I’m trying to join 2 tables and count the number of entries for unique variables in one of the columns. In this case I’m trying to join 2 tables – patients and trials (patients has a FK to trials) and count the number of patients that show up in each trial. This is the code i have so far: The
Tag: aggregate
Why does this suggested solution prefer a different way of calculating percentages based on aggregations?
I’m working through a problem set from CMU’s public db systems course. I have the following two tables: Order Id CustomerId EmployeeId OrderDate RequiredDate ShippedDate ShipVia Freight ShipName ShipAddress ShipCity ShipRegion ShipPostalCode ShipCountry 10248 VINET 5 2012-07-04 2012-08-01 2012-07-16 3 16.75 Vins et alcools Chevalier 59 rue de l’Abbaye Reims Western Europe 51100 France 10249 TOMSP 6 2012-07-05 2012-08-16 2012-07-10
How to aggregate on multiple columns using SQL or spark SQL
I have following table: Expected output is: The aggregation computation involves 2 columns, is this supported in SQL? Answer In Spark SQL you can do it like this: or in one select: Higher-order aggregate function is used in this example. aggregate(expr, start, merge, finish) – Applies a binary operator to an initial state and all elements in the array, and
PostgreSQL subquery COUNT fails when the subquery is joined more than once
I have 2 tables: Table class: Table class_event, where I store events related to classes, such as “started” and “ended”. I need a query the amount of times each class has been started and ended. This works: But when I do exactly the same to get the amount of ended classes it shows incorrect amounts: Also, the query takes significantly
How to separate column values by condition (pivot) to fill one row
I have two tables that I’d like do a full outer join where the resulting view separates the values table into two separate columns with one row for each name_id. I have made one approach with a CASE expression to select by type and then use it with pandas to fill in the values and return distinct name_ids. Name Table
Get non-aggregated column values without joins MySQL
I’m using mysql 8.0 and the table I have has a lot of rows so the solutions from this link take too long to run. Table example: ID Name Value Category 1 a 5 alpha 2 b 7 beta 3 c 8 alpha 4 d 10 beta I would like to group it by category and then select the max
grouping equal values – aggregate function problem
I’ve created a table that lists venues in which several events take place. The same event in the same venue can have a different price. The last column calculates the total revenue for one venue. venue event totalprice sum Venue A Event A 5 30 Venue A Event A 10 30 Venue A Event B 5 30 Venue A Event
subquery double where + aggreate functions
I have table and rows I want to have sum of balance and payed for simple users with approvedAdminId (isSimpleUser = 1 AND approvedAdminId is not NULL) and for not simple users (isSimpleUser = 0) Expected Result Answer Output:
SQL duplicates despite grouping on all key variables?
I am new to SQL and use it for work, so I am going to censor the real names of columns going forward in the query below. I am writing a query where the necessary data is spread across 3 tables. I have a network with users who send and receive packages from different nodes, and I want to see
SQL Create a new calculated column based on values of multi rows and cols
I have a data about airline’s booking, using Oracle db, sample is structured as below: Recordlocator is booking code Sequencenmbr: whenever there is a change in booking, it records new status of a booking with higher Sequencenmbr. So the highest Sequencenmbr in the database shows the latest/current status of bookings Sequenceair: is the sequence of flights in bookings, it may