转换率，卡口转化率：主要计算不同卡口下车辆之间的流向，求出之间的转换率。

1、查出每个地区下每个路段下的车流量

select
	car,
	monitor_id,
	action_time,
	ROW_NUMBER () OVER (PARTITION by car
ORDER by
	action_time) as n1
FROM
	traffic.hive_flow_action

此结果做为表1，方便后面错位连接使用

2、通过错位连接获取每辆车的行车记录

通过表1的结果，与自身进行错位链接，并以车牌为分区，拼接经过卡口的过程

(select
	t1.car,
	t1.monitor_id,
	concat(t1.monitor_id,
	"->",
	t2.monitor_id) as way
from
	(
	select
		car,
		monitor_id,
		action_time,
		ROW_NUMBER () OVER (PARTITION by car
	ORDER by
		action_time) as n1
	FROM
		traffic.hive_flow_action) t1
left join (
	select
		car,
		monitor_id,
		action_time,
		ROW_NUMBER () OVER (PARTITION by car
	ORDER by
		action_time) as n1
	FROM
		traffic.hive_flow_action) t2 on
	t1.car = t2.car
	and t1.n1 = t2.n1-1
where
	t2.action_time is not null)

获取到每辆车的一个行车记录，经过的卡口

3、获取行车过程中的车辆数

获取卡口1~卡口2，…等的车辆数有哪些,即拿上面的行车记录字段进行分区在进行统计

(select
	s1.way,
	COUNT(1) sumCar
from
	--行车过程
(select
		t1.car,
		t1.monitor_id,
		concat(t1.monitor_id,
		"->",
		t2.monitor_id) as way
	from
		(
		select
			car,
			monitor_id,
			action_time,
			ROW_NUMBER () OVER (PARTITION by car
		ORDER by
			action_time) as n1
		FROM
			traffic.hive_flow_action) t1
	left join (
		select
			car,
			monitor_id,
			action_time,
			ROW_NUMBER () OVER (PARTITION by car
		ORDER by
			action_time) as n1
		FROM
			traffic.hive_flow_action) t2 on
		t1.car = t2.car
		and t1.n1 = t2.n1-1
	where
		t2.action_time is not null)s1
group by way)

4、获取每个卡口的总车辆数

获取每个卡口最初的车辆数，方便后面拿行车轨迹车辆数/总车辆数，得出卡口之间的转换率

select
	monitor_id ,
	COUNT(1) sumall
from
	traffic.hive_flow_action
group by
	monitor_id

5、求出卡口之间的转换率

select
	s2.way,
	s2.sumCar / s3.sumall zhl
from
	(
	select
		s1.way,
		COUNT(1) sumCar
	from
		--行车过程
(
		select
			t1.car,
			t1.monitor_id,
			concat(t1.monitor_id,
			"->",
			t2.monitor_id) as way
		from
			(
			select
				car,
				monitor_id,
				action_time,
				ROW_NUMBER () OVER (PARTITION by car
			ORDER by
				action_time) as n1
			FROM
				traffic.hive_flow_action) t1
		left join (
			select
				car,
				monitor_id,
				action_time,
				ROW_NUMBER () OVER (PARTITION by car
			ORDER by
				action_time) as n1
			FROM
				traffic.hive_flow_action) t2 on
			t1.car = t2.car
			and t1.n1 = t2.n1-1
		where
			t2.action_time is not null)s1
	group by
		way)s2
left join
	--每个卡口总车数
(
	select
		monitor_id ,
		COUNT(1) sumall
	from
		traffic.hive_flow_action
	group by
		monitor_id) s3 on
	split(s2.way,
	"->")[0]= s3.monitor_id

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原文地址：https://blog.csdn.net/llAl_lAll/article/details/123134334