SELECT

DQL now supports projections and aggregates in addition to SELECT * operations. You can select specific fields, perform calculations, and use aggregate functions like COUNT, SUM, AVG, MIN, and MAX.

SELECT Statements

The following syntax outlines the basic structure and optional clauses you can use within your SELECT statements:

DQL

SELECT [DISTINCT] projection
FROM your_collection_name
[WHERE condition]
[GROUP BY groupby_expression_1, groupby_expression_2, ...]
[HAVING condition]
[ORDER BY orderby_expression_1, orderby_expression_2, ... [ASC|DESC]]
[LIMIT limit_value]
[OFFSET number_of_documents_to_skip]

Where projection can be:

* - Returns all fields from the documents
field1, field2, ... - Returns specific fields
expression AS alias - Returns calculated values with custom names
Aggregate functions like COUNT(*), SUM(field), etc.

For instance, retrieve all documents in the cars collection WHERE the color property is set to the value ‘blue’ :

DQL

SELECT * FROM cars WHERE color = 'blue'

To perform a SELECT and receive all document fields, including an embedded MAP:

Clauses for Filtering

The following table provides an overview of the different clauses you can use to define specific conditions and calculations within your DQL SELECT statements to provide more granular control over your queries:

Clause	Description
FROM	The required clause specifying the collection containing the documents for retrieval. (See FROM)
WHERE	Applies filtering conditions to restrict the documents included in the result set. (See WHERE)
GROUP BY	Groups documents based on one or more expressions for aggregate calculations. (See GROUP BY)
HAVING	Filters grouped results based on aggregate conditions. (See HAVING)
ORDER BY	Specifies the sorting order of the result set based on one or more expressions. (See ORDER BY)
LIMIT	Restricts the number of documents included in the result set. (See LIMIT)
OFFSET	Skips a specific number of documents before returning the result set. (See OFFSET)

FROM

Required in each SELECT statement you write in DQL, the FROM element identifies the collection for document retrieval.

DQL

SELECT *
FROM your_collection_name

For example, a SELECT statement querying documents from the cars collection:

DQL

SELECT * FROM cars

WHERE

The WHERE clause filters data based on either an expression or a set of conditions that narrow the result set returned to you:

DQL

SELECT *
FROM your_collection_name
WHERE [condition]

For example, here is a basic SELECT statement querying documents from the cars collection based on a given address:

DQL

SELECT * FROM cars
WHERE location.address = '123 Main St, San Francisco, CA 98105'

To demonstrate a more complex query, here is a SELECT statement that queries using multiple expressions and logical operators to further refine the criteria for document retrieval:

DQL


SELECT * FROM cars
WHERE color = 'blue' AND features.trim = 'Standard' OR features.mileage > 10000

ORDER BY

With the ORDER BY clause, if you’d like, you can integrate calculations or expressions in your SELECT statement. Then sort the resulting documents to return in either ascending (ASC) or descending (DESC) alphabetical order:

DQL

SELECT *
FROM your_collection_name
ORDER BY expression_1, expression_2, ... [ASC|DESC]

For example, here is a simple SELECT statement that uses the ORDER BY clause to query and sort documents from the cars collection in descending (DESC) alphabetical order based on the field value set for the color property:

DQL

SELECT *
FROM cars ORDER BY color DESC

In this syntax:

your_collection_name is the name of the collection from which you want to retrieve the data.
expression_1, expression_2, ... are the expressions evaluated to sort the result. Expressions are resolved in order.
[ASC|DESC] is an optional parameter that specifies the sort order. If omitted, the default sort order is ascending (ASC). To sort in descending order, you can specify DESC.

Example In this example, the result set from the query will be sorted in descending order based on the values in the field:

DQL

-- Sort by a given field_name
SELECT *
FROM your_collection_name
ORDER BY field_name DESC

For instance, here "blue" cars return first and other cars sort by the natural order in the collection:

DQL

SELECT *
FROM cars
ORDER BY color = 'blue'

Sort Order by Object Type

In DQL, the hierarchy for comparing and sorting objects varies based on the following criteria:

If ascending (ASC) order operations:
- boolean
- number
- binary
- string
- array
- object
- null
- missing
If descending (DESC) order operations, sorting order is reversed:
- missing
- null
- object
- array
- string
- binary
- number
- boolean
If evaluating values, true results are prioritized and ordered first followed by false results.

Expressing Sort Order

Unless explicitly defined as DESC in your query, Ditto defaults to sorting in ascending (ASC). So, if you want to sort in ascending order, you do not have to express that in your query.

LIMIT

The LIMIT clause is used to restrict the number of documents returned by a query, allowing you to specify a maximum limit on the number of documents to be included in the result set:

DQL

SELECT *
FROM your_collection_name
LIMIT limit_value

In this syntax:

your_collection_name is the name of the collection from which you want to retrieve the data.
limit_value is the maximum number of documents you want to include in the result set.

For example, only return the first 10 documents from the your_collection_name collection:

DQL

SELECT *
FROM your_collection_name
LIMIT 10

OFFSET

The OFFSET clause is used to specify the number of records to skip before starting to return documents from the query result:

DQL

SELECT *
FROM your_collection_name
OFFSET number_of_items_to_skip

In this syntax:

your_collection_name is the name of the collection from which you want to retrieve the data.
number_of_items_to_skip is the number of items before returning the result set.

Using OFFSET with LIMIT is a common way to utilize OFFSET; for example:

DQL

SELECT *
FROM your_collection_name
LIMIT 10
OFFSET 10

Projections

Projections allow you to specify exactly which fields or calculated values to return from your query, rather than returning entire documents. This reduces data transfer and processing overhead.

Basic Field Selection

Select specific fields from documents:

DQL

SELECT make, model, year FROM cars

Aliasing

Use aliases to rename fields in your results:

DQL

SELECT make AS manufacturer, model AS car_model FROM cars

Default aliases are assigned if not specified:

Simple field references use the field name as the alias
Expressions get aliases like ($1), ($2), etc.

Calculated Fields

Create new fields using expressions:

DQL

SELECT make, model, price * 0.9 AS discounted_price FROM cars

DISTINCT Results

Remove duplicate rows from your results:

DQL

SELECT DISTINCT color FROM cars

When using DISTINCT, all projections are buffered in memory to enforce uniqueness, which increases memory requirements. Avoid using DISTINCT when the _id field is included, as results are already unique.

Aggregate Functions

Aggregate functions perform calculations across multiple documents and return a single result. DQL supports the following aggregate functions:

COUNT

Count documents or non-null values:

DQL

-- Count all documents
SELECT COUNT(*) FROM cars

-- Count non-null values in a field
SELECT COUNT(color) FROM cars

-- Count distinct values
SELECT COUNT(DISTINCT color) FROM cars

SUM

Calculate the sum of numeric values:

DQL

SELECT SUM(price) AS total_value FROM cars

-- Sum distinct values only
SELECT SUM(DISTINCT price) FROM cars

AVG

Calculate the average of numeric values:

DQL

SELECT AVG(mileage) AS average_mileage FROM cars

MIN and MAX

Find minimum and maximum values:

DQL

SELECT MIN(year) AS oldest_year, MAX(year) AS newest_year FROM cars

Combining Aggregates

Use multiple aggregate functions in a single query:

DQL

SELECT 
  COUNT(*) AS total_cars,
  AVG(price) AS avg_price,
  MIN(price) AS lowest_price,
  MAX(price) AS highest_price
FROM cars

GROUP BY

Group results and calculate aggregates for each group:

DQL

SELECT color, COUNT(*) AS count, AVG(price) AS avg_price 
FROM cars 
GROUP BY color

When using aggregates with GROUP BY, non-aggregate projections must be part of the GROUP BY clause:

DQL

-- This works: 'make' is in GROUP BY
SELECT make, COUNT(*) AS model_count 
FROM cars 
GROUP BY make

-- This would fail: 'model' is not in GROUP BY
-- SELECT make, model, COUNT(*) FROM cars GROUP BY make

HAVING

Filter grouped results based on aggregate values:

DQL

SELECT color, COUNT(*) AS count 
FROM cars 
GROUP BY color 
HAVING COUNT(*) > 5

Aggregate functions form a “dam” in the execution pipeline - all documents must be processed before results can be returned. This differs from non-aggregate queries which can stream results.

Statements

Types and Functions

Reference

SELECT Statements

Clauses for Filtering

FROM

WHERE

ORDER BY

Sort Order by Object Type

Expressing Sort Order

LIMIT

OFFSET

Projections

Basic Field Selection

Aliasing

Calculated Fields

DISTINCT Results

Aggregate Functions

COUNT

SUM

AVG

MIN and MAX

Combining Aggregates

GROUP BY

HAVING

Statements

Types and Functions

Reference

​SELECT Statements

​Clauses for Filtering

​FROM

​WHERE

​ORDER BY

​Sort Order by Object Type

​Expressing Sort Order

​LIMIT

​OFFSET

​Projections

​Basic Field Selection

​Aliasing

​Calculated Fields

​DISTINCT Results

​Aggregate Functions

​COUNT

​SUM

​AVG

​MIN and MAX

​Combining Aggregates

​GROUP BY

​HAVING

SELECT Statements

Clauses for Filtering

FROM

WHERE

ORDER BY

Sort Order by Object Type

Expressing Sort Order

LIMIT

OFFSET

Projections

Basic Field Selection

Aliasing

Calculated Fields

DISTINCT Results

Aggregate Functions

COUNT

SUM

AVG

MIN and MAX

Combining Aggregates

GROUP BY

HAVING