aggregate-functions

问题 I want to show the given records in the following table into the specific format which is shown below in the table. Creating table: Test_1 CREATE TABLE Test_1 ( ColumnA varchar, ColumnB varchar ); Insertion of records: INSERT INTO Test_1 values('A101','B101'),('A102','B102'), ('A103','B103'),('A104','B104'), ('A105','B105'),('A106','B106'), ('A107','B107'),('A108','B108'), ('A109','B109'),('A201','B201'); I want to show the result like this: Expected Result : ColumnA ColumnX -----------------

问题 I am trying to solve an interesting problem, it's easy to just do a groupBy for aggregation like sum, count etc. But this problem is slightly different. Let me explain: This is my list of tuples: val repeatSmokers: List[(String, String, String, String, String, String)] = List( ("ID76182", "sachin", "kita MR.", "56308", "1990", "300"), ("ID76182", "KOUN", "Jana MR.", "56714", "1990", "100"), ("ID76182", "GANGS", "SKILL", "27539", "1990", "255"), ("ID76182", "GANGS", "SKILL", "27539", "1990",

问题 Let's say I have the following DataFrame : [Row(user='bob', values=[0.5, 0.3, 0.2]), Row(user='bob', values=[0.1, 0.3, 0.6]), Row(user='bob', values=[0.8, 0.1, 0.1])] I would like to groupBy user and do something like avg(values) where the average is taken over each index of the array values like this: [Row(user='bob', avgerages=[0.466667, 0.233333, 0.3])] How can I do this in PySpark? 回答1: You can expand array and compute average for each index. Python from pyspark.sql.functions import array

问题 Let's say I have the following DataFrame : [Row(user='bob', values=[0.5, 0.3, 0.2]), Row(user='bob', values=[0.1, 0.3, 0.6]), Row(user='bob', values=[0.8, 0.1, 0.1])] I would like to groupBy user and do something like avg(values) where the average is taken over each index of the array values like this: [Row(user='bob', avgerages=[0.466667, 0.233333, 0.3])] How can I do this in PySpark? 回答1: You can expand array and compute average for each index. Python from pyspark.sql.functions import array

问题 Let's say I have the following DataFrame : [Row(user='bob', values=[0.5, 0.3, 0.2]), Row(user='bob', values=[0.1, 0.3, 0.6]), Row(user='bob', values=[0.8, 0.1, 0.1])] I would like to groupBy user and do something like avg(values) where the average is taken over each index of the array values like this: [Row(user='bob', avgerages=[0.466667, 0.233333, 0.3])] How can I do this in PySpark? 回答1: You can expand array and compute average for each index. Python from pyspark.sql.functions import array

问题 I am trying to produce a results table with the last completed course date for each course code, as well as the last completed course code overall for each employee. Below is my query: SELECT employee_number, MAX(course_completion_date) OVER (PARTITION BY course_code) AS max_course_date, MAX(course_completion_date) AS max_date FROM employee_course_completion WHERE course_code IN ('M910303', 'M91301R', 'M91301P') GROUP BY employee_number This query produces the following error: 3504 : Selected

问题 I am trying to produce a results table with the last completed course date for each course code, as well as the last completed course code overall for each employee. Below is my query: SELECT employee_number, MAX(course_completion_date) OVER (PARTITION BY course_code) AS max_course_date, MAX(course_completion_date) AS max_date FROM employee_course_completion WHERE course_code IN ('M910303', 'M91301R', 'M91301P') GROUP BY employee_number This query produces the following error: 3504 : Selected

问题 I have this query: Select count(incidentnumber) as average from incidents Where IncidentStationGround <> firstpumparriving_deployedfromstation; I got a result, it's something like 20,000. But how can I convert this number to a percentage? Plus, I want the results in decimal, can I? 回答1: your query in comment should work cast count to decimal to achieve decimal percentage count(incidentnumber)::decimal*100 回答2: Assuming percentage of the total count: SELECT (count(incidentnumber) FILTER (WHERE

问题 Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted. This question already has answers here : Retrieving the last record in each group - MySQL (27 answers) Closed 10 months ago . I have this table for documents (simplified version here): +------+-------+--------------------------------------+ | id | rev | content | +------+-------+---------------------

问题 Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted. This question already has answers here : Retrieving the last record in each group - MySQL (27 answers) Closed 10 months ago . I have this table for documents (simplified version here): +------+-------+--------------------------------------+ | id | rev | content | +------+-------+---------------------