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derive: base layout per symbol/year for backfill-driven 5m aggregation

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Simon-Pierre Boucher committed (Nov 1, 2026) parent 0467d44 Browse files

1 changed file +33 −1

Unified Split
modified services/ingest/src/findata_ingest/tasks/derive.py +33 −1
@@ -4,13 +4,14 @@ from __future__ import annotations
4 4 from datetime import date
5 5 from typing import Any
6 6
7 +import pyarrow as pa
7 8 from findata_core.db import connection, transaction
8 9 from findata_quality import aggregate_bars
9 10 from findata_schema import Interval
10 11
11 12 from findata_ingest.lake import Lake, live_files
12 13 from findata_ingest.reader import read_bars
13 −from findata_ingest.tasks.common import live_delta_paths_for_dates, upsert_coverage
14 +from findata_ingest.tasks.common import live_delta_dates, live_delta_paths_for_dates, upsert_coverage
14 15
15 16
16 17 def run(job: dict[str, Any], lake: Lake, log) -> dict[str, Any]:
@@ -35,6 +36,37 @@ def run(job: dict[str, Any], lake: Lake, log) -> dict[str, Any]:
35 36 all_syms = symbols or [r["symbol"] for r in conn.execute("SELECT DISTINCT symbol FROM coverage WHERE dataset_id=%s AND session_date = ANY(%s)", (src, dates)).fetchall()]
36 37 written, rows = [], 0
37 38 tables = {}
39 + if symbols:
40 + # backfill path: aggregate per symbol over all its sessions and write base files per (symbol, year)
41 + import pyarrow.compute as pc
42 + retire: list[str] = []
43 + for s in sorted(set(x.upper() for x in symbols)):
44 + t, _ = read_bars(src, [s], None, None, lake=lake)
45 + if t.num_rows == 0:
46 + continue
47 + agg = aggregate_bars(t, target, Interval.m1)
48 + years = pc.year(agg.column("session_date"))
49 + with connection() as conn:
50 + old = conn.execute("SELECT path FROM lake_files WHERE dataset_id=%s AND layout='base' AND version_removed IS NULL AND symbol_min=%s AND symbol_max=%s",
51 + (dst, s, s)).fetchall()
52 + delta_dates = live_delta_dates(conn, dst)
53 + if delta_dates:
54 + agg = agg.filter(pc.invert(pc.is_in(agg.column("session_date"), value_set=pa.array(sorted(delta_dates), pa.date32()))))
55 + years = pc.year(agg.column("session_date"))
56 + for y in sorted(set(years.to_pylist())):
57 + ty = agg.filter(pc.equal(years, y))
58 + written.append(lake.write_table(dst, ty, "base", {"symbol": s, "year": str(y)}))
59 + retire.extend(o["path"] for o in old)
60 + rows += agg.num_rows
61 + tables[s] = agg
62 + if not written:
63 + return {"rows": 0, "symbols": len(symbols)}
64 + pub = lake.publish(dst, written, sorted(set(retire)), run_id, note=f"derive {target.value} (base) from {src} for {len(symbols)} symbols")
65 + with transaction() as conn:
66 + for t in tables.values():
67 + upsert_coverage(conn, dst, t, target)
68 + log.info("derive.done", rows=rows, files=len(written), **pub)
69 + return {"rows": rows, "files": len(written), "symbols": len(tables), **pub}
38 70 for d in dates:
39 71 t, _ = read_bars(src, all_syms, d, d, lake=lake)
40 72 if t.num_rows == 0:
41 73
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