window-functions

问题 I need to formulate a mysql query to select values normalized this way: normalized = (value-min(values))/(max(values)-min(values)) My attempt looks like this: select Measurement_Values.Time, ((Measurement_Values.Value-min(Measurement_Values.Value))/(max(Measurement_Values.Value)-min(Measurement_Values.Value))) from Measurement_Values where Measurement_Values.Measure_ID = 49 and Measurement_Values.time >= '2020-05-30 00:00' but is obviously wrong as it returns only one value. Can you help me

问题 I need to formulate a mysql query to select values normalized this way: normalized = (value-min(values))/(max(values)-min(values)) My attempt looks like this: select Measurement_Values.Time, ((Measurement_Values.Value-min(Measurement_Values.Value))/(max(Measurement_Values.Value)-min(Measurement_Values.Value))) from Measurement_Values where Measurement_Values.Measure_ID = 49 and Measurement_Values.time >= '2020-05-30 00:00' but is obviously wrong as it returns only one value. Can you help me

问题 New to Python here and trying to see if there is a more elegant solution. I have a time series data of telematics devices that has motion indicator. I need to expand the motion indicator to +/- 1 row of the actual motion start and stop (denoted by motion2 column below). I was doing it in SQL using case statements and lead and lag window functions. Trying to convert my codes to python... Here is the data. import pandas as pd data = {'device':[1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2], 'time

问题 I am having a Spark SQL DataFrame with data and what I'm trying to get is all the rows preceding current row in a given date range. So for example I want to have all the rows from 7 days back preceding given row. I figured out I need to use a Window Function like: Window \ .partitionBy('id') \ .orderBy('start') and here comes the problem. I want to have a rangeBetween 7 days, but there is nothing in the Spark docs I could find on this. Does Spark even provide such option? For now I'm just

问题 I have a table and in this table i have data is not properly loaded data integrity issue ,since this is a dimension table we need to maintain the effective_dt_from and effective_dt_to and version correctly ,below is the table and sample data create table TEST ( LOC_SID NUMBER(38,0), CITY VARCHAR2(180 BYTE), POSTAL_CD VARCHAR2(15 BYTE), EFFECTIVE_DT_FROM DATE, EFFECTIVE_DT_TO DATE, VERSION NUMBER(38,0) ); Insert into TEST values (25101,'Assam',1153,to_date('01.01.00 00:00:00','DD.MM.YY HH24:MI

问题 I do understand window functions and group by separately. But what happens when you use both a window function and a group by clause in the same query ? Are the selected rows grouped first, then considered by the window function ? Or does the window function executes first, then the resulting values are grouped by group by ? Something else ? 回答1: Quote from the manual: If the query contains any window functions, these functions are evaluated after any grouping, aggregation, and HAVING

问题 I do understand window functions and group by separately. But what happens when you use both a window function and a group by clause in the same query ? Are the selected rows grouped first, then considered by the window function ? Or does the window function executes first, then the resulting values are grouped by group by ? Something else ? 回答1: Quote from the manual: If the query contains any window functions, these functions are evaluated after any grouping, aggregation, and HAVING

问题 I do understand window functions and group by separately. But what happens when you use both a window function and a group by clause in the same query ? Are the selected rows grouped first, then considered by the window function ? Or does the window function executes first, then the resulting values are grouped by group by ? Something else ? 回答1: Quote from the manual: If the query contains any window functions, these functions are evaluated after any grouping, aggregation, and HAVING

问题 I have never queried for such a thing before and not sure how possible it is. Let's say I have the following table: user_id date event 22 2012-05-02 11:02:39 login 22 2012-05-02 11:02:53 send_message 22 2012-05-02 11:03:28 logout 22 2012-05-02 11:04:09 login 22 2012-05-02 11:03:16 send_message 22 2012-05-02 11:03:43 search_run How can I calculate the percent of time a user logs in and within 2 minutes sends a message? 回答1: For a given user: SELECT round(count(*) FILTER (WHERE sent_in_time) *

问题 I need to get one column(revision) maximum value based on another column(drawingNumber). Can anyone tell me the JPA query for this functionality. I have written the following query and this query is not working. Please help me how to write MAX and OVER (PARTITION BY) functions in JPA query. @Query("select dr FROM (SELECT MAX(dr.revision) over (PARTITION BY d.drawing_number) AS latest_revision FROM DrawingRate dr JOIN dr.drawing d JOIN d.modifiedBy mb WHERE mb.Id=:Id OR piu.Id=:Id ORDER BY d