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use crate::{
client::{prepare_command, PreparedCommand},
resp::{cmd, CollectionResponse, CommandArgs, SingleArg, SingleArgCollection, ToArgs, Value},
};
use serde::Deserialize;
use std::collections::HashMap;
/// A group of Redis commands related to [`T-Digest`](https://redis.io/docs/stack/bloom/)
///
/// # See Also
/// [T-Digest Commands](https://redis.io/commands/?group=tdigest)
pub trait TDigestCommands<'a> {
/// Adds one or more observations to a t-digest sketch.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `values` - collection values of an observation (floating-point).
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.add/>](https://redis.io/commands/tdigest.add/)
#[must_use]
fn tdigest_add(
self,
key: impl SingleArg,
values: impl SingleArgCollection<f64>,
) -> PreparedCommand<'a, Self, ()>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.ADD").arg(key).arg(values))
}
/// Returns, for each input rank, an estimation of the value (floating-point) with that rank.
///
/// Multiple estimations can be retrieved in a single call.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `ranks` - collection of ranks, for which the value should be retrieved.
/// * `0` - is the rank of the value of the smallest observation.
/// * `n-1` - is the rank of the value of the largest observation; `n` denotes the number of observations added to the sketch.
///
/// # Return
/// a collection of floating-points populated with value_1, value_2, ..., value_R:
/// * Return an accurate result when rank is `0` (the value of the smallest observation)
/// * Return an accurate result when rank is `n-1` (the value of the largest observation), \
/// where n denotes the number of observations added to the sketch.
/// * Return `inf` when rank is equal to n or larger than `n`
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.byrank/>](https://redis.io/commands/tdigest.byrank/)
#[must_use]
fn tdigest_byrank<R: CollectionResponse<f64>>(
self,
key: impl SingleArg,
ranks: impl SingleArgCollection<usize>,
) -> PreparedCommand<'a, Self, R>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.BYRANK").arg(key).arg(ranks))
}
/// Returns, for each input reverse rank, an estimation of the value (floating-point) with that reverse rank.
///
/// Multiple estimations can be retrieved in a single call.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `ranks` - collection of reverse ranks, for which the value should be retrieved.
/// * `0` - is the reverse rank of the value of the largest observation.
/// * `n-1` - s the reverse rank of the value of the smallest observation; n denotes the number of observations added to the sketch.
///
/// # Return
/// a collection of floating-points populated with value_1, value_2, ..., value_R:
/// * Return an accurate result when `revrank` is `0` (the value of the largest observation)
/// * Return an accurate result when `revrank` is `n-1` (the value of the smallest observation), \
/// where `n` denotes the number of observations added to the sketch.
/// * Return 'inf' when `revrank` is equal to `n` or larger than `n`
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.byrevrank/>](https://redis.io/commands/tdigest.byrevrank/)
#[must_use]
fn tdigest_byrevrank<R: CollectionResponse<f64>>(
self,
key: impl SingleArg,
ranks: impl SingleArgCollection<usize>,
) -> PreparedCommand<'a, Self, R>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.BYREVRANK").arg(key).arg(ranks))
}
/// Returns, for each input reverse rank, an estimation of the value (floating-point) with that reverse rank.
///
/// Multiple estimations can be retrieved in a single call.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `values` - collection values for which the CDF \
/// ([`Cumulative Distribution Function`](https://en.wikipedia.org/wiki/Cumulative_distribution_function)) should be retrieved.
///
/// # Return
/// a collection of floating-points populated with fraction_1, fraction_2, ..., fraction_N.
///
/// All values are `nan` if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.cdf/>](https://redis.io/commands/tdigest.cdf/)
#[must_use]
fn tdigest_cdf<V: SingleArg, R: CollectionResponse<f64>>(
self,
key: impl SingleArg,
values: impl SingleArgCollection<V>,
) -> PreparedCommand<'a, Self, R>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.CDF").arg(key).arg(values))
}
/// Allocates memory and initializes a new t-digest sketch.
///
/// # Arguments
/// * `key` - key name for this new t-digest sketch.
/// * `compression` - controllable tradeoff between accuracy and memory consumption. \
/// 100 is a common value for normal uses. 1000 is more accurate. \
/// If no value is passed by default the compression will be 100. \
/// For more information on scaling of accuracy versus the compression parameter,\
/// see [`The t-digest: Efficient estimates of distributions`](https://www.sciencedirect.com/science/article/pii/S2665963820300403).
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.create/>](https://redis.io/commands/tdigest.create/)
#[must_use]
fn tdigest_create(
self,
key: impl SingleArg,
compression: Option<i64>,
) -> PreparedCommand<'a, Self, ()>
where
Self: Sized,
{
prepare_command(
self,
cmd("TDIGEST.CREATE")
.arg(key)
.arg(compression.map(|c| ("COMPRESSION", c))),
)
}
/// Returns information and statistics about a t-digest sketch
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
///
/// # Return
/// An instance of [`TDigestInfoResult`](TDigestInfoResult)
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.info/>](https://redis.io/commands/tdigest.info/)
#[must_use]
fn tdigest_info(self, key: impl SingleArg) -> PreparedCommand<'a, Self, TDigestInfoResult>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.INFO").arg(key))
}
/// Returns the maximum observation value from a t-digest sketch.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
///
/// # Return
/// maximum observation value from a sketch. The result is always accurate.
/// `nan` if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.max/>](https://redis.io/commands/tdigest.max/)
#[must_use]
fn tdigest_max(self, key: impl SingleArg) -> PreparedCommand<'a, Self, f64>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.MAX").arg(key))
}
/// Merges multiple t-digest sketches into a single sketch.
///
/// # Arguments
/// * `destination` - key name for a t-digest sketch to merge observation values to.
/// * If `destination` not exist, a new sketch is created.
/// * If `destination` is an existing sketch, its values are merged with the values of the source keys.\
/// To override the destination key contents use [`override`](TDigestMergeOptions::_override).
/// * `sources` - collection of key names for t-digest sketches to merge observation values from.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.merge/>](https://redis.io/commands/tdigest.merge/)
#[must_use]
fn tdigest_merge<S: SingleArg>(
self,
destination: impl SingleArg,
sources: impl SingleArgCollection<S>,
options: TDigestMergeOptions,
) -> PreparedCommand<'a, Self, ()>
where
Self: Sized,
{
prepare_command(
self,
cmd("TDIGEST.MERGE")
.arg(destination)
.arg(sources.num_args())
.arg(sources)
.arg(options),
)
}
/// Returns the minimum observation value from a t-digest sketch.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
///
/// # Return
/// minimum observation value from a sketch. The result is always accurate.
/// `nan` if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.min/>](https://redis.io/commands/tdigest.min/)
#[must_use]
fn tdigest_min(self, key: impl SingleArg) -> PreparedCommand<'a, Self, f64>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.MIN").arg(key))
}
/// Returns, for each input fraction, an estimation of the value
/// (floating point) that is smaller than the given fraction of observations.
///
/// Multiple quantiles can be retrieved in a signle call.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `quantiles` - collection of quantiles which are input fractions (between 0 and 1 inclusively)
///
/// # Return
/// a collection of estimates (floating-point) populated with value_1, value_2, ..., value_N.
/// * Return an accurate result when quantile is 0 (the value of the smallest observation)
/// * Return an accurate result when quantile is 1 (the value of the largest observation)
///
/// All values are `nan` if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.quantile/>](https://redis.io/commands/tdigest.quantile/)
#[must_use]
fn tdigest_quantile<Q: SingleArg, R: CollectionResponse<f64>>(
self,
key: impl SingleArg,
quantiles: impl SingleArgCollection<Q>,
) -> PreparedCommand<'a, Self, R>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.QUANTILE").arg(key).arg(quantiles))
}
/// Returns, for each input value (floating-point), the estimated rank of the value
/// (the number of observations in the sketch that are smaller than the value + half the number of observations that are equal to the value).
///
/// Multiple ranks can be retrieved in a signle call.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `values` - collection of values for which the rank should be estimated.
///
/// # Return
/// a collection of integers populated with rank_1, rank_2, ..., rank_V:
/// * `-1` - when `value` is smaller than the value of the smallest observation.
/// * The number of observations - when `value` is larger than the value of the largest observation.
/// * Otherwise: an estimation of the number of (observations smaller than `value` + half the observations equal to `value`).
///
/// `0` is the rank of the value of the smallest observation.
///
/// `n-1` is the rank of the value of the largest observation; `n` denotes the number of observations added to the sketch.
///
/// All values are `-2` if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.rank/>](https://redis.io/commands/tdigest.rank/)
#[must_use]
fn tdigest_rank<V: SingleArg, R: CollectionResponse<isize>>(
self,
key: impl SingleArg,
values: impl SingleArgCollection<V>,
) -> PreparedCommand<'a, Self, R>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.RANK").arg(key).arg(values))
}
/// Resets a t-digest sketch: empty the sketch and re-initializes it.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.reset/>](https://redis.io/commands/tdigest.reset/)
#[must_use]
fn tdigest_reset(self, key: impl SingleArg) -> PreparedCommand<'a, Self, ()>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.RESET").arg(key))
}
/// Returns, for each input value (floating-point), the estimated reverse rank of the value
/// (the number of observations in the sketch that are smaller than the value + half the number of observations that are equal to the value).
///
/// Multiple reverse ranks can be retrieved in a signle call.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `values` - collection of values for which the reverse rank should be estimated.
///
/// # Return
/// a collection of integers populated with revrank_1, revrank_2, ..., revrank_V:
/// * `-1` - when `value` is smaller than the value of the smallest observation.
/// * The number of observations - when `value` is larger than the value of the largest observation.
/// * Otherwise: an estimation of the number of (observations smaller than `value` + half the observations equal to `value`).
///
/// `0` is the reverse rank of the value of the smallest observation.
///
/// `n-1` is the reverse rank of the value of the largest observation; `n` denotes the number of observations added to the sketch.
///
/// All values are `-2` if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.revrank/>](https://redis.io/commands/tdigest.revrank/)
#[must_use]
fn tdigest_revrank<V: SingleArg, R: CollectionResponse<isize>>(
self,
key: impl SingleArg,
values: impl SingleArgCollection<V>,
) -> PreparedCommand<'a, Self, R>
where
Self: Sized,
{
prepare_command(self, cmd("TDIGEST.REVRANK").arg(key).arg(values))
}
/// Returns an estimation of the mean value from the sketch, excluding observation values outside the low and high cutoff quantiles.
///
/// # Arguments
/// * `key` - key name for an existing t-digest sketch.
/// * `low_cut_quantile` - Foating-point value in the range [0..1], should be lower than `high_cut_quantile` \
/// When equal to 0: No low cut. \
/// When higher than 0: Exclude observation values lower than this quantile.
/// * `high_cut_quantile` - Floating-point value in the range [0..1], should be higher than `low_cut_quantile` \
/// When lower than 1: Exclude observation values higher than or equal to this quantile. \
/// When equal to 1: No high cut.
///
/// # Return
/// estimation of the mean value. 'nan' if the sketch is empty.
///
/// # See Also
/// * [<https://redis.io/commands/tdigest.trimmed_mean/>](https://redis.io/commands/tdigest.trimmed_mean/)
#[must_use]
fn tdigest_trimmed_mean(
self,
key: impl SingleArg,
low_cut_quantile: f64,
high_cut_quantile: f64,
) -> PreparedCommand<'a, Self, f64>
where
Self: Sized,
{
prepare_command(
self,
cmd("TDIGEST.TRIMMED_MEAN")
.arg(key)
.arg(low_cut_quantile)
.arg(high_cut_quantile),
)
}
}
/// Result for the [`tdigest_info`](TDigestCommands::tdigest_info) command.
#[derive(Debug, Deserialize)]
pub struct TDigestInfoResult {
/// The compression (controllable trade-off between accuracy and memory consumption) of the sketch
#[serde(rename = "Compression")]
pub compression: usize,
/// Size of the buffer used for storing the centroids and for the incoming unmerged observations
#[serde(rename = "Capacity")]
pub capacity: usize,
/// Number of merged observations
#[serde(rename = "Merged nodes")]
pub merged_nodes: usize,
/// Number of buffered nodes (uncompressed observations)
#[serde(rename = "Unmerged nodes")]
pub unmerged_nodes: usize,
/// Weight of values of the merged nodes
#[serde(rename = "Merged weight")]
pub merged_weight: usize,
/// Weight of values of the unmerged nodes (uncompressed observations)
#[serde(rename = "Unmerged weight")]
pub unmerged_weight: usize,
/// Number of observations added to the sketch
#[serde(rename = "Observations")]
pub observations: usize,
/// Number of times this sketch compressed data together
#[serde(rename = "Total compressions")]
pub total_compressions: usize,
/// Number of bytes allocated for the sketch
#[serde(rename = "Memory usage")]
pub memory_usage: usize,
/// Additional information
#[serde(flatten)]
pub additional_info: HashMap<String, Value>,
}
/// Options for the [`tdigest_merge`](TDigestCommands::tdigest_merge) command.
#[derive(Default)]
pub struct TDigestMergeOptions {
command_args: CommandArgs,
}
impl TDigestMergeOptions {
/// controllable tradeoff between accuracy and memory consumption.
///
/// 100 is a common value for normal uses.
/// 1000 is more accurate.
/// If no value is passed by default the compression will be 100.
/// For more information on scaling of accuracy versus the compression parameter
/// see [`The t-digest: Efficient estimates of distributions`](https://www.sciencedirect.com/science/article/pii/S2665963820300403).
///
/// When COMPRESSION is not specified:
/// * If `destination` does not exist or if [`override`](TDigestMergeOptions::_override) is specified, \
/// the compression is set to the maximal value among all source sketches.
/// * If `destination` already exists and [`override`](TDigestMergeOptions::_override) is not specified, \
/// its compression is not changed.
#[must_use]
pub fn compression(mut self, compression: usize) -> Self {
Self {
command_args: self.command_args.arg("COMPRESSION").arg(compression).build(),
}
}
/// When specified, if `destination` already exists, it is overwritten.
#[must_use]
pub fn _override(mut self) -> Self {
Self {
command_args: self.command_args.arg("OVERRIDE").build(),
}
}
}
impl ToArgs for TDigestMergeOptions {
fn write_args(&self, args: &mut CommandArgs) {
args.arg(&self.command_args);
}
}