(google-cloud-spanner) DB-API Cursor fetchall/fetchmany/fetchone silently return partial results when the result stream fails mid-read
Mantenedores costumam responder em até 1 dia
Ninguém assumiu esta issue ainda.
Avaliação
- Dificuldade
- 3/5
- Tempo estimado
- 1-2 dias
- Facilidade para iniciantes
- 42/100
Direção de pesquisa
Start in Cursor._fetch in google/cloud/spanner_dbapi/cursor.py, where the except block records the exception and then returns rows instead of re-raising. Run repro_partial_fetch.py (mocked iterator, no Spanner instance needed) to confirm the partial results. Done when the mocked errors raise from fetchall() for read-only connections and Aborted in read-write connections no longer returns a truncated result, with existing spanner_dbapi cursor tests still passing.
Escrita pelo modelo de indexação a partir do texto da issue.
Descrição
Determine this is the right repository
- I determined this is the correct repository in which to report this bug.
This is a client library bug, not a Spanner service bug. The service correctly ends the stream with an error, and StreamedResultSet raises it. The DB-API Cursor then swallows it.
Summary of the issue
Context
We read Spanner through SQLAlchemy (sqlalchemy-spanner), which fetches rows through the DB-API cursor's fetchall() / fetchmany() / fetchone(). Sometimes a query's result stream fails after the first chunk of rows has already arrived, for example with DeadlineExceeded on a long read or Aborted in a read-write transaction. When that happens, the cursor returns the rows read so far as if they were the complete result. Nothing is raised or logged, so the caller can't tell a partial result from a complete one.
The cause is in Cursor._fetch (google/cloud/spanner_dbapi/cursor.py). It wraps the read in except Exception as e: exception = e, records the exception for the transaction-retry bookkeeping (add_fetch_statement_for_retry), and then return rows without re-raising. The same code is on main today. Some older releases (for example 3.51 and 3.63) had a raise, but a return rows inside the finally discarded it, with the same effect.
Not every error is affected. _restart_on_unavailable resumes UNAVAILABLE and RST_STREAM before they reach the cursor. Every other error that reaches the cursor mid-stream is swallowed: DeadlineExceeded, Aborted, ResourceExhausted, Cancelled, non-resumable InternalServerError, session NotFound, and so on.
Aborted behaves worse than the others:
- In a read-write connection,
_fetchcallstransaction_helper.retry_transaction(). That replays the transaction's statements on new cursors (_cursor_map). Thewhile Trueloop then reads on from the original cursor's broken stream, so_fetchreturns[]. - In a read-only connection the
Abortedis swallowed like the other errors, and_fetchreturns[].
Expected Behavior:
When the result stream fails partway, fetchall() / fetchmany() / fetchone() either raise the error or (for Aborted in a read-write transaction) retry and return the complete result. A caller never gets a silently truncated result.
Actual Behavior:
They return the rows read before the failure (or [] for Aborted) and raise nothing.
API client name and version
google-cloud-spanner 3.72.0 (also reproduced on 3.68.0; same _fetch on main)
Reproduction steps: code
file: repro_partial_fetch.py
"""Minimal reproduction: spanner_dbapi Cursor.fetchall()/fetchmany() return a partial
result, with no exception, when the result stream fails after some rows were read.
No Spanner instance is needed: the cursor's row iterator is replaced by one that yields
three rows and then raises, the way StreamedResultSet does when the gRPC stream breaks.
"""
from unittest import mock
from google.api_core import exceptions
from google.cloud.spanner_dbapi.cursor import Cursor
from google.cloud.spanner_v1 import __version__
def rows_then(error):
yield ["row-1"]
yield ["row-2"]
yield ["row-3"]
raise error
def cursor_over(stream, read_only):
connection = mock.MagicMock(is_closed=False, read_only=read_only)
cursor = Cursor(connection)
cursor._itr = stream
return cursor
print("google-cloud-spanner", __version__)
for read_only in (True, False):
for error in (
exceptions.DeadlineExceeded("Deadline Exceeded"),
exceptions.ResourceExhausted("quota"),
exceptions.Aborted("Transaction was aborted."),
):
cursor = cursor_over(rows_then(error), read_only)
try:
rows = cursor.fetchall()
print(f"read_only={read_only}: {type(error).__name__} after 3 rows -> fetchall() returned {rows!r}, no exception")
except Exception as raised:
print(f"read_only={read_only}: {type(error).__name__} after 3 rows -> raised {type(raised).__name__}")
Reproduction steps: supporting files
None. Needs only pip install google-cloud-spanner==3.72.0. No Spanner instance or emulator is required.
Reproduction steps: actual results
google-cloud-spanner 3.72.0
read_only=True: DeadlineExceeded after 3 rows -> fetchall() returned [['row-1'], ['row-2'], ['row-3']], no exception
read_only=True: ResourceExhausted after 3 rows -> fetchall() returned [['row-1'], ['row-2'], ['row-3']], no exception
read_only=True: Aborted after 3 rows -> fetchall() returned [], no exception
read_only=False: DeadlineExceeded after 3 rows -> fetchall() returned [['row-1'], ['row-2'], ['row-3']], no exception
read_only=False: ResourceExhausted after 3 rows -> fetchall() returned [['row-1'], ['row-2'], ['row-3']], no exception
read_only=False: Aborted after 3 rows -> fetchall() returned [], no exception
Reproduction steps: expected results
google-cloud-spanner 3.72.0
read_only=True: DeadlineExceeded after 3 rows -> raised DeadlineExceeded
read_only=True: ResourceExhausted after 3 rows -> raised ResourceExhausted
read_only=True: Aborted after 3 rows -> raised Aborted
read_only=False: DeadlineExceeded after 3 rows -> raised DeadlineExceeded
read_only=False: ResourceExhausted after 3 rows -> raised ResourceExhausted
read_only=False: Aborted after 3 rows -> raised Aborted (or the transaction is retried and the full result returned)
OS & version + platform
macOS 27.2 (arm64) for the repro. The code path is platform-independent; we run on Linux (Google App Engine and Cloud Run).
Python environment
Python 3.12.13
Python dependencies
Package Version
---------------------- -------
google-api-core 2.44.0
google-cloud-spanner 3.72.0
grpcio 1.85.1
proto-plus 1.29.0
protobuf 7.36.2
(In production, also sqlalchemy-spanner 1.19.0 and SQLAlchemy 2.0.)
Additional context
Impact: SQLAlchemy reads through these cursor methods, so application code gets short or empty query results that look complete. Code that acts on what's missing from a result can then delete or overwrite good data. Examples are a sync job that removes rows not returned, or a check that a record doesn't exist yet.
Suggested fix: keep recording the exception for the retry bookkeeping, then re-raise it. For Aborted in a read-write transaction, either raise it to the caller, or, after retry_transaction(), continue from the replayed cursor's result instead of the original cursor's broken stream.
Workaround we're using in the meantime: replace Cursor._fetch with a version that records the exception via add_fetch_statement_for_retry and then re-raises.
- Linguagem predominante
- Python
- Estrelas
- 5.4k
- Forks
- 1.8k
- Merge médio
- 2d 7h
- PRs com merge (30d)
- 173
Preparar o ambiente
- Sem Dockerfile nem arquivo Docker Compose
- Tem um modelo de pull request
- Ler o guia de contribuição
Primeiros passos
- Leia a issue inteira e depois o guia de contribuição do projeto.
- Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
- Faça um fork do repositório e trabalhe em uma branch.
- Abra um pull request que referencie o número da issue.
Mais de googleapis/google-cloud-python
-
firestore: field path with a quoted name ending in a backslash is misparsedTalvez já em andamento @sebxt assumiu há 25 dias. Aberta
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 78/100
googleapis/google-cloud-python#18771 ·
Mantenedores costumam responder em até 1 dia
-
api: spanner type: feature request
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 68/100
googleapis/google-cloud-python#18584 ·
Mantenedores costumam responder em até 1 dia
-
auth: `impersonated_credentials` loses `subject` on copy, so `with_scopes()` and `with_quota_project()` turn off domain wide delegationTalvez já em andamento @Om-singhaI assumiu há 55 dias. Abertaauth priority: p2 type: bug
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 88/100
googleapis/google-cloud-python#18428 ·
Mantenedores costumam responder em até 1 dia
-
A client called `run_in_transaction` be stuck if Spanner is downTalvez já em andamento @founderinaction assumiu há 7 dias. Abertapriority: p2 type: bug
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 72/100
googleapis/google-cloud-python#18375 · 1 comentário ·
Mantenedores costumam responder em até 1 dia
-
ci: enable --strict flag in presubmit twine_checkTalvez livre de novo @ohmayr assumiu há 44 dias e não há nenhum pull request aberto. Aberta
Dificuldade 1/5 Menos de uma hora Facilidade para iniciantes 76/100
googleapis/google-cloud-python#18339 · 1 comentário · 1 responsável ·
Mantenedores costumam responder em até 1 dia
Todas as issues de googleapis/google-cloud-python
Issues semelhantes
-
plot_graph crashes when a mesh node has no m2m edgeTalvez já em andamento @tygvi assumiu hoje. Aberta
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 78/100
mllam/neural-lam#883 · 1 comentário ·
Mantenedores costumam responder em até 2 dias
-
enhancement possible-duplicate
Dificuldade 1/5 1-3 horas Facilidade para iniciantes 78/100
AOSSIE-Org/PictoPy#1715 · 2 comentários ·
Mantenedores costumam responder em até 6 dias
-
SQLite connector omits generated columns from the catalog, and drops relationships sourced on themAberta
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 72/100
NVIDIA/auto-ontology#511 ·
Mantenedores costumam responder em até 1 dia
-
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 72/100
ethereum/execution-specs#3996 ·
Mantenedores costumam responder em até 1 dia
-
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 62/100
cpp-best-practices/project_validator#267 ·
Mantenedores costumam responder em até 1 dia