MySQL Solution for Average Time of Process Per Machine Problem
Intuition\n Describe your first thoughts on how to solve this problem. \nThe query aims to calculate the average time taken by each machine to complete a proces
# Intuition\n<!-- Describe your first thoughts on how to solve this problem. -->\nThe query aims to calculate the average time taken by each machine to complete a process. It involves retrieving the start and end timestamps for each process on each machine and then calculating the average processing time for each machine.\n\n# Approach\n<!-- Describe your approach to solving the problem. -->\n1. The inner subquery groups the activity records by machine_id and process_id and uses conditional statements (CASE WHEN) to determine the start and end timestamps for each process.\n1. The subquery calculates the maximum start timestamp and maximum end timestamp for each process using the MAX() function.\n1. The outer query uses the results from the subquery and calculates the average processing time for each machine by subtracting the start time from the end time.\n1. The ROUND() function is used to round the average processing time to 3 decimal places.\n1. Finally, the outer query groups the results by machine_id and retrieves the machine ID along with the corresponding average processing time.\n\n# Complexity\n- Time complexity:\n<!-- Add your time complexity here, e.g. $$O(n)$$ -->\nThe time complexity of this query depends on the number of records in the Activity table. Let\'s denote this number as N.\n\n- The inner subquery performs a grouping operation on the Activity table, which requires iterating through all N records. Therefore, its time complexity is O(N).\n- The outer query performs a grouping operation on the results of the subquery, which also requires iterating through all N records. Thus, its time complexity is O(N).\nOverall, the time complexity of the query is O(N).\n\n- Space complexity:\n<!-- Add your space complexity here, e.g. $$O(n)$$ -->\nThe space complexity is determined by the storage of the intermediate subquery results and the final result set. Since the subquery groups the records by machine_id and process_id, the number of rows in the subquery result will be equal to or less than the number of records in the Activity table. Therefore, the space complexity is O(N) to store the intermediate subquery results. The final result set will contain a row for each unique machine_id, so its space complexity is O(M), where M is the number of unique machines.\nHence, the overall space complexity is O(N + M).\n\n# Code\n```\n# Write your MySQL query statement below\nSELECT machine_id, ROUND(AVG(end_time - start_time), 3) AS processing_time\nFROM (\n    SELECT machine_id, process_id, MAX(CASE WHEN activity_type = \'start\' THEN timestamp END) AS start_time,\n           MAX(CASE WHEN activity_type = \'end\' THEN timestamp END) AS end_time\n    FROM Activity\n    GROUP BY machine_id, process_id\n) AS subquery\nGROUP BY machine_id;\n\n```
['MySQL']