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FA-45056 / Data systems / Open access

Fetch drains all remaining rows despite its output quota · case 01

Fetch drains all remaining rows despite its output quota.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

batch-resume-cursor: Fetch drains all remaining rows despite its output quota.

THE FAILURE

batch-resume-cursor: Fetch drains all remaining rows despite its output quota.

Unsuccessful approach: Allowing zero quota emits one extra row.

Case contract

Fetch at most quota rows from a sequence of batches starting at [batch-index,row-offset]. Skip exhausted and empty batches, return the emitted rows and a canonical next cursor, and mark exhaustion as [number-of-batches,0]. Quota zero preserves a normalized cursor.

Why this case matters

A bounded deterministic data engine model makes representation and changelog faults reproducible.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(d):
    try:
        batches,batch,offset,quota=d
        out=[]
        while batch<len(batches) and offset>=len(batches[batch]):
            batch+=1; offset=0
        while batch<len(batches):
            out.append(batches[batch][offset])
            offset+=1; quota-=1
            while batch<len(batches) and offset>=len(batches[batch]):
                batch+=1; offset=0
        return [out,[batch,offset]]
    except (IndexError, KeyError, ValueError, StopIteration) as exc:
        return {"representation_error": type(exc).__name__}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
if N == 1:
    check('partial current batch', solve([[[1, 2, 3]], 0, 1, 1]), [[2], [0, 2]])
    check('cross empty batches', solve([[[1], [], [], [2, 3]], 0, 0, 2]), [[1, 2], [3, 1]])
    check('initial exhausted', solve([[[], [], [1, 2]], 0, 0, 1]), [[1], [2, 1]])
    check('resume past long batch', solve([[[1, 2], [3, 4]], 0, 0, 3]), [[1, 2, 3], [1, 1]])
    check('all exhausted', solve([[[1]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[1, 2]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[1, 2, 3, 4]], 0, 0, 2]), [[1, 2], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 2:
    check('partial current batch', solve([[[2, 3, 4]], 0, 1, 1]), [[3], [0, 2]])
    check('cross empty batches', solve([[[2], [], [], [3, 4]], 0, 0, 2]), [[2, 3], [3, 1]])
    check('initial exhausted', solve([[[], [], [2, 3]], 0, 0, 1]), [[2], [2, 1]])
    check('resume past long batch', solve([[[2, 3], [4, 5]], 0, 0, 3]), [[2, 3, 4], [1, 1]])
    check('all exhausted', solve([[[2]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[2, 3]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[2, 3, 4, 5]], 0, 0, 2]), [[2, 3], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 3:
    check('partial current batch', solve([[[3, 4, 5]], 0, 1, 1]), [[4], [0, 2]])
    check('cross empty batches', solve([[[3], [], [], [4, 5]], 0, 0, 2]), [[3, 4], [3, 1]])
    check('initial exhausted', solve([[[], [], [3, 4]], 0, 0, 1]), [[3], [2, 1]])
    check('resume past long batch', solve([[[3, 4], [5, 6]], 0, 0, 3]), [[3, 4, 5], [1, 1]])
    check('all exhausted', solve([[[3]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[3, 4]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[3, 4, 5, 6]], 0, 0, 2]), [[3, 4], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 4:
    check('partial current batch', solve([[[4, 5, 6]], 0, 1, 1]), [[5], [0, 2]])
    check('cross empty batches', solve([[[4], [], [], [5, 6]], 0, 0, 2]), [[4, 5], [3, 1]])
    check('initial exhausted', solve([[[], [], [4, 5]], 0, 0, 1]), [[4], [2, 1]])
    check('resume past long batch', solve([[[4, 5], [6, 7]], 0, 0, 3]), [[4, 5, 6], [1, 1]])
    check('all exhausted', solve([[[4]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[4, 5]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[4, 5, 6, 7]], 0, 0, 2]), [[4, 5], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 5:
    check('partial current batch', solve([[[5, 6, 7]], 0, 1, 1]), [[6], [0, 2]])
    check('cross empty batches', solve([[[5], [], [], [6, 7]], 0, 0, 2]), [[5, 6], [3, 1]])
    check('initial exhausted', solve([[[], [], [5, 6]], 0, 0, 1]), [[5], [2, 1]])
    check('resume past long batch', solve([[[5, 6], [7, 8]], 0, 0, 3]), [[5, 6, 7], [1, 1]])
    check('all exhausted', solve([[[5]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[5, 6]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[5, 6, 7, 8]], 0, 0, 2]), [[5, 6], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
partial current batch[[2, 3], [1, 0]][[2], [0, 2]]Failed
cross empty batches[[1, 2, 3], [4, 0]][[1, 2], [3, 1]]Failed
initial exhausted[[1, 2], [3, 0]][[1], [2, 1]]Failed
resume past long batch[[1, 2, 3, 4], [2, 0]][[1, 2, 3], [1, 1]]Failed
all exhausted[[], [1, 0]][[], [1, 0]]Passed
zero quota[[2], [1, 0]][[], [0, 1]]Failed
within long batch[[1, 2, 3, 4], [1, 0]][[1, 2], [0, 2]]Failed
empty stream[[], [0, 0]][[], [0, 0]]Passed

SHA-256 / f73bb423a86cff328129da6fb373580140aff1ca3de987b6e15acb27e1e54be5

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(d):
    try:
        batches,batch,offset,quota=d
        out=[]
        while batch<len(batches) and offset>=len(batches[batch]):
            batch+=1; offset=0
        while quota>=0 and batch<len(batches):
            out.append(batches[batch][offset])
            offset+=1; quota-=1
            while batch<len(batches) and offset>=len(batches[batch]):
                batch+=1; offset=0
        return [out,[batch,offset]]
    except (IndexError, KeyError, ValueError, StopIteration) as exc:
        return {"representation_error": type(exc).__name__}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
if N == 1:
    check('partial current batch', solve([[[1, 2, 3]], 0, 1, 1]), [[2], [0, 2]])
    check('cross empty batches', solve([[[1], [], [], [2, 3]], 0, 0, 2]), [[1, 2], [3, 1]])
    check('initial exhausted', solve([[[], [], [1, 2]], 0, 0, 1]), [[1], [2, 1]])
    check('resume past long batch', solve([[[1, 2], [3, 4]], 0, 0, 3]), [[1, 2, 3], [1, 1]])
    check('all exhausted', solve([[[1]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[1, 2]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[1, 2, 3, 4]], 0, 0, 2]), [[1, 2], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 2:
    check('partial current batch', solve([[[2, 3, 4]], 0, 1, 1]), [[3], [0, 2]])
    check('cross empty batches', solve([[[2], [], [], [3, 4]], 0, 0, 2]), [[2, 3], [3, 1]])
    check('initial exhausted', solve([[[], [], [2, 3]], 0, 0, 1]), [[2], [2, 1]])
    check('resume past long batch', solve([[[2, 3], [4, 5]], 0, 0, 3]), [[2, 3, 4], [1, 1]])
    check('all exhausted', solve([[[2]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[2, 3]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[2, 3, 4, 5]], 0, 0, 2]), [[2, 3], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 3:
    check('partial current batch', solve([[[3, 4, 5]], 0, 1, 1]), [[4], [0, 2]])
    check('cross empty batches', solve([[[3], [], [], [4, 5]], 0, 0, 2]), [[3, 4], [3, 1]])
    check('initial exhausted', solve([[[], [], [3, 4]], 0, 0, 1]), [[3], [2, 1]])
    check('resume past long batch', solve([[[3, 4], [5, 6]], 0, 0, 3]), [[3, 4, 5], [1, 1]])
    check('all exhausted', solve([[[3]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[3, 4]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[3, 4, 5, 6]], 0, 0, 2]), [[3, 4], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 4:
    check('partial current batch', solve([[[4, 5, 6]], 0, 1, 1]), [[5], [0, 2]])
    check('cross empty batches', solve([[[4], [], [], [5, 6]], 0, 0, 2]), [[4, 5], [3, 1]])
    check('initial exhausted', solve([[[], [], [4, 5]], 0, 0, 1]), [[4], [2, 1]])
    check('resume past long batch', solve([[[4, 5], [6, 7]], 0, 0, 3]), [[4, 5, 6], [1, 1]])
    check('all exhausted', solve([[[4]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[4, 5]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[4, 5, 6, 7]], 0, 0, 2]), [[4, 5], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
elif N == 5:
    check('partial current batch', solve([[[5, 6, 7]], 0, 1, 1]), [[6], [0, 2]])
    check('cross empty batches', solve([[[5], [], [], [6, 7]], 0, 0, 2]), [[5, 6], [3, 1]])
    check('initial exhausted', solve([[[], [], [5, 6]], 0, 0, 1]), [[5], [2, 1]])
    check('resume past long batch', solve([[[5, 6], [7, 8]], 0, 0, 3]), [[5, 6, 7], [1, 1]])
    check('all exhausted', solve([[[5]], 0, 1, 3]), [[], [1, 0]])
    check('zero quota', solve([[[5, 6]], 0, 1, 0]), [[], [0, 1]])
    check('within long batch', solve([[[5, 6, 7, 8]], 0, 0, 2]), [[5, 6], [0, 2]])
    check('empty stream', solve([[], 0, 0, 2]), [[], [0, 0]])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
partial current batch[[2, 3], [1, 0]][[2], [0, 2]]Failed
cross empty batches[[1, 2, 3], [4, 0]][[1, 2], [3, 1]]Failed
initial exhausted[[1, 2], [3, 0]][[1], [2, 1]]Failed
resume past long batch[[1, 2, 3, 4], [2, 0]][[1, 2, 3], [1, 1]]Failed
all exhausted[[], [1, 0]][[], [1, 0]]Passed
zero quota[[2], [1, 0]][[], [0, 1]]Failed
within long batch[[1, 2, 3], [0, 3]][[1, 2], [0, 2]]Failed
empty stream[[], [0, 0]][[], [0, 0]]Passed

SHA-256 / 1549f753e0fff852305dc039bbfde9bce841d12c8efe95f8514969d47e716707

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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Verification & scope

Offline stipulated semantics over valid small inputs; no performance, concurrency, or production-engine conformance claim. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.

Observations recorded using Python 3.12.14 at 2026-09-29T14:44:18.307400+00:00.

Case digest / 836bc9cc9d97112a4f8cbbb551b44ccba2d5b049300d483ef28e50260b299149