Struct QueryBuilder 

pub struct QueryBuilder { /* private fields */ }

Query builder for ElastiCube queries

Provides a fluent API for building and executing queries against a cube. Supports both SQL queries and a DataFrame-style fluent API.

Examples

// SQL query
let results = cube.query()
    .sql("SELECT region, SUM(sales) FROM cube GROUP BY region")
    .execute()
    .await?;

// Fluent API query
let results = cube.query()
    .select(&["region", "SUM(sales) as total_sales"])
    .filter("sales > 1000")
    .group_by(&["region"])
    .order_by(&["total_sales DESC"])
    .limit(10)
    .execute()
    .await?;

Implementations

impl QueryBuilder

pub fn sql(self, query: impl Into<String>) -> Self

Execute a raw SQL query

Arguments

• query - SQL query string (can reference the cube as “cube”)

Example

let results = cube.query()
    .sql("SELECT region, SUM(sales) as total FROM cube GROUP BY region")
    .execute()
    .await?;

pub fn select(self, columns: &[impl AsRef<str>]) -> Self

Select specific columns or expressions

Arguments

• columns - Column names or SQL expressions

Example

.select(&["region", "product", "SUM(sales) as total_sales"])

pub fn filter(self, condition: impl Into<String>) -> Self

Add a WHERE filter condition

Arguments

• condition - SQL filter expression

Example

.filter("sales > 1000 AND region = 'North'")

pub fn where_clause(self, condition: impl Into<String>) -> Self

Add WHERE filter (alias for filter)

pub fn group_by(self, columns: &[impl AsRef<str>]) -> Self

Group by columns

Arguments

• columns - Column names to group by

Example

.group_by(&["region", "product"])

pub fn order_by(self, columns: &[impl AsRef<str>]) -> Self

Order results by columns

Arguments

• columns - Column names with optional ASC/DESC

Example

.order_by(&["total_sales DESC", "region ASC"])

pub fn limit(self, count: usize) -> Self

Limit the number of results

Example

.limit(100)

pub fn offset(self, count: usize) -> Self

Skip a number of results

Example

.offset(50)

pub fn slice(self, dimension: impl AsRef<str>, value: impl AsRef<str>) -> Self

OLAP Operation: Slice - filter on a single dimension

Example

.slice("region", "North")

pub fn dice(self, filters: &[(impl AsRef<str>, impl AsRef<str>)]) -> Self

OLAP Operation: Dice - filter on multiple dimensions

Example

.dice(&[("region", "North"), ("product", "Widget")])

pub fn drill_down( self, _parent_level: impl AsRef<str>, child_levels: &[impl AsRef<str>], ) -> Self

OLAP Operation: Drill-down - navigate down a hierarchy

This selects data at a more granular level by including a lower-level dimension.

Example

// Drill down from year to month
.drill_down("year", &["year", "month"])

pub fn roll_up(self, dimensions_to_remove: &[impl AsRef<str>]) -> Self

OLAP Operation: Roll-up - aggregate across dimensions

This aggregates data by removing one or more dimensions from grouping.

Example

.roll_up(&["region"]) // Aggregate across all regions

pub async fn execute(self) -> Result<QueryResult>

Execute the query and return results

Returns

A QueryResult containing the data and metadata