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The code in this change was extracted from #2595 (Heikki’s on-demand download draft PR). High-Level Changes - New RemoteLayer Type - On-Demand Download As An Effect Of Page Reconstruction - Breaking Semantics For Physical Size Metrics There are several follow-up work items planned. Refer to the Epic issue on GitHub: https://github.com/neondatabase/neon/issues/2029 closes https://github.com/neondatabase/neon/pull/3013 Co-authored-by: Kirill Bulatov <kirill@neon.tech> Co-authored-by: Christian Schwarz <christian@neon.tech> New RemoteLayer Type ==================== Instead of downloading all layers during tenant attach, we create RemoteLayer instances for each of them and add them to the layer map. On-Demand Download As An Effect Of Page Reconstruction ====================================================== At the heart of pageserver is Timeline::get_reconstruct_data(). It traverses the layer map until it has collected all the data it needs to produce the page image. Most code in the code base uses it, though many layers of indirection. Before this patch, the function would use synchronous filesystem IO to load data from disk-resident layer files if the data was not cached. That is not possible with RemoteLayer, because the layer file has not been downloaded yet. So, we do the download when get_reconstruct_data gets there, i.e., “on demand”. The mechanics of how the download is done are rather involved, because of the infamous async-sync-async sandwich problem that plagues the async Rust world. We use the new PageReconstructResult type to work around this. Its introduction is the cause for a good amount of code churn in this patch. Refer to the block comment on `with_ondemand_download()` for details. Breaking Semantics For Physical Size Metrics ============================================ We rename prometheus metric pageserver_{current,resident}_physical_size to reflect what this metric actually represents with on-demand download. This intentionally BREAKS existing grafana dashboard and the cost model data pipeline. Breaking is desirable because the meaning of this metrics has changed with on-demand download. See https://docs.google.com/document/d/12AFpvKY-7FZdR5a4CaD6Ir_rI3QokdCLSPJ6upHxJBo/edit# for how we will handle this breakage. Likewise, we rename the new billing_metrics’s PhysicalSize => ResidentSize. This is not yet used anywhere, so, this is not a breaking change. There is still a field called TimelineInfo::current_physical_size. It is now the sum of the layer sizes in layer map, regardless of whether local or remote. To compute that sum, we added a new trait method PersistentLayer::file_size(). When updating the Python tests, we got rid of current_physical_size_non_incremental. An earlier commit removed it from the OpenAPI spec already, so this is not a breaking change. test_timeline_size.py has grown additional assertions on the resident_physical_size metric.
478 lines
20 KiB
Python
478 lines
20 KiB
Python
# It's possible to run any regular test with the local fs remote storage via
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# env NEON_PAGESERVER_OVERRIDES="remote_storage={local_path='/tmp/neon_zzz/'}" poetry ......
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import os
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import re
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import shutil
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import threading
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import time
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from pathlib import Path
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import pytest
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from fixtures.log_helper import log
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from fixtures.neon_fixtures import (
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NeonEnvBuilder,
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PageserverApiException,
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RemoteStorageKind,
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available_remote_storages,
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wait_for_last_flush_lsn,
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wait_for_last_record_lsn,
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wait_for_upload,
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wait_until_tenant_state,
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)
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from fixtures.types import Lsn, TenantId, TimelineId
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from fixtures.utils import print_gc_result, query_scalar, wait_until
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#
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# Tests that a piece of data is backed up and restored correctly:
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#
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# 1. Initial pageserver
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# * starts a pageserver with remote storage, stores specific data in its tables
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# * triggers a checkpoint (which produces a local data scheduled for backup), gets the corresponding timeline id
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# * polls the timeline status to ensure it's copied remotely
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# * inserts more data in the pageserver and repeats the process, to check multiple checkpoints case
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# * stops the pageserver, clears all local directories
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#
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# 2. Second pageserver
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# * starts another pageserver, connected to the same remote storage
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# * timeline_attach is called for the same timeline id
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# * timeline status is polled until it's downloaded
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# * queries the specific data, ensuring that it matches the one stored before
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#
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# The tests are done for all types of remote storage pageserver supports.
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@pytest.mark.parametrize("remote_storage_kind", available_remote_storages())
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def test_remote_storage_backup_and_restore(
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neon_env_builder: NeonEnvBuilder,
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remote_storage_kind: RemoteStorageKind,
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):
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# Use this test to check more realistic SK ids: some etcd key parsing bugs were related,
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# and this test needs SK to write data to pageserver, so it will be visible
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neon_env_builder.safekeepers_id_start = 12
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neon_env_builder.enable_remote_storage(
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remote_storage_kind=remote_storage_kind,
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test_name="test_remote_storage_backup_and_restore",
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)
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# Exercise retry code path by making all uploads and downloads fail for the
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# first time. The retries print INFO-messages to the log; we will check
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# that they are present after the test.
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neon_env_builder.pageserver_config_override = "test_remote_failures=1"
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data_id = 1
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data = "just some data"
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##### First start, insert data and upload it to the remote storage
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env = neon_env_builder.init_start()
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# FIXME: Is this expected?
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env.pageserver.allowed_errors.append(
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".*marking .* as locally complete, while it doesnt exist in remote index.*"
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)
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env.pageserver.allowed_errors.append(".*No timelines to attach received.*")
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env.pageserver.allowed_errors.append(".*Failed to get local tenant state.*")
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# FIXME retry downloads without throwing errors
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env.pageserver.allowed_errors.append(".*failed to load remote timeline.*")
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# we have a bunch of pytest.raises for these below
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env.pageserver.allowed_errors.append(".*tenant .*? already exists, state:.*")
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env.pageserver.allowed_errors.append(
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".*Cannot attach tenant .*?, local tenant directory already exists.*"
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)
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env.pageserver.allowed_errors.append(".*simulated failure of remote operation.*")
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pageserver_http = env.pageserver.http_client()
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pg = env.postgres.create_start("main")
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client = env.pageserver.http_client()
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tenant_id = TenantId(pg.safe_psql("show neon.tenant_id")[0][0])
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timeline_id = TimelineId(pg.safe_psql("show neon.timeline_id")[0][0])
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checkpoint_numbers = range(1, 3)
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for checkpoint_number in checkpoint_numbers:
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with pg.cursor() as cur:
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cur.execute(
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f"""
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CREATE TABLE t{checkpoint_number}(id int primary key, data text);
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INSERT INTO t{checkpoint_number} VALUES ({data_id}, '{data}|{checkpoint_number}');
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"""
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)
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current_lsn = Lsn(query_scalar(cur, "SELECT pg_current_wal_flush_lsn()"))
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# wait until pageserver receives that data
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wait_for_last_record_lsn(client, tenant_id, timeline_id, current_lsn)
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# run checkpoint manually to be sure that data landed in remote storage
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pageserver_http.timeline_checkpoint(tenant_id, timeline_id)
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# wait until pageserver successfully uploaded a checkpoint to remote storage
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log.info(f"waiting for checkpoint {checkpoint_number} upload")
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wait_for_upload(client, tenant_id, timeline_id, current_lsn)
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log.info(f"upload of checkpoint {checkpoint_number} is done")
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# Check that we had to retry the uploads
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assert env.pageserver.log_contains(
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".*failed to perform remote task UploadLayer.*, will retry.*"
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)
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assert env.pageserver.log_contains(
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".*failed to perform remote task UploadMetadata.*, will retry.*"
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)
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##### Stop the first pageserver instance, erase all its data
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env.postgres.stop_all()
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env.pageserver.stop()
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dir_to_clear = Path(env.repo_dir) / "tenants"
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shutil.rmtree(dir_to_clear)
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os.mkdir(dir_to_clear)
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##### Second start, restore the data and ensure it's the same
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env.pageserver.start()
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# Introduce failpoint in list remote timelines code path to make tenant_attach fail.
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# This is before the failures injected by test_remote_failures, so it's a permanent error.
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pageserver_http.configure_failpoints(("storage-sync-list-remote-timelines", "return"))
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env.pageserver.allowed_errors.append(
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".*error attaching tenant: storage-sync-list-remote-timelines",
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)
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# Attach it. This HTTP request will succeed and launch a
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# background task to load the tenant. In that background task,
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# listing the remote timelines will fail because of the failpoint,
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# and the tenant will be marked as Broken.
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client.tenant_attach(tenant_id)
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wait_until_tenant_state(pageserver_http, tenant_id, "Broken", 15)
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# Ensure that even though the tenant is broken, we can't attach it again.
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with pytest.raises(Exception, match=f"tenant {tenant_id} already exists, state: Broken"):
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client.tenant_attach(tenant_id)
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# Restart again, this implicitly clears the failpoint.
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# test_remote_failures=1 remains active, though, as it's in the pageserver config.
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# This means that any of the remote client operations after restart will exercise the
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# retry code path.
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#
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# The initiated attach operation should survive the restart, and continue from where it was.
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env.pageserver.stop()
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layer_download_failed_regex = (
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r"download.*[0-9A-F]+-[0-9A-F]+.*open a download stream for layer.*simulated failure"
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)
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assert not env.pageserver.log_contains(
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layer_download_failed_regex
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), "we shouldn't have tried any layer downloads yet since list remote timelines has a failpoint"
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env.pageserver.start()
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# Ensure that the pageserver remembers that the tenant was attaching, by
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# trying to attach it again. It should fail.
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with pytest.raises(Exception, match=f"tenant {tenant_id} already exists, state:"):
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client.tenant_attach(tenant_id)
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log.info("waiting for tenant to become active. this should be quick with on-demand download")
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def tenant_active():
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all_states = client.tenant_list()
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[tenant] = [t for t in all_states if TenantId(t["id"]) == tenant_id]
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assert tenant["state"] == "Active"
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wait_until(
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number_of_iterations=5,
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interval=1,
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func=tenant_active,
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)
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detail = client.timeline_detail(tenant_id, timeline_id)
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log.info("Timeline detail after attach completed: %s", detail)
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assert (
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Lsn(detail["last_record_lsn"]) >= current_lsn
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), "current db Lsn should should not be less than the one stored on remote storage"
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log.info("select some data, this will cause layers to be downloaded")
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pg = env.postgres.create_start("main")
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with pg.cursor() as cur:
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for checkpoint_number in checkpoint_numbers:
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assert (
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query_scalar(cur, f"SELECT data FROM t{checkpoint_number} WHERE id = {data_id};")
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== f"{data}|{checkpoint_number}"
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)
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log.info("ensure that we neede to retry downloads due to test_remote_failures=1")
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assert env.pageserver.log_contains(layer_download_failed_regex)
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# Exercises the upload queue retry code paths.
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# - Use failpoints to cause all storage ops to fail
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# - Churn on database to create layer & index uploads, and layer deletions
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# - Check that these operations are queued up, using the appropriate metrics
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# - Disable failpoints
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# - Wait for all uploads to finish
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# - Verify that remote is consistent and up-to-date (=all retries were done and succeeded)
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@pytest.mark.parametrize("remote_storage_kind", [RemoteStorageKind.LOCAL_FS])
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def test_remote_storage_upload_queue_retries(
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neon_env_builder: NeonEnvBuilder,
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remote_storage_kind: RemoteStorageKind,
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):
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neon_env_builder.enable_remote_storage(
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remote_storage_kind=remote_storage_kind,
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test_name="test_remote_storage_upload_queue_retries",
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)
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env = neon_env_builder.init_start()
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# create tenant with config that will determinstically allow
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# compaction and gc
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tenant_id, timeline_id = env.neon_cli.create_tenant(
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conf={
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# small checkpointing and compaction targets to ensure we generate many upload operations
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"checkpoint_distance": f"{128 * 1024}",
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"compaction_threshold": "1",
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"compaction_target_size": f"{128 * 1024}",
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# no PITR horizon, we specify the horizon when we request on-demand GC
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"pitr_interval": "0s",
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# disable background compaction and GC. We invoke it manually when we want it to happen.
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"gc_period": "0s",
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"compaction_period": "0s",
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# don't create image layers, that causes just noise
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"image_creation_threshold": "10000",
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}
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)
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client = env.pageserver.http_client()
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pg = env.postgres.create_start("main", tenant_id=tenant_id)
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pg.safe_psql("CREATE TABLE foo (id INTEGER PRIMARY KEY, val text)")
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def configure_storage_sync_failpoints(action):
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client.configure_failpoints(
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[
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("before-upload-layer", action),
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("before-upload-index", action),
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("before-delete-layer", action),
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]
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)
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def overwrite_data_and_wait_for_it_to_arrive_at_pageserver(data):
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# create initial set of layers & upload them with failpoints configured
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pg.safe_psql_many(
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[
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f"""
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INSERT INTO foo (id, val)
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SELECT g, '{data}'
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FROM generate_series(1, 10000) g
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ON CONFLICT (id) DO UPDATE
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SET val = EXCLUDED.val
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""",
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# to ensure that GC can actually remove some layers
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"VACUUM foo",
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]
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)
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wait_for_last_flush_lsn(env, pg, tenant_id, timeline_id)
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def get_queued_count(file_kind, op_kind):
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metrics = client.get_metrics()
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matches = re.search(
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f'^pageserver_remote_upload_queue_unfinished_tasks{{file_kind="{file_kind}",op_kind="{op_kind}",tenant_id="{tenant_id}",timeline_id="{timeline_id}"}} (\\S+)$',
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metrics,
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re.MULTILINE,
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)
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assert matches
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return int(matches[1])
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# create some layers & wait for uploads to finish
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overwrite_data_and_wait_for_it_to_arrive_at_pageserver("a")
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client.timeline_checkpoint(tenant_id, timeline_id)
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client.timeline_compact(tenant_id, timeline_id)
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overwrite_data_and_wait_for_it_to_arrive_at_pageserver("b")
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client.timeline_checkpoint(tenant_id, timeline_id)
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client.timeline_compact(tenant_id, timeline_id)
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gc_result = client.timeline_gc(tenant_id, timeline_id, 0)
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print_gc_result(gc_result)
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assert gc_result["layers_removed"] > 0
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wait_until(2, 1, lambda: get_queued_count(file_kind="layer", op_kind="upload") == 0)
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wait_until(2, 1, lambda: get_queued_count(file_kind="index", op_kind="upload") == 0)
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wait_until(2, 1, lambda: get_queued_count(file_kind="layer", op_kind="delete") == 0)
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# let all future operations queue up
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configure_storage_sync_failpoints("return")
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# Create more churn to generate all upload ops.
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# The checkpoint / compact / gc ops will block because they call remote_client.wait_completion().
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# So, run this in a differen thread.
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churn_thread_result = [False]
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def churn_while_failpoints_active(result):
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overwrite_data_and_wait_for_it_to_arrive_at_pageserver("c")
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client.timeline_checkpoint(tenant_id, timeline_id)
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client.timeline_compact(tenant_id, timeline_id)
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overwrite_data_and_wait_for_it_to_arrive_at_pageserver("d")
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client.timeline_checkpoint(tenant_id, timeline_id)
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client.timeline_compact(tenant_id, timeline_id)
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gc_result = client.timeline_gc(tenant_id, timeline_id, 0)
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print_gc_result(gc_result)
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assert gc_result["layers_removed"] > 0
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result[0] = True
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churn_while_failpoints_active_thread = threading.Thread(
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target=churn_while_failpoints_active, args=[churn_thread_result]
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)
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churn_while_failpoints_active_thread.start()
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# wait for churn thread's data to get stuck in the upload queue
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wait_until(10, 0.1, lambda: get_queued_count(file_kind="layer", op_kind="upload") > 0)
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wait_until(10, 0.1, lambda: get_queued_count(file_kind="index", op_kind="upload") >= 2)
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wait_until(10, 0.1, lambda: get_queued_count(file_kind="layer", op_kind="delete") > 0)
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# unblock churn operations
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configure_storage_sync_failpoints("off")
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# ... and wait for them to finish. Exponential back-off in upload queue, so, gracious timeouts.
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wait_until(30, 1, lambda: get_queued_count(file_kind="layer", op_kind="upload") == 0)
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wait_until(30, 1, lambda: get_queued_count(file_kind="index", op_kind="upload") == 0)
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wait_until(30, 1, lambda: get_queued_count(file_kind="layer", op_kind="delete") == 0)
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# The churn thread doesn't make progress once it blocks on the first wait_completion() call,
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# so, give it some time to wrap up.
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churn_while_failpoints_active_thread.join(30)
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assert not churn_while_failpoints_active_thread.is_alive()
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assert churn_thread_result[0]
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# try a restore to verify that the uploads worked
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# XXX: should vary this test to selectively fail just layer uploads, index uploads, deletions
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# but how do we validate the result after restore?
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env.pageserver.stop(immediate=True)
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env.postgres.stop_all()
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dir_to_clear = Path(env.repo_dir) / "tenants"
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shutil.rmtree(dir_to_clear)
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os.mkdir(dir_to_clear)
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env.pageserver.start()
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client = env.pageserver.http_client()
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client.tenant_attach(tenant_id)
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def tenant_active():
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all_states = client.tenant_list()
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[tenant] = [t for t in all_states if TenantId(t["id"]) == tenant_id]
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assert tenant["state"] == "Active"
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wait_until(30, 1, tenant_active)
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log.info("restarting postgres to validate")
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pg = env.postgres.create_start("main", tenant_id=tenant_id)
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with pg.cursor() as cur:
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assert query_scalar(cur, "SELECT COUNT(*) FROM foo WHERE val = 'd'") == 10000
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# Test that we correctly handle timeline with layers stuck in upload queue
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@pytest.mark.parametrize("remote_storage_kind", [RemoteStorageKind.LOCAL_FS])
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def test_timeline_deletion_with_files_stuck_in_upload_queue(
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neon_env_builder: NeonEnvBuilder,
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remote_storage_kind: RemoteStorageKind,
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):
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neon_env_builder.enable_remote_storage(
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remote_storage_kind=remote_storage_kind,
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test_name="test_timeline_deletion_with_files_stuck_in_upload_queue",
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)
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env = neon_env_builder.init_start()
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# create tenant with config that will determinstically allow
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# compaction and gc
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tenant_id, timeline_id = env.neon_cli.create_tenant(
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conf={
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# small checkpointing and compaction targets to ensure we generate many operations
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"checkpoint_distance": f"{64 * 1024}",
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"compaction_threshold": "1",
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"compaction_target_size": f"{64 * 1024}",
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# large horizon to avoid automatic GC (our assert on gc_result below relies on that)
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"gc_horizon": f"{1024 ** 4}",
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"gc_period": "1h",
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# disable PITR so that GC considers just gc_horizon
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"pitr_interval": "0s",
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}
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)
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timeline_path = env.repo_dir / "tenants" / str(tenant_id) / "timelines" / str(timeline_id)
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client = env.pageserver.http_client()
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def get_queued_count(file_kind, op_kind):
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|
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,
|
|
)
|
|
if matches is None:
|
|
return None
|
|
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, so, the metric will be gone
|
|
assert get_queued_count(file_kind="index", op_kind="upload") is None
|
|
|
|
# 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.
|