Files
neon/test_runner/regress/test_remote_storage.py
Heikki Linnakangas b513619503 Remove obsolete 'awaits_download' field.
It used to be a separate piece of state, but after 9a6c0be823 it's just
an alias for the Tenant being in Attaching state. It was only used in
one assertion in a test, but that check doesn't make sense anymore, so
just remove it.

Fixes https://github.com/neondatabase/neon/issues/2930
2022-12-07 13:13:54 +02:00

453 lines
18 KiB
Python

# It's possible to run any regular test with the local fs remote storage via
# env NEON_PAGESERVER_OVERRIDES="remote_storage={local_path='/tmp/neon_zzz/'}" poetry ......
import os
import re
import shutil
import threading
import time
from pathlib import Path
import pytest
from fixtures.log_helper import log
from fixtures.neon_fixtures import (
NeonEnvBuilder,
PageserverApiException,
RemoteStorageKind,
assert_no_in_progress_downloads_for_tenant,
available_remote_storages,
wait_for_last_flush_lsn,
wait_for_last_record_lsn,
wait_for_upload,
)
from fixtures.types import Lsn, TenantId, TimelineId
from fixtures.utils import print_gc_result, query_scalar, wait_until
#
# Tests that a piece of data is backed up and restored correctly:
#
# 1. Initial pageserver
# * starts a pageserver with remote storage, stores specific data in its tables
# * triggers a checkpoint (which produces a local data scheduled for backup), gets the corresponding timeline id
# * polls the timeline status to ensure it's copied remotely
# * inserts more data in the pageserver and repeats the process, to check multiple checkpoints case
# * stops the pageserver, clears all local directories
#
# 2. Second pageserver
# * starts another pageserver, connected to the same remote storage
# * timeline_attach is called for the same timeline id
# * timeline status is polled until it's downloaded
# * queries the specific data, ensuring that it matches the one stored before
#
# The tests are done for all types of remote storage pageserver supports.
@pytest.mark.parametrize("remote_storage_kind", available_remote_storages())
def test_remote_storage_backup_and_restore(
neon_env_builder: NeonEnvBuilder,
remote_storage_kind: RemoteStorageKind,
):
# Use this test to check more realistic SK ids: some etcd key parsing bugs were related,
# and this test needs SK to write data to pageserver, so it will be visible
neon_env_builder.safekeepers_id_start = 12
neon_env_builder.enable_remote_storage(
remote_storage_kind=remote_storage_kind,
test_name="test_remote_storage_backup_and_restore",
)
data_id = 1
data_secret = "very secret secret"
##### First start, insert secret data and upload it to the remote storage
env = neon_env_builder.init_start()
# FIXME: Is this expected?
env.pageserver.allowed_errors.append(
".*marking .* as locally complete, while it doesnt exist in remote index.*"
)
env.pageserver.allowed_errors.append(".*No timelines to attach received.*")
env.pageserver.allowed_errors.append(".*Failed to get local tenant state.*")
# FIXME retry downloads without throwing errors
env.pageserver.allowed_errors.append(".*failed to load remote timeline.*")
# we have a bunch of pytest.raises for these below
env.pageserver.allowed_errors.append(".*tenant .*? already exists, state:.*")
env.pageserver.allowed_errors.append(
".*Cannot attach tenant .*?, local tenant directory already exists.*"
)
pageserver_http = env.pageserver.http_client()
pg = env.postgres.create_start("main")
client = env.pageserver.http_client()
tenant_id = TenantId(pg.safe_psql("show neon.tenant_id")[0][0])
timeline_id = TimelineId(pg.safe_psql("show neon.timeline_id")[0][0])
checkpoint_numbers = range(1, 3)
# On the first iteration, exercise retry code path by making the uploads
# fail for the first 3 times
action = "3*return->off"
pageserver_http.configure_failpoints(
[
("before-upload-layer", action),
("before-upload-index", action),
]
)
for checkpoint_number in checkpoint_numbers:
with pg.cursor() as cur:
cur.execute(
f"""
CREATE TABLE t{checkpoint_number}(id int primary key, secret text);
INSERT INTO t{checkpoint_number} VALUES ({data_id}, '{data_secret}|{checkpoint_number}');
"""
)
current_lsn = Lsn(query_scalar(cur, "SELECT pg_current_wal_flush_lsn()"))
# wait until pageserver receives that data
wait_for_last_record_lsn(client, tenant_id, timeline_id, current_lsn)
# run checkpoint manually to be sure that data landed in remote storage
pageserver_http.timeline_checkpoint(tenant_id, timeline_id)
# wait until pageserver successfully uploaded a checkpoint to remote storage
log.info(f"waiting for checkpoint {checkpoint_number} upload")
wait_for_upload(client, tenant_id, timeline_id, current_lsn)
log.info(f"upload of checkpoint {checkpoint_number} is done")
##### Stop the first pageserver instance, erase all its data
env.postgres.stop_all()
env.pageserver.stop()
dir_to_clear = Path(env.repo_dir) / "tenants"
shutil.rmtree(dir_to_clear)
os.mkdir(dir_to_clear)
##### Second start, restore the data and ensure it's the same
env.pageserver.start()
# Introduce failpoint in download
pageserver_http.configure_failpoints(("remote-storage-download-pre-rename", "return"))
client.tenant_attach(tenant_id)
# is there a better way to assert that failpoint triggered?
time.sleep(10)
# assert cannot attach timeline that is scheduled for download
# FIXME implement layer download retries
with pytest.raises(Exception, match=f"tenant {tenant_id} already exists, state: Broken"):
client.tenant_attach(tenant_id)
tenant_status = client.tenant_status(tenant_id)
log.info("Tenant status with active failpoint: %s", tenant_status)
# FIXME implement layer download retries
# assert tenant_status["has_in_progress_downloads"] is True
# trigger temporary download files removal
env.pageserver.stop()
env.pageserver.start()
# ensure that an initiated attach operation survives pageserver restart
with pytest.raises(Exception, match=f"tenant {tenant_id} already exists, state:"):
client.tenant_attach(tenant_id)
log.info("waiting for timeline redownload")
wait_until(
number_of_iterations=20,
interval=1,
func=lambda: assert_no_in_progress_downloads_for_tenant(client, tenant_id),
)
detail = client.timeline_detail(tenant_id, timeline_id)
log.info("Timeline detail after attach completed: %s", detail)
assert (
Lsn(detail["last_record_lsn"]) >= current_lsn
), "current db Lsn should should not be less than the one stored on remote storage"
pg = env.postgres.create_start("main")
with pg.cursor() as cur:
for checkpoint_number in checkpoint_numbers:
assert (
query_scalar(cur, f"SELECT secret FROM t{checkpoint_number} WHERE id = {data_id};")
== f"{data_secret}|{checkpoint_number}"
)
# Exercises the upload queue retry code paths.
# - Use failpoints to cause all storage ops to fail
# - Churn on database to create layer & index uploads, and layer deletions
# - Check that these operations are queued up, using the appropriate metrics
# - Disable failpoints
# - Wait for all uploads to finish
# - Verify that remote is consistent and up-to-date (=all retries were done and succeeded)
@pytest.mark.parametrize("remote_storage_kind", [RemoteStorageKind.LOCAL_FS])
def test_remote_storage_upload_queue_retries(
neon_env_builder: NeonEnvBuilder,
remote_storage_kind: RemoteStorageKind,
):
neon_env_builder.enable_remote_storage(
remote_storage_kind=remote_storage_kind,
test_name="test_remote_storage_upload_queue_retries",
)
env = neon_env_builder.init_start()
# create tenant with config that will determinstically allow
# compaction and gc
tenant_id, timeline_id = env.neon_cli.create_tenant(
conf={
# small checkpointing and compaction targets to ensure we generate many upload operations
"checkpoint_distance": f"{128 * 1024}",
"compaction_threshold": "1",
"compaction_target_size": f"{128 * 1024}",
# no PITR horizon, we specify the horizon when we request on-demand GC
"pitr_interval": "0s",
# disable background compaction and GC. We invoke it manually when we want it to happen.
"gc_period": "0s",
"compaction_period": "0s",
# don't create image layers, that causes just noise
"image_creation_threshold": "10000",
}
)
client = env.pageserver.http_client()
pg = env.postgres.create_start("main", tenant_id=tenant_id)
pg.safe_psql("CREATE TABLE foo (id INTEGER PRIMARY KEY, val text)")
def configure_storage_sync_failpoints(action):
client.configure_failpoints(
[
("before-upload-layer", action),
("before-upload-index", action),
("before-delete-layer", action),
]
)
def overwrite_data_and_wait_for_it_to_arrive_at_pageserver(data):
# create initial set of layers & upload them with failpoints configured
pg.safe_psql_many(
[
f"""
INSERT INTO foo (id, val)
SELECT g, '{data}'
FROM generate_series(1, 10000) g
ON CONFLICT (id) DO UPDATE
SET val = EXCLUDED.val
""",
# to ensure that GC can actually remove some layers
"VACUUM foo",
]
)
wait_for_last_flush_lsn(env, pg, tenant_id, timeline_id)
def get_queued_count(file_kind, op_kind):
metrics = client.get_metrics()
matches = re.search(
f'^pageserver_remote_upload_queue_unfinished_tasks{{file_kind="{file_kind}",op_kind="{op_kind}",tenant_id="{tenant_id}",timeline_id="{timeline_id}"}} (\\S+)$',
metrics,
re.MULTILINE,
)
assert matches
return int(matches[1])
# create some layers & wait for uploads to finish
overwrite_data_and_wait_for_it_to_arrive_at_pageserver("a")
client.timeline_checkpoint(tenant_id, timeline_id)
client.timeline_compact(tenant_id, timeline_id)
overwrite_data_and_wait_for_it_to_arrive_at_pageserver("b")
client.timeline_checkpoint(tenant_id, timeline_id)
client.timeline_compact(tenant_id, timeline_id)
gc_result = client.timeline_gc(tenant_id, timeline_id, 0)
print_gc_result(gc_result)
assert gc_result["layers_removed"] > 0
wait_until(2, 1, lambda: get_queued_count(file_kind="layer", op_kind="upload") == 0)
wait_until(2, 1, lambda: get_queued_count(file_kind="index", op_kind="upload") == 0)
wait_until(2, 1, lambda: get_queued_count(file_kind="layer", op_kind="delete") == 0)
# let all future operations queue up
configure_storage_sync_failpoints("return")
# Create more churn to generate all upload ops.
# The checkpoint / compact / gc ops will block because they call remote_client.wait_completion().
# So, run this in a differen thread.
churn_thread_result = [False]
def churn_while_failpoints_active(result):
overwrite_data_and_wait_for_it_to_arrive_at_pageserver("c")
client.timeline_checkpoint(tenant_id, timeline_id)
client.timeline_compact(tenant_id, timeline_id)
overwrite_data_and_wait_for_it_to_arrive_at_pageserver("d")
client.timeline_checkpoint(tenant_id, timeline_id)
client.timeline_compact(tenant_id, timeline_id)
gc_result = client.timeline_gc(tenant_id, timeline_id, 0)
print_gc_result(gc_result)
assert gc_result["layers_removed"] > 0
result[0] = True
churn_while_failpoints_active_thread = threading.Thread(
target=churn_while_failpoints_active, args=[churn_thread_result]
)
churn_while_failpoints_active_thread.start()
# wait for churn thread's data to get stuck in the upload queue
wait_until(10, 0.1, lambda: get_queued_count(file_kind="layer", op_kind="upload") > 0)
wait_until(10, 0.1, lambda: get_queued_count(file_kind="index", op_kind="upload") >= 2)
wait_until(10, 0.1, lambda: get_queued_count(file_kind="layer", op_kind="delete") > 0)
# unblock churn operations
configure_storage_sync_failpoints("off")
# ... and wait for them to finish. Exponential back-off in upload queue, so, gracious timeouts.
wait_until(30, 1, lambda: get_queued_count(file_kind="layer", op_kind="upload") == 0)
wait_until(30, 1, lambda: get_queued_count(file_kind="index", op_kind="upload") == 0)
wait_until(30, 1, lambda: get_queued_count(file_kind="layer", op_kind="delete") == 0)
# The churn thread doesn't make progress once it blocks on the first wait_completion() call,
# so, give it some time to wrap up.
churn_while_failpoints_active_thread.join(30)
assert not churn_while_failpoints_active_thread.is_alive()
assert churn_thread_result[0]
# try a restore to verify that the uploads worked
# XXX: should vary this test to selectively fail just layer uploads, index uploads, deletions
# but how do we validate the result after restore?
env.pageserver.stop(immediate=True)
env.postgres.stop_all()
dir_to_clear = Path(env.repo_dir) / "tenants"
shutil.rmtree(dir_to_clear)
os.mkdir(dir_to_clear)
env.pageserver.start()
client = env.pageserver.http_client()
client.tenant_attach(tenant_id)
def tenant_active():
all_states = client.tenant_list()
[tenant] = [t for t in all_states if TenantId(t["id"]) == tenant_id]
assert tenant["has_in_progress_downloads"] is False
assert tenant["state"] == "Active"
wait_until(30, 1, tenant_active)
log.info("restarting postgres to validate")
pg = env.postgres.create_start("main", tenant_id=tenant_id)
with pg.cursor() as cur:
assert query_scalar(cur, "SELECT COUNT(*) FROM foo WHERE val = 'd'") == 10000
# Test that we correctly handle timeline with layers stuck in upload queue
@pytest.mark.parametrize("remote_storage_kind", [RemoteStorageKind.LOCAL_FS])
def test_timeline_deletion_with_files_stuck_in_upload_queue(
neon_env_builder: NeonEnvBuilder,
remote_storage_kind: RemoteStorageKind,
):
neon_env_builder.enable_remote_storage(
remote_storage_kind=remote_storage_kind,
test_name="test_timeline_deletion_with_files_stuck_in_upload_queue",
)
env = neon_env_builder.init_start()
# create tenant with config that will determinstically allow
# compaction and gc
tenant_id, timeline_id = env.neon_cli.create_tenant(
conf={
# small checkpointing and compaction targets to ensure we generate many operations
"checkpoint_distance": f"{64 * 1024}",
"compaction_threshold": "1",
"compaction_target_size": f"{64 * 1024}",
# large horizon to avoid automatic GC (our assert on gc_result below relies on that)
"gc_horizon": f"{1024 ** 4}",
"gc_period": "1h",
# disable PITR so that GC considers just gc_horizon
"pitr_interval": "0s",
}
)
timeline_path = env.repo_dir / "tenants" / str(tenant_id) / "timelines" / str(timeline_id)
client = env.pageserver.http_client()
def get_queued_count(file_kind, op_kind):
metrics = client.get_metrics()
matches = re.search(
f'^pageserver_remote_upload_queue_unfinished_tasks{{file_kind="{file_kind}",op_kind="{op_kind}",tenant_id="{tenant_id}",timeline_id="{timeline_id}"}} (\\S+)$',
metrics,
re.MULTILINE,
)
assert matches
return int(matches[1])
pg = env.postgres.create_start("main", tenant_id=tenant_id)
client.configure_failpoints(("before-upload-layer", "return"))
pg.safe_psql_many(
[
"CREATE TABLE foo (x INTEGER)",
"INSERT INTO foo SELECT g FROM generate_series(1, 10000) g",
]
)
wait_for_last_flush_lsn(env, pg, tenant_id, timeline_id)
# Kick off a checkpoint operation.
# It will get stuck in remote_client.wait_completion(), since the select query will have
# generated layer upload ops already.
checkpoint_allowed_to_fail = threading.Event()
def checkpoint_thread_fn():
try:
client.timeline_checkpoint(tenant_id, timeline_id)
except PageserverApiException:
assert (
checkpoint_allowed_to_fail.is_set()
), "checkpoint op should only fail in response to timeline deletion"
checkpoint_thread = threading.Thread(target=checkpoint_thread_fn)
checkpoint_thread.start()
# Wait for stuck uploads. NB: if there were earlier layer flushes initiated during `INSERT INTO`,
# this will be their uploads. If there were none, it's the timeline_checkpoint()'s uploads.
def assert_compacted_and_uploads_queued():
assert timeline_path.exists()
assert len(list(timeline_path.glob("*"))) >= 8
assert get_queued_count(file_kind="index", op_kind="upload") > 0
wait_until(20, 0.1, assert_compacted_and_uploads_queued)
# Regardless, give checkpoint some time to block for good.
# Not strictly necessary, but might help uncover failure modes in the future.
time.sleep(2)
# Now delete the timeline. It should take priority over ongoing
# checkpoint operations. Hence, checkpoint is allowed to fail now.
log.info("sending delete request")
checkpoint_allowed_to_fail.set()
client.timeline_delete(tenant_id, timeline_id)
assert not timeline_path.exists()
# timeline deletion should kill ongoing uploads
assert get_queued_count(file_kind="index", op_kind="upload") == 0
# timeline deletion should be unblocking checkpoint ops
checkpoint_thread.join(2.0)
assert not checkpoint_thread.is_alive()
# Just to be sure, unblock ongoing uploads. If the previous assert was incorrect, or the prometheus metric broken,
# this would likely generate some ERROR level log entries that the NeonEnvBuilder would detect
client.configure_failpoints(("before-upload-layer", "off"))
# XXX force retry, currently we have to wait for exponential backoff
time.sleep(10)
# TODO Test that we correctly handle GC of files that are stuck in upload queue.