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1661. Average Time of Process per Machine
Description
Table: Activity
+----------------+---------+
| Column Name | Type |
+----------------+---------+
| machine_id | int |
| process_id | int |
| activity_type | enum |
| timestamp | float |
+----------------+---------+
The table shows the user activities for a factory website.
(machine_id, process_id, activity_type) is the primary key (combination of columns with unique values) of this table.
machine_id is the ID of a machine.
process_id is the ID of a process running on the machine with ID machine_id.
activity_type is an ENUM (category) of type ('start', 'end').
timestamp is a float representing the current time in seconds.
'start' means the machine starts the process at the given timestamp and 'end' means the machine ends the process at the given timestamp.
The 'start' timestamp will always be before the 'end' timestamp for every (machine_id, process_id) pair.
There is a factory website that has several machines each running the same number of processes. Write a solution to find the average time each machine takes to complete a process.
The time to complete a process is the 'end' timestamp minus the 'start' timestamp. The average time is calculated by the total time to complete every process on the machine divided by the number of processes that were run.
The resulting table should have the machine_id along with the average time as processing_time, which should be rounded to 3 decimal places.
Return the result table in any order.
The result format is in the following example.
Example 1:
Input: Activity table: +------------+------------+---------------+-----------+ | machine_id | process_id | activity_type | timestamp | +------------+------------+---------------+-----------+ | 0 | 0 | start | 0.712 | | 0 | 0 | end | 1.520 | | 0 | 1 | start | 3.140 | | 0 | 1 | end | 4.120 | | 1 | 0 | start | 0.550 | | 1 | 0 | end | 1.550 | | 1 | 1 | start | 0.430 | | 1 | 1 | end | 1.420 | | 2 | 0 | start | 4.100 | | 2 | 0 | end | 4.512 | | 2 | 1 | start | 2.500 | | 2 | 1 | end | 5.000 | +------------+------------+---------------+-----------+ Output: +------------+-----------------+ | machine_id | processing_time | +------------+-----------------+ | 0 | 0.894 | | 1 | 0.995 | | 2 | 1.456 | +------------+-----------------+ Explanation: There are 3 machines running 2 processes each. Machine 0's average time is ((1.520 - 0.712) + (4.120 - 3.140)) / 2 = 0.894 Machine 1's average time is ((1.550 - 0.550) + (1.420 - 0.430)) / 2 = 0.995 Machine 2's average time is ((4.512 - 4.100) + (5.000 - 2.500)) / 2 = 1.456
Solutions
Solution 1: Grouping and Aggregation
We can group by machine_id and use the AVG function to calculate the average time consumption of all process tasks on each machine. Since each process task on the machine has a pair of start and end timestamps, the time consumption of each process task can be calculated by subtracting the start timestamp from the end timestamp. Therefore, we can use the CASE WHEN or IF function to calculate the time consumption of each process task, and then use the AVG function to calculate the average time consumption of all process tasks on each machine.
Note that each machine has $2$ process tasks, so we need to multiply the calculated average time consumption by $2$.
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# Write your MySQL query statement below SELECT TMP.MACHINE_ID as machine_id, ROUND(SUM(TMP.TIME_DIFF)/COUNT(TMP.TIME_DIFF),3) AS processing_time FROM ( SELECT A.MACHINE_ID, ROUND(SUM(CASE WHEN A.ACTIVITY_TYPE = 'END' THEN A.TIMESTAMP ELSE 0 END ),3) - ROUND(SUM(CASE WHEN A.ACTIVITY_TYPE = 'START' THEN A.TIMESTAMP ELSE 0 END),3) AS 'TIME_DIFF' FROM ACTIVITY AS A GROUP BY A.MACHINE_ID, A.PROCESS_ID ) AS TMP GROUP BY TMP.MACHINE_ID -- SELECT machine_id, ROUND( AVG( CASE WHEN activity_type = 'start' THEN -timestamp ELSE timestamp END ) * 2, 3 ) AS processing_time FROM Activity GROUP BY 1;