Struct ArrayOfDoublesSketchBuilder 

pub struct ArrayOfDoublesSketchBuilder { /* private fields */ }

Builder for crate::tuple::ArrayOfDoublesSketch, mirroring upstream’s update_array_of_doubles_sketch::builder. lg_k defaults to 12, resize_factor to ResizeFactor::X8, p to 1.0 (no sampling), and num_values to 1 (matching upstream’s default_array_tuple_update_policy default). The seed is never exposed — every sketch built by this crate uses upstream’s DEFAULT_SEED.

Implementations

impl ArrayOfDoublesSketchBuilder

pub fn new() -> Self

Creates a new builder with default settings (lg_k = 12, resize_factor = X8, p = 1.0, num_values = 1).

Examples found in repository

examples/tuple.rs (line 16)

fn main() {
    // Two sketches of user IDs, each carrying [sessions, revenue] per user.
    let mut day1 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 0..10_000u64 {
        day1.update_u64(id, &[1.0, 2.50]).unwrap();
    }

    let mut day2 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 5_000..15_000u64 {
        day2.update_u64(id, &[1.0, 4.00]).unwrap();
    }

    println!("Day 1 unique users (estimate): {:.0}", day1.get_estimate());
    println!("Day 2 unique users (estimate): {:.0}", day2.get_estimate());
    println!("Values per entry: {}", day1.get_num_values());

    // Union: unique users across both days, with per-user values summed for
    // anyone who appeared on both.
    let mut union = ArrayOfDoublesUnionBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    union.update(&day1).unwrap();
    union.update(&day2).unwrap();
    let combined = union.get_result(true);
    println!(
        "Total unique users (union estimate): {:.0}",
        combined.get_estimate()
    );

    // Per-entry access is what distinguishes Tuple sketches from HLL/Theta/CPC:
    // scale the retained sample's revenue back up by 1/theta to estimate the
    // full population total.
    let retained_revenue: f64 = combined.entries().map(|(_, values)| values[1]).sum();
    println!(
        "Estimated total revenue: {:.2} (from {} retained entries, theta = {:.4})",
        retained_revenue / combined.get_theta(),
        combined.get_num_retained(),
        combined.get_theta()
    );

    // Intersection: users who came back on day 2.
    let mut intersection = ArrayOfDoublesIntersection::new(2).unwrap();
    intersection.update(&day1).unwrap();
    intersection.update(&day2).unwrap();
    match intersection.get_result(true) {
        Ok(returning) => println!(
            "Returning users (intersection estimate): {:.0}",
            returning.get_estimate()
        ),
        Err(e) => println!("No intersection result: {e}"),
    }

    // A-not-b: users who only came on day 1.
    let a_not_b = ArrayOfDoublesAnotB::new();
    let day1_only = a_not_b.compute(&day1, &day2, true).unwrap();
    println!(
        "Day-1-only users (a-not-b estimate): {:.0}",
        day1_only.get_estimate()
    );

    // Jaccard similarity of the two days' audiences.
    let similarity = array_of_doubles_jaccard_similarity(&day1, &day2).unwrap();
    println!(
        "Jaccard similarity: {:.3} (range [{:.3}, {:.3}])",
        similarity.estimate, similarity.lower_bound, similarity.upper_bound
    );

    // Serialize a compact sketch for storage/transmission, then restore it.
    let compact = day1.compact(true);
    let bytes = compact.serialize();
    println!("Serialized day-1 sketch: {} bytes", bytes.len());
    let restored = CompactArrayOfDoublesSketch::deserialize(&bytes).unwrap();
    println!(
        "Restored estimate: {:.0} ({} values per entry)",
        restored.get_estimate(),
        restored.get_num_values()
    );
}

pub fn lg_k(self, lg_k: u8) -> Self

Sets the base-2 log of the target number of retained entries.

Examples found in repository

examples/tuple.rs (line 17)

fn main() {
    // Two sketches of user IDs, each carrying [sessions, revenue] per user.
    let mut day1 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 0..10_000u64 {
        day1.update_u64(id, &[1.0, 2.50]).unwrap();
    }

    let mut day2 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 5_000..15_000u64 {
        day2.update_u64(id, &[1.0, 4.00]).unwrap();
    }

    println!("Day 1 unique users (estimate): {:.0}", day1.get_estimate());
    println!("Day 2 unique users (estimate): {:.0}", day2.get_estimate());
    println!("Values per entry: {}", day1.get_num_values());

    // Union: unique users across both days, with per-user values summed for
    // anyone who appeared on both.
    let mut union = ArrayOfDoublesUnionBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    union.update(&day1).unwrap();
    union.update(&day2).unwrap();
    let combined = union.get_result(true);
    println!(
        "Total unique users (union estimate): {:.0}",
        combined.get_estimate()
    );

    // Per-entry access is what distinguishes Tuple sketches from HLL/Theta/CPC:
    // scale the retained sample's revenue back up by 1/theta to estimate the
    // full population total.
    let retained_revenue: f64 = combined.entries().map(|(_, values)| values[1]).sum();
    println!(
        "Estimated total revenue: {:.2} (from {} retained entries, theta = {:.4})",
        retained_revenue / combined.get_theta(),
        combined.get_num_retained(),
        combined.get_theta()
    );

    // Intersection: users who came back on day 2.
    let mut intersection = ArrayOfDoublesIntersection::new(2).unwrap();
    intersection.update(&day1).unwrap();
    intersection.update(&day2).unwrap();
    match intersection.get_result(true) {
        Ok(returning) => println!(
            "Returning users (intersection estimate): {:.0}",
            returning.get_estimate()
        ),
        Err(e) => println!("No intersection result: {e}"),
    }

    // A-not-b: users who only came on day 1.
    let a_not_b = ArrayOfDoublesAnotB::new();
    let day1_only = a_not_b.compute(&day1, &day2, true).unwrap();
    println!(
        "Day-1-only users (a-not-b estimate): {:.0}",
        day1_only.get_estimate()
    );

    // Jaccard similarity of the two days' audiences.
    let similarity = array_of_doubles_jaccard_similarity(&day1, &day2).unwrap();
    println!(
        "Jaccard similarity: {:.3} (range [{:.3}, {:.3}])",
        similarity.estimate, similarity.lower_bound, similarity.upper_bound
    );

    // Serialize a compact sketch for storage/transmission, then restore it.
    let compact = day1.compact(true);
    let bytes = compact.serialize();
    println!("Serialized day-1 sketch: {} bytes", bytes.len());
    let restored = CompactArrayOfDoublesSketch::deserialize(&bytes).unwrap();
    println!(
        "Restored estimate: {:.0} ({} values per entry)",
        restored.get_estimate(),
        restored.get_num_values()
    );
}

pub fn resize_factor(self, resize_factor: ResizeFactor) -> Self

Sets the hash table’s growth ResizeFactor.

pub fn p(self, p: f32) -> Self

Sets the sampling probability. 1.0 (the default) disables sampling; values below 1.0 put the sketch into estimation mode from the start.

pub fn num_values(self, num_values: u8) -> Self

Sets the fixed number of f64 values each retained entry carries. Must be at least 1. Every sketch that will later be unioned, intersected, or differenced with this one must use the same value.

Examples found in repository

examples/tuple.rs (line 18)

fn main() {
    // Two sketches of user IDs, each carrying [sessions, revenue] per user.
    let mut day1 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 0..10_000u64 {
        day1.update_u64(id, &[1.0, 2.50]).unwrap();
    }

    let mut day2 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 5_000..15_000u64 {
        day2.update_u64(id, &[1.0, 4.00]).unwrap();
    }

    println!("Day 1 unique users (estimate): {:.0}", day1.get_estimate());
    println!("Day 2 unique users (estimate): {:.0}", day2.get_estimate());
    println!("Values per entry: {}", day1.get_num_values());

    // Union: unique users across both days, with per-user values summed for
    // anyone who appeared on both.
    let mut union = ArrayOfDoublesUnionBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    union.update(&day1).unwrap();
    union.update(&day2).unwrap();
    let combined = union.get_result(true);
    println!(
        "Total unique users (union estimate): {:.0}",
        combined.get_estimate()
    );

    // Per-entry access is what distinguishes Tuple sketches from HLL/Theta/CPC:
    // scale the retained sample's revenue back up by 1/theta to estimate the
    // full population total.
    let retained_revenue: f64 = combined.entries().map(|(_, values)| values[1]).sum();
    println!(
        "Estimated total revenue: {:.2} (from {} retained entries, theta = {:.4})",
        retained_revenue / combined.get_theta(),
        combined.get_num_retained(),
        combined.get_theta()
    );

    // Intersection: users who came back on day 2.
    let mut intersection = ArrayOfDoublesIntersection::new(2).unwrap();
    intersection.update(&day1).unwrap();
    intersection.update(&day2).unwrap();
    match intersection.get_result(true) {
        Ok(returning) => println!(
            "Returning users (intersection estimate): {:.0}",
            returning.get_estimate()
        ),
        Err(e) => println!("No intersection result: {e}"),
    }

    // A-not-b: users who only came on day 1.
    let a_not_b = ArrayOfDoublesAnotB::new();
    let day1_only = a_not_b.compute(&day1, &day2, true).unwrap();
    println!(
        "Day-1-only users (a-not-b estimate): {:.0}",
        day1_only.get_estimate()
    );

    // Jaccard similarity of the two days' audiences.
    let similarity = array_of_doubles_jaccard_similarity(&day1, &day2).unwrap();
    println!(
        "Jaccard similarity: {:.3} (range [{:.3}, {:.3}])",
        similarity.estimate, similarity.lower_bound, similarity.upper_bound
    );

    // Serialize a compact sketch for storage/transmission, then restore it.
    let compact = day1.compact(true);
    let bytes = compact.serialize();
    println!("Serialized day-1 sketch: {} bytes", bytes.len());
    let restored = CompactArrayOfDoublesSketch::deserialize(&bytes).unwrap();
    println!(
        "Restored estimate: {:.0} ({} values per entry)",
        restored.get_estimate(),
        restored.get_num_values()
    );
}

pub fn build(self) -> Result<ArrayOfDoublesSketch, SketchError>

Builds the sketch. Returns SketchError::InvalidConfig if lg_k is out of range, p is outside (0, 1], or num_values is 0.

Examples found in repository

examples/tuple.rs (line 19)

fn main() {
    // Two sketches of user IDs, each carrying [sessions, revenue] per user.
    let mut day1 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 0..10_000u64 {
        day1.update_u64(id, &[1.0, 2.50]).unwrap();
    }

    let mut day2 = ArrayOfDoublesSketchBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    for id in 5_000..15_000u64 {
        day2.update_u64(id, &[1.0, 4.00]).unwrap();
    }

    println!("Day 1 unique users (estimate): {:.0}", day1.get_estimate());
    println!("Day 2 unique users (estimate): {:.0}", day2.get_estimate());
    println!("Values per entry: {}", day1.get_num_values());

    // Union: unique users across both days, with per-user values summed for
    // anyone who appeared on both.
    let mut union = ArrayOfDoublesUnionBuilder::new()
        .lg_k(12)
        .num_values(2)
        .build()
        .unwrap();
    union.update(&day1).unwrap();
    union.update(&day2).unwrap();
    let combined = union.get_result(true);
    println!(
        "Total unique users (union estimate): {:.0}",
        combined.get_estimate()
    );

    // Per-entry access is what distinguishes Tuple sketches from HLL/Theta/CPC:
    // scale the retained sample's revenue back up by 1/theta to estimate the
    // full population total.
    let retained_revenue: f64 = combined.entries().map(|(_, values)| values[1]).sum();
    println!(
        "Estimated total revenue: {:.2} (from {} retained entries, theta = {:.4})",
        retained_revenue / combined.get_theta(),
        combined.get_num_retained(),
        combined.get_theta()
    );

    // Intersection: users who came back on day 2.
    let mut intersection = ArrayOfDoublesIntersection::new(2).unwrap();
    intersection.update(&day1).unwrap();
    intersection.update(&day2).unwrap();
    match intersection.get_result(true) {
        Ok(returning) => println!(
            "Returning users (intersection estimate): {:.0}",
            returning.get_estimate()
        ),
        Err(e) => println!("No intersection result: {e}"),
    }

    // A-not-b: users who only came on day 1.
    let a_not_b = ArrayOfDoublesAnotB::new();
    let day1_only = a_not_b.compute(&day1, &day2, true).unwrap();
    println!(
        "Day-1-only users (a-not-b estimate): {:.0}",
        day1_only.get_estimate()
    );

    // Jaccard similarity of the two days' audiences.
    let similarity = array_of_doubles_jaccard_similarity(&day1, &day2).unwrap();
    println!(
        "Jaccard similarity: {:.3} (range [{:.3}, {:.3}])",
        similarity.estimate, similarity.lower_bound, similarity.upper_bound
    );

    // Serialize a compact sketch for storage/transmission, then restore it.
    let compact = day1.compact(true);
    let bytes = compact.serialize();
    println!("Serialized day-1 sketch: {} bytes", bytes.len());
    let restored = CompactArrayOfDoublesSketch::deserialize(&bytes).unwrap();
    println!(
        "Restored estimate: {:.0} ({} values per entry)",
        restored.get_estimate(),
        restored.get_num_values()
    );
}

Trait Implementations

impl Clone for ArrayOfDoublesSketchBuilder

fn clone(&self) -> ArrayOfDoublesSketchBuilder

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for ArrayOfDoublesSketchBuilder

impl Debug for ArrayOfDoublesSketchBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ArrayOfDoublesSketchBuilder

fn default() -> Self

Returns the “default value” for a type.