How Group By Works On Multiple Columns

Carole Stephens
• Wednesday, 11 November, 2020
• 11 min read

The following statement groups rows with the same values in both category and produced columns : In SQL, the group by statement is used along with aggregate functions like SUM, AVG, MAX, etc.

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The median rebounds assists for players in position G on team A is 11. The sequence of the columns in the GROUP BY clause has no effect on the end result of a statement.

As an example, let us add some aggregation functions to the previous SELECT statement: This aggregation level is lower than that of a statement in which the grouping is equal to or .

Exercise 10.5: For each combination of won–lost sets, get the number of matches won. Exercise 10.6: For each combination of year–month, get the number of committee members who started in that year and that month.

Exercise 10.7: Group the matches on town of player and division of team, and get the sum of the sets won for each combination of towndivision. Exercise 10.8: For each player who lives in Inglewood, get the name, initials, and number of penalties incurred by him or her.

EF uses Line syntax when you send queries to the database. When I was first learning MVC, I was coming from a background where I used raw SQL queries exclusively in my work flow.

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One of the particularly difficult stumbling blocks I had in translating the SQL in my head to Line was the Group By statement. We’ll walk through what Line is, and follow up with multiple examples of how to use Group By.

Line stands for Language Integrated Query, which, admittedly, doesn’t explain too much about what it is. The simplest summary is that Line lets you write SQL-style queries in .NET languages, like C# and VB.

The example above uses to Line to query from a database, which is a very common use case. However, you could also query other data sources, like an XML document or a .NET collection.

There are also some types of queries that are simply easier to write in one version vs. another. For the rest of this article, I’ll be showing how to use Group By in both versions.

We also want to keep track of who submitted the recipe, so we have an Author column. Just keep in mind that you could take any of the following examples and use the foreign keys to group by instead of a text field.

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Let’s also imagine that we have the following data in the Recipes table: IDCategoryAuthorTitlePrepTime1AppetizerSally McdonaldSeven-Layer Taco Dip302AppetizerSally McdonaldBacon Jalapeño Popper Puffs453DinnerHugo Sharp Sweet and Sour Chicken1004DinnerHugo SharpHamburger Stroganoff205DinnerSally McdonaldOven-Roasted Greek Potatoes906DessertHugo SharpGrandma's Butterscotch Pie557DessertVicki HawkinsClassic Strawberry Shortcake30Now, let’s say we want to find out which of our authors have been most productive.

We want to count the number of recipes, and group by the author’s name. AuthorRecipeCountHugo Sharp3Sally McDonald3Vicki Hawkins1What we’ve done is to create groups out of the authors, which has the effect of getting rid of duplicate data.

I think that, in my own head, I always thought of GROUP BY as the “magical get rid of the duplicate rows” command. Now, let’s imagine that we wanted to find our most prolific authors, like we did in the SQL query in the last section.

In our new anonymous object, we’ve added the RecipeCount property, and assigned the count to it. AuthorCategoryRecipeCountHugo SharpDinner2Hugo SharpDessert1Sally McdonaldAppetizer2Sally McdonaldDinner1Vicki HawkinsDessert1In order to group by multiple columns, the structure of our queries is basically the same as before.

If you want to be able to test your Line syntax without having to build and re-build your project, check out Linked. You can make quick changes to your code and get instant feedback on the results of that Line query.

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The biggest thing I can see missing from the free version is AutoComplete syntax, but the tool is still useful without that. To be perfectly honest, whenever I have to use Group By in a query, I’m tempted to return to raw SQL.

However, once I start to add in more complex features, like table joins, ordering, a bunch of conditionals, and maybe even a few other things, I typically find SQL easier to reason about. Grouping is one of the most important tasks that you have to deal with while working with the databases.

The GROUP BY clause is an optional clause of the SELECT statement that combines rows into groups based on matching values in specified columns. You often use the GROUP BY in conjunction with an aggregate function such as MIN, MAX, AVG, SUM, or COUNT to calculate a measure that provides the information for each group.

It is not mandatory to include an aggregate function in the SELECT clause. However, if you use an aggregate function, it will calculate the summary value for each group.

Place all rows with the same values in the department_id column in one group. For example, in the shipping department, there are 2 employees holding the shipping clerk job, 1 employee holding the stock clerk job, and 4 employees holding the stock manager job.

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The following statement also retrieves the phone numbers but instead of using the GROUP BY clause, it uses the DISTINCT operator. The result set is the same except that the one returned by the DISTINCT operator is not sorted.

The only difference is that the result set returns by MySQL query using GROUP BY clause is sorted and in contrast, the result set return by MySQL query using District clause is not sorted. The SELECT statement returns one row per group.

A column alias that is defined in the SELECT list. It can use a column alias for a derived table that is defined in the FROM clause.

A column of type text, next, or image. However, you can use a column of text, next, or image as an argument to a function that returns a value of a valid data type.

It can include a user-defined function that uses XML data type methods. It can include a computed column that uses XML data type methods.

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Groups the SELECT statement results according to the values in a list of one or more column expressions. CountryRegionSalesCanadaAlberta100CanadaBritish Columbia200CanadaBritish Columbia300United StatesMontana100This next query groups Country and Region and returns the aggregate sum for each combination of values.

The query result has 3 rows since there are 3 combinations of values for Country and Region. The TotalS ales for Canada and British Columbia is the sum of two rows.

In addition, it “rolls up” the results into subtotals and grand totals. To do this, it moves from right to left decreasing the number of column expressions over which it creates groups and the aggregation(s).

The query result has the same aggregations as the simple GROUP BY without the ROLL UP. In addition, it creates subtotals for each value of Country.

Using the table from the previous examples, this code runs a GROUP BY CUBE operation on Country and Region. The results are the equivalent of UNION All the specified groups.

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This example returns the union of the ROLL UP and CUBE results for Country and Region. The results are the same as this query that returns a union of the two GROUP BY statements.

For example, in GROUP BY ((), CUBE (Country, Region)) , both elements return a row for the grand total and both rows will be listed in the results. Specifies the empty group which generates the grand total.

NOTE: This syntax is provided for backward compatibility only. Specifies to include all groups in the results regardless of whether they meet the search criteria in the WHERE clause.

The DISTRIBUTED_AGG query hint forces the massively parallel processing (MPP) system to redistribute a table on a specific column before performing an aggregation. Only one column in the GROUP BY clause can have a DISTRIBUTED_AGG query hint.

After the query finishes, the redistributed table is dropped. NOTE: The DISTRIBUTED_AGG query hint is provided for backwards compatibility with earlier Parallel Data Warehouse versions and will not improve performance for most queries.

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By default, MPP already redistributes data as necessary to improve performance for aggregations. SQL removes Rows that do not meet the conditions in the WHERE clause before any grouping operation is performed.

A maximum of 12 grouping expressions is permitted when CUBE or ROLL UP is specified. For example, GROUP BY Column1, (Column2, ... ColumnN) is allowed in the standard but not in Transact-SQL.

The following error message is returned: “Incorrect syntax near the keyword 'cube'|'roll up'.” The following example is allowed: SELECT SUM (x) FROM T GROUP BY .

GROUPING Season supportedSupportedSupportedCUBENot supportedSupportedNot supportedROLLUPNot supportedSupportedNot supportedGrand total, such as GROUP BY ()Not supportedSupportedSupportedGROUPING_ID function supportedSupportedSupportedGROUPING functionSupportedSupportedSupportedWITH CUBESupportedSupportedSupportedWITH ROLLUPSupportedSupportedSupportedWITH CUBE or WITH ROLL UP “duplicate” grouping removalSupportedSupportedSupported The following example retrieves the total for each SalesOrderID from the SalesOrderDetail table. The following example retrieves the total sales for each year by using the Depart function.

The same expression must be present in both the SELECT list and GROUP BY clause. The following example finds the total amount for all sales on each day.

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One row containing the sum of all sales is returned for each day. This example uses the DISTRIBUTED_AGG query hint to force the appliance to shuffle the table on the Customer Key column before performing the aggregation.

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