revert: reject neutral symbol-id series storage

crates/fidc-core/src/data.rs

@@ -1318,6 +1318,8 @@ pub struct DataSet {
     execution_quote_dates: Arc<Vec<NaiveDate>>,
     order_book_depth_index: Arc<HashMap<(NaiveDate, String), Vec<IntradayOrderBookDepthLevel>>>,
     benchmark_by_date: Arc<BTreeMap<NaiveDate, BenchmarkSnapshot>>,
+    market_series_by_symbol: Arc<AHashMap<String, Arc<SymbolPriceSeries>>>,
+    adjusted_close_series_by_symbol: Arc<AHashMap<String, Arc<AdjustedCloseSeries>>>,
     market_series_by_symbol_id: Arc<Vec<Option<Arc<SymbolPriceSeries>>>>,
     adjusted_close_series_by_symbol_id: Arc<Vec<Option<Arc<AdjustedCloseSeries>>>>,
     market_series_end_positions_by_calendar_index: Arc<Option<CalendarSeriesEndPositions>>,
@@ -1707,68 +1709,44 @@ impl DataSet {
             .into_iter()
             .map(|instrument| (instrument.symbol.clone(), instrument))
             .collect::<HashMap<_, _>>();
-        let symbol_id_by_code = build_symbol_id_index(
+        let mut market_rows_by_symbol = AHashMap::<String, Vec<&DailyMarketSnapshot>>::new();
-            &instruments,
-            &market_by_date,
-            &factor_by_date,
-            &candidate_by_date,
-        );
-        let symbol_count = symbol_id_by_code.len();
-        let mut symbol_by_id = vec![Arc::<str>::from(""); symbol_count];
-        for (symbol, symbol_id) in &symbol_id_by_code {
-            symbol_by_id[*symbol_id as usize] = Arc::<str>::from(symbol.as_str());
-        }
-        let mut instruments_by_symbol_id = vec![None; symbol_count];
-        for (symbol, instrument) in &instruments {
-            if let Some(symbol_id) = symbol_id_by_code.get(symbol).copied() {
-                instruments_by_symbol_id[symbol_id as usize] = Some(instrument.clone());
-            }
-        }
-
-        let mut market_rows_by_symbol_id = (0..symbol_count)
-            .map(|_| Vec::<&DailyMarketSnapshot>::new())
-            .collect::<Vec<_>>();
         for row in market_by_date.values().flatten() {
-            let symbol_id = *symbol_id_by_code
+            if let Some(rows) = market_rows_by_symbol.get_mut(row.symbol.as_str()) {
-                .get(row.symbol.as_str())
+                rows.push(row);
-                .expect("market symbol missing from FIDC symbol index");
+                continue;
-            market_rows_by_symbol_id[symbol_id as usize].push(row);
+            }
+            market_rows_by_symbol.insert(row.symbol.clone(), vec![row]);
         }
-        let market_series_by_symbol_id = market_rows_by_symbol_id
+        let market_rows_by_symbol = market_rows_by_symbol.into_iter().collect::<Vec<_>>();
+        let market_series_by_symbol = market_rows_by_symbol
             .into_par_iter()
-            .enumerate()
+            .map(|(symbol, rows)| {
-            .map(|(symbol_id, rows)| {
+                let series = Arc::new(SymbolPriceSeries::from_sorted_rows(symbol.clone(), rows));
-                if rows.is_empty() {
+                (symbol, series)
-                    return None;
-                }
-                Some(Arc::new(SymbolPriceSeries::from_sorted_rows(
-                    symbol_by_id[symbol_id].to_string(),
-                    rows,
-                )))
             })
-            .collect::<Vec<_>>();
+            .collect::<Vec<_>>()
-        let mut factor_rows_by_symbol_id = (0..symbol_count)
+            .into_iter()
-            .map(|_| Vec::<&DailyFactorSnapshot>::new())
+            .collect::<AHashMap<_, _>>();
-            .collect::<Vec<_>>();
+        let mut factor_rows_by_symbol = AHashMap::<&str, Vec<&DailyFactorSnapshot>>::new();
         for row in factor_by_date.values().flatten() {
-            let symbol_id = *symbol_id_by_code
+            factor_rows_by_symbol
-                .get(row.symbol.as_str())
+                .entry(row.symbol.as_str())
-                .expect("factor symbol missing from FIDC symbol index");
+                .or_default()
-            factor_rows_by_symbol_id[symbol_id as usize].push(row);
+                .push(row);
         }
-        let adjusted_close_series_by_symbol_id = market_series_by_symbol_id
+        let adjusted_close_series_by_symbol = market_series_by_symbol
             .par_iter()
-            .enumerate()
+            .filter_map(|(symbol, market)| {
-            .map(|(symbol_id, market)| {
+                let factor_rows = factor_rows_by_symbol
-                market.as_ref().and_then(|market| {
+                    .get(symbol.as_str())
-                    AdjustedCloseSeries::new(
+                    .map(Vec::as_slice)
-                        market,
+                    .unwrap_or_default();
-                        factor_rows_by_symbol_id[symbol_id].as_slice(),
+                AdjustedCloseSeries::new(market, factor_rows)
-                    )
+                    .map(|series| (symbol.clone(), Arc::new(series)))
-                    .map(Arc::new)
-                })
             })
-            .collect::<Vec<_>>();
+            .collect::<Vec<_>>()
+            .into_iter()
+            .collect::<AHashMap<_, _>>();
         let factor_texts = factor_texts
             .into_iter()
             .filter_map(|mut item| {
@@ -1786,6 +1764,22 @@ impl DataSet {
             .map(|item| ((item.date, item.symbol.clone(), item.field.clone()), item))
             .collect::<HashMap<_, _>>();
 
+        let symbol_id_by_code = build_symbol_id_index(
+            &instruments,
+            &market_by_date,
+            &factor_by_date,
+            &candidate_by_date,
+        );
+        let mut symbol_by_id = vec![Arc::<str>::from(""); symbol_id_by_code.len()];
+        for (symbol, symbol_id) in &symbol_id_by_code {
+            symbol_by_id[*symbol_id as usize] = Arc::<str>::from(symbol.as_str());
+        }
+        let mut instruments_by_symbol_id = vec![None; symbol_id_by_code.len()];
+        for (symbol, instrument) in &instruments {
+            if let Some(symbol_id) = symbol_id_by_code.get(symbol).copied() {
+                instruments_by_symbol_id[symbol_id as usize] = Some(instrument.clone());
+            }
+        }
         let market_symbol_ids_by_date =
             build_group_symbol_ids(&market_by_date, &symbol_id_by_code, |item| {
                 item.symbol.as_str()
@@ -1815,6 +1809,18 @@ impl DataSet {
             &candidate_symbol_ids_by_date,
             symbol_id_by_code.len(),
         );
+        let mut market_series_by_symbol_id = vec![None; symbol_id_by_code.len()];
+        for (symbol, series) in &market_series_by_symbol {
+            if let Some(symbol_id) = symbol_id_by_code.get(symbol).copied() {
+                market_series_by_symbol_id[symbol_id as usize] = Some(Arc::clone(series));
+            }
+        }
+        let mut adjusted_close_series_by_symbol_id = vec![None; symbol_id_by_code.len()];
+        for (symbol, series) in &adjusted_close_series_by_symbol {
+            if let Some(symbol_id) = symbol_id_by_code.get(symbol).copied() {
+                adjusted_close_series_by_symbol_id[symbol_id as usize] = Some(Arc::clone(series));
+            }
+        }
         let market_series_end_positions_by_calendar_index =
             build_calendar_series_end_positions(&market_series_by_symbol_id, &calendar);
         let execution_quotes_by_date = build_execution_quote_index(execution_quotes);
@@ -1847,6 +1853,8 @@ impl DataSet {
             execution_quote_dates: Arc::new(execution_quote_dates),
             order_book_depth_index: Arc::new(order_book_depth_index),
             benchmark_by_date: Arc::new(benchmark_by_date),
+            market_series_by_symbol: Arc::new(market_series_by_symbol),
+            adjusted_close_series_by_symbol: Arc::new(adjusted_close_series_by_symbol),
             market_series_by_symbol_id: Arc::new(market_series_by_symbol_id),
             adjusted_close_series_by_symbol_id: Arc::new(adjusted_close_series_by_symbol_id),
             market_series_end_positions_by_calendar_index: Arc::new(
@@ -1985,7 +1993,7 @@ impl DataSet {
     }
 
     fn market_series(&self, symbol: &str) -> Option<&SymbolPriceSeries> {
-        self.market_series_by_symbol_id(self.symbol_id(symbol)?)
+        self.market_series_by_symbol.get(symbol).map(Arc::as_ref)
     }
 
     fn market_series_by_symbol_id(&self, symbol_id: u32) -> Option<&SymbolPriceSeries> {
@@ -1995,7 +2003,9 @@ impl DataSet {
     }
 
     fn adjusted_close_series(&self, symbol: &str) -> Option<&AdjustedCloseSeries> {
-        self.adjusted_close_series_by_symbol_id(self.symbol_id(symbol)?)
+        self.adjusted_close_series_by_symbol
+            .get(symbol)
+            .map(Arc::as_ref)
     }
 
     fn adjusted_close_series_by_symbol_id(&self, symbol_id: u32) -> Option<&AdjustedCloseSeries> {

docs/evidence/symbol-id-series-storage-20260906.json

@@ -1,118 +0,0 @@
-{
-  "schemaVersion": "fidc-symbol-id-series-storage/v1",
-  "measuredAt": "2026-09-06T06:25:00+08:00",
-  "host": "192.168.31.177",
-  "engineCommit": "5a7c49a",
-  "serviceCommit": "61a478839674ab03356083fb777840342ad4c726",
-  "implementation": {
-    "description": "build market and adjusted-close series directly in immutable symbol-id vectors and route string helpers through the canonical symbol-id index",
-    "removedStructures": [
-      "market_series_by_symbol AHashMap",
-      "adjusted_close_series_by_symbol AHashMap",
-      "second Arc copy from string maps into symbol-id vectors"
-    ],
-    "publicDataHelpersChanged": false,
-    "rollingSemanticsChanged": false,
-    "adjustmentSemanticsChanged": false,
-    "pitSemanticsChanged": false,
-    "selectionResultsCached": false,
-    "netSourceLines": -10
-  },
-  "adjacentBaseline": {
-    "engineCommit": "cda249e9b4458770361b4cad570bd1e52f9eb67a",
-    "runs": [
-      {
-        "runId": "btr_1788645721278_2764691_0",
-        "totalSeconds": 18.207,
-        "dataSeconds": 14.052,
-        "datasetConstructSeconds": 4.448
-      },
-      {
-        "runId": "btr_1788646439501_2764691_2",
-        "totalSeconds": 17.858,
-        "dataSeconds": 13.878,
-        "datasetConstructSeconds": 4.546
-      }
-    ],
-    "datasetConstructMedianSeconds": 4.497
-  },
-  "primaryFiveYearContract": {
-    "runId": "btr_1788646914659_2773606_0",
-    "totalReturn": 0.9219861819172002,
-    "tradeCount": 26088,
-    "canonicalSha256": "b42fea66237d06eadb24f6b8c9e2760e7319fe3699f315b99e01f433ef2aa234",
-    "resultStoreSha256": "9ccf0c0fc6f5d72e974381ad4cd09a80241d7de99f2649f2b01736f7c80dc2c7",
-    "coldTotalSeconds": 16.322,
-    "coldDataSeconds": 12.815,
-    "datasetConstructSeconds": 3.899,
-    "hotTotalMedianSeconds": 3.402,
-    "hotEngineMedianSeconds": 2.792,
-    "terminalAuditStatus": "clean",
-    "resultConsistent": true
-  },
-  "secondaryFiveYearContract": {
-    "runId": "btr_1788646986983_2773606_4",
-    "totalReturn": 1.1342962298106998,
-    "tradeCount": 19404,
-    "canonicalSha256": "0dbd3fad624097c673c4a5ec2f545f95e9c21d1d5337bb2b48ffeb22b16cb2b9",
-    "resultStoreSha256": "dd744dd6710bc28bb4ecd9ca912051292b9a1eefa0056e02c62a38cad85cf435",
-    "coldTotalSeconds": 15.292,
-    "coldDataSeconds": 12.238,
-    "datasetConstructSeconds": 3.895,
-    "terminalAuditStatus": "clean",
-    "resultConsistent": true
-  },
-  "genericRankFiveYearContract": {
-    "runId": "btr_1788647058500_2773606_8",
-    "rankBy": "free_float_cap",
-    "totalReturn": 0.7140315244542004,
-    "tradeCount": 21876,
-    "canonicalSha256": "84367993911b42437939aad88f29379d007af6f5f171667ff7ad6677dd488fd2",
-    "resultStoreSha256": "865c00f81d17153285e391eb48ea51487e33fd3bba55a6c2a0ca280b07511077",
-    "coldTotalSeconds": 16.739,
-    "coldDataSeconds": 11.512,
-    "datasetConstructSeconds": 3.663,
-    "terminalAuditStatus": "clean",
-    "resultConsistent": true
-  },
-  "minuteContract": {
-    "runId": "btr_1788647032685_2773606_6",
-    "totalReturn": 0.03473222656500008,
-    "tradeCount": 156,
-    "canonicalSha256": "457c086b1bca784fe83f447bb22451925e8f022456bb0fc7b54237a7a7886849",
-    "resultStoreSha256": "a77894eecf4e6a49168a38ff83cf27226e274b6850e10196892efa7d95be91cd",
-    "coldTotalSeconds": 0.814,
-    "hotTotalSeconds": 0.543,
-    "terminalAuditStatus": "clean",
-    "resultConsistent": true
-  },
-  "performance": {
-    "candidateDatasetConstructSeconds": [3.899, 3.895, 3.663],
-    "candidateDatasetConstructMedianSeconds": 3.895,
-    "datasetConstructMedianImprovementPercent": 13.386702,
-    "primaryColdDataImprovementPercent": 7.659605,
-    "primaryColdTotalImprovementPercent": 8.601187,
-    "wallComparisonsIncludeHostLoadVariance": true
-  },
-  "memory": {
-    "singleDatasetCandidateCurrentBytes": 11495055360,
-    "singleDatasetBaselineCurrentBytes": 11470495744,
-    "comparison": "within allocator and concurrent workload variance; no memory reduction claimed",
-    "repeatedManualCacheClearHighWaterExcluded": true
-  },
-  "testGate": {
-    "corePassed": 538,
-    "ignoredManualBenchmarks": 8,
-    "failed": 0
-  },
-  "remoteArtifacts": [
-    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-primary-five-year-20260906.json",
-    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-secondary-five-year-20260906.json",
-    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-generic-rank-five-year-20260906.json",
-    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-minute-20260906.json"
-  ],
-  "acceptance": {
-    "status": "accepted",
-    "reason": "three independent cold five-year builds reduce DataSet construction time, four distinct strategy contracts preserve exact canonical outputs, and duplicate string-keyed series indexes are removed rather than hidden behind another cache"
-  }
-}

docs/evidence/symbol-id-series-storage-rejection-20260906.json

@@ -0,0 +1,45 @@
+{
+  "schemaVersion": "fidc-symbol-id-series-storage-rejection/v1",
+  "measuredAt": "2026-09-06T06:31:00+08:00",
+  "host": "192.168.31.177",
+  "candidateCommit": "5a7c49a4543b584503ff0d2c2ae513c68d25de8a",
+  "implementation": "remove duplicate string-keyed market and adjusted-close series maps and build symbol-id vectors directly",
+  "businessParity": {
+    "primaryFiveYearCanonicalSha256": "b42fea66237d06eadb24f6b8c9e2760e7319fe3699f315b99e01f433ef2aa234",
+    "secondaryFiveYearCanonicalSha256": "0dbd3fad624097c673c4a5ec2f545f95e9c21d1d5337bb2b48ffeb22b16cb2b9",
+    "genericRankFiveYearCanonicalSha256": "84367993911b42437939aad88f29379d007af6f5f171667ff7ad6677dd488fd2",
+    "minuteCanonicalSha256": "457c086b1bca784fe83f447bb22451925e8f022456bb0fc7b54237a7a7886849",
+    "allTerminalAuditsClean": true,
+    "allResultsConsistent": true
+  },
+  "performance": {
+    "baselineDatasetConstructSeconds": [4.448, 4.546],
+    "candidateEarlyDatasetConstructSeconds": [3.899, 3.895, 3.663],
+    "candidateFinalRestartDatasetConstructSeconds": 4.472,
+    "candidateFinalRestartColdDataSeconds": 14.513,
+    "candidateFinalRestartColdTotalSeconds": 18.381,
+    "conclusion": "the apparent early improvement did not reproduce after a final restart under the current host phase; the final constructor time is equal to the adjacent baseline range"
+  },
+  "memory": {
+    "baselineSingleDatasetCurrentBytes": 11470495744,
+    "candidateSingleDatasetCurrentBytes": 11473674240,
+    "conclusion": "no measurable resident-memory reduction"
+  },
+  "testGate": {
+    "corePassed": 538,
+    "ignoredManualBenchmarks": 8,
+    "failed": 0
+  },
+  "remoteArtifacts": [
+    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-primary-five-year-20260906.json",
+    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-secondary-five-year-20260906.json",
+    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-generic-rank-five-year-20260906.json",
+    "/srv/fidc/canonical/run/fidc-private/evidence/symbol-id-series-minute-20260906.json",
+    "/srv/fidc/canonical/run/fidc-private/evidence/final-symbol-id-series-post-doc-sync-20260906.json"
+  ],
+  "decision": {
+    "status": "rejected_and_removed",
+    "reason": "the candidate preserved correctness but did not provide a stable end-to-end or memory improvement across restart validation; duplicate maps are not a proven material bottleneck",
+    "nextTarget": "remove the SourceRowRecord to DailySnapshot to DataSet multi-stage materialization, or publish a content-addressed base panel that can be mapped across restarts"
+  }
+}