zrx_stream/stream/operator/lift.rs
1// Copyright (c) 2025-2026 Zensical and contributors
2
3// SPDX-License-Identifier: MIT
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23
24// ----------------------------------------------------------------------------
25
26//! Lift operator.
27
28use ahash::HashMap;
29
30use zrx_scheduler::action::descriptor::Property;
31use zrx_scheduler::action::output::IntoOutputs;
32use zrx_scheduler::action::{Descriptor, Report};
33use zrx_scheduler::effect::Item;
34use zrx_scheduler::{Id, Value};
35use zrx_store::behavior::StoreDelta;
36use zrx_store::StoreMutRef;
37
38use crate::stream::function::LiftFn;
39use crate::stream::value::Delta;
40use crate::stream::Stream;
41
42use super::{Operator, OperatorExt};
43
44// ----------------------------------------------------------------------------
45// Structs
46// ----------------------------------------------------------------------------
47
48/// Lift operator.
49struct Lift<F, I, U> {
50 /// Operator function.
51 function: F,
52 /// Store of change sets.
53 store: HashMap<I, HashMap<I, U>>,
54}
55
56// ----------------------------------------------------------------------------
57// Implementations
58// ----------------------------------------------------------------------------
59
60impl<I, T> Stream<I, T>
61where
62 I: Id,
63 T: Value,
64{
65 pub fn lift<F, U>(&self, f: F) -> Stream<I, Delta<I, U>>
66 where
67 F: LiftFn<I, T, U>,
68 U: Value + Clone + Eq,
69 {
70 self.with_operator(Lift {
71 function: f,
72 store: HashMap::default(),
73 })
74 }
75}
76
77// ----------------------------------------------------------------------------
78// Trait implementations
79// ----------------------------------------------------------------------------
80
81impl<I, T, F, U> Operator<I, T> for Lift<F, I, U>
82where
83 I: Id,
84 T: Value,
85 F: LiftFn<I, T, U>,
86 U: Value + Clone + Eq,
87{
88 type Item<'a> = Item<&'a I, Option<&'a T>>;
89
90 /// Handles the given item.
91 ///
92 /// Lifting is an essential operation in stream processing, as it allows an
93 /// input item to be transformed into multiple related output items with a
94 /// user-defined function. This operator always returns a delta of items,
95 /// ensuring that the related items can be processed differentially.
96 #[cfg_attr(
97 feature = "tracing",
98 tracing::instrument(level = "debug", skip_all, fields(id = %item.id))
99 )]
100 fn handle(&mut self, item: Self::Item<'_>) -> impl IntoOutputs<I> {
101 if let Some(data) = item.data {
102 // When new data arrives, we apply the operator function to generate
103 // related items. We then compute the delta between the previous set
104 // of related items and the returned set, ensuring that only changes
105 // are propagated downstream.
106 self.function.execute(item.id, data).map(|report| {
107 report.map(|data| {
108 let store = self.store.get_or_insert_default(item.id);
109 let delta = store
110 .changes(data.into_iter().map(Item::into_parts))
111 .map(|(id, data)| Item::new(id, data))
112 .collect();
113
114 // Return delta of items
115 Item::new(item.id.clone(), Some(delta))
116 })
117 })
118 } else {
119 // If the incoming item has no data, interpret this as a deletion,
120 // removing any previously stored related items. By emitting a delta
121 // of items instead of a deletion, we can ensure that all downstream
122 // operators can update their internal state accordingly.
123 let store = self.store.remove(item.id);
124 let delta = store.map_or_else(Delta::default, |inner| {
125 inner.into_keys().map(|id| Item::new(id, None)).collect()
126 });
127
128 // Return delta of items
129 Ok(Report::new(Item::new(item.id.clone(), Some(delta))))
130 }
131 }
132
133 /// Returns the descriptor.
134 #[inline]
135 fn descriptor(&self) -> Descriptor {
136 Descriptor::builder() // fmt
137 .property(Property::Stable)
138 .build()
139 }
140}