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perf: reuse current rolling series boundary

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boris
2026-09-04 23:06:52 +08:00
parent 914820cc07
commit 52b07be19b
2 changed files with 238 additions and 18 deletions
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crates/fidc-core/src/data.rs
+180 -5
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@@ -2012,6 +2012,14 @@ impl DataSet {
Some(*end as usize)
}
pub(crate) fn market_current_series_end_index_by_symbol_id(
&self,
date: NaiveDate,
symbol_id: u32,
) -> Option<usize> {
self.market_series_end_index_by_symbol_id(date, symbol_id, true)
}
pub fn factor(&self, date: NaiveDate, symbol: &str) -> Option<&DailyFactorSnapshot> {
let symbol_id = self.symbol_id(symbol)?;
self.factor_by_symbol_id(date, symbol_id)
@@ -3347,20 +3355,56 @@ impl DataSet {
symbol: &str,
field: &str,
lookback: usize,
) -> Option<f64> {
let normalized = normalized_field(field);
let series_end = matches!(
normalized.as_ref(),
"close"
| "prev_close"
| "stock_close"
| "price"
| "volume"
| "stock_volume"
| "day_open"
| "dayopen"
| "open"
| "last"
| "last_price"
)
.then(|| self.market_current_series_end_index_by_symbol_id(date, symbol_id))
.flatten();
self.market_current_numeric_moving_average_with_end_by_symbol_id(
date,
symbol_id,
symbol,
normalized.as_ref(),
lookback,
series_end,
)
}
pub(crate) fn market_current_numeric_moving_average_with_end_by_symbol_id(
&self,
date: NaiveDate,
symbol_id: u32,
symbol: &str,
field: &str,
lookback: usize,
series_end: Option<usize>,
) -> Option<f64> {
let field = normalized_field(field);
match field.as_ref() {
"close" | "prev_close" | "stock_close" | "price" => self
.adjusted_close_series_by_symbol_id(symbol_id)
.and_then(|series| {
self.market_series_end_index_by_symbol_id(date, symbol_id, true)
series_end
.map(|end| series.moving_average_at_end(end, lookback))
.unwrap_or_else(|| series.current_moving_average(date, lookback))
}),
"volume" | "stock_volume" => {
self.market_series_by_symbol_id(symbol_id)
.and_then(|series| {
self.market_series_end_index_by_symbol_id(date, symbol_id, true)
series_end
.map(|end| {
series
.valid_volume_window(end, lookback)
@@ -3379,7 +3423,7 @@ impl DataSet {
"day_open" | "dayopen" => {
self.market_series_by_symbol_id(symbol_id)
.and_then(|series| {
self.market_series_end_index_by_symbol_id(date, symbol_id, true)
series_end
.map(|end| {
series.moving_average_at_end(end, lookback, PriceField::DayOpen)
})
@@ -3391,14 +3435,14 @@ impl DataSet {
"open" => self
.market_series_by_symbol_id(symbol_id)
.and_then(|series| {
self.market_series_end_index_by_symbol_id(date, symbol_id, true)
series_end
.map(|end| series.moving_average_at_end(end, lookback, PriceField::Open))
.unwrap_or_else(|| series.moving_average(date, lookback, PriceField::Open))
}),
"last" | "last_price" => {
self.market_series_by_symbol_id(symbol_id)
.and_then(|series| {
self.market_series_end_index_by_symbol_id(date, symbol_id, true)
series_end
.map(|end| {
series.moving_average_at_end(end, lookback, PriceField::Last)
})
@@ -5052,6 +5096,137 @@ mod tests {
);
}
#[test]
#[ignore = "manual release-mode current rolling boundary benchmark"]
fn benchmark_current_rolling_reuses_symbol_boundary() {
let start = NaiveDate::from_ymd_opt(2025, 1, 1).unwrap();
let dates = (0..160)
.map(|offset| start + chrono::Duration::days(offset))
.collect::<Vec<_>>();
let data = DataSet::from_components(
vec![Instrument {
symbol: "000001.SZ".to_string(),
name: "000001.SZ".to_string(),
board: "SZ".to_string(),
round_lot: 100,
listed_at: None,
delisted_at: None,
status: "active".to_string(),
}],
dates
.iter()
.enumerate()
.map(|(index, date)| {
market_row(
&date.format("%Y-%m-%d").to_string(),
10.0 + index as f64 / 100.0,
100_000 + index as u64,
)
})
.collect(),
dates
.iter()
.map(|date| DailyFactorSnapshot {
date: *date,
symbol: "000001.SZ".to_string(),
market_cap_bn: 10.0,
free_float_cap_bn: 8.0,
pe_ttm: 10.0,
turnover_ratio: None,
effective_turnover_ratio: None,
extra_factors: NumericFactorMap::from([(
Cow::Borrowed(BACKWARD_ADJUSTMENT_FACTOR_FIELD),
1.0,
)]),
})
.collect(),
Vec::new(),
dates
.iter()
.enumerate()
.map(|(index, date)| {
benchmark_row(&date.format("%Y-%m-%d").to_string(), 1_000.0 + index as f64)
})
.collect(),
)
.unwrap();
let date = *dates.last().unwrap();
let symbol = "000001.SZ";
let symbol_id = data.symbol_id(symbol).unwrap();
let requirements = [
("close", 5usize),
("close", 10usize),
("close", 30usize),
("volume", 5usize),
("volume", 100usize),
];
let iterations = 100_000usize;
let mut repeated_nanos = 0u128;
let mut reused_nanos = 0u128;
let mut repeated_checksum = 0.0;
let mut reused_checksum = 0.0;
for iteration in 0..iterations {
if iteration % 2 == 0 {
let started = std::time::Instant::now();
for (field, lookback) in requirements {
repeated_checksum += data
.market_current_numeric_moving_average_by_symbol_id(
date, symbol_id, symbol, field, lookback,
)
.unwrap();
}
repeated_nanos += started.elapsed().as_nanos();
let started = std::time::Instant::now();
let series_end = data.market_current_series_end_index_by_symbol_id(date, symbol_id);
for (field, lookback) in requirements {
reused_checksum += data
.market_current_numeric_moving_average_with_end_by_symbol_id(
date, symbol_id, symbol, field, lookback, series_end,
)
.unwrap();
}
reused_nanos += started.elapsed().as_nanos();
} else {
let started = std::time::Instant::now();
let series_end = data.market_current_series_end_index_by_symbol_id(date, symbol_id);
for (field, lookback) in requirements {
reused_checksum += data
.market_current_numeric_moving_average_with_end_by_symbol_id(
date, symbol_id, symbol, field, lookback, series_end,
)
.unwrap();
}
reused_nanos += started.elapsed().as_nanos();
let started = std::time::Instant::now();
for (field, lookback) in requirements {
repeated_checksum += data
.market_current_numeric_moving_average_by_symbol_id(
date, symbol_id, symbol, field, lookback,
)
.unwrap();
}
repeated_nanos += started.elapsed().as_nanos();
}
}
assert!((repeated_checksum - reused_checksum).abs() < 1e-6);
let repeated_seconds = repeated_nanos as f64 / 1_000_000_000.0;
let reused_seconds = reused_nanos as f64 / 1_000_000_000.0;
eprintln!(
"{}",
serde_json::json!({
"schemaVersion": "fidc-current-rolling-boundary-benchmark/v1",
"iterations": iterations,
"helperCallsPerIteration": requirements.len(),
"repeatedLookupSeconds": repeated_seconds,
"reusedBoundarySeconds": reused_seconds,
"speedup": repeated_seconds / reused_seconds,
"equal": true,
})
);
}
#[test]
#[ignore = "manual component benchmark"]
fn benchmark_daily_snapshot_view_lookup() {