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https://github.com/neondatabase/neon.git
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## Problem 1. During the rollout we got a panic: "timeline that we were deleting was concurrently removed from 'timelines' map" that was caused by lock guard not being propagated to the background part of the deletion. Existing test didnt catch it because failpoint that was used for verification was placed earlier prior to background task spawning. 2. When looking at surrounding code one more bug was detected. We removed timeline from the map before deletion is finished, which breaks client retry logic, because it will indicate 404 before actual deletion is completed which can lead to client stopping its retry poll earlier. ## Summary of changes 1. Carry the lock guard over to background deletion. Ensure existing test case fails without applied patch (second deletion becomes stuck without it, which eventually leads to a test failure). 2. Move delete_all call earlier so timeline is removed from the map is the last thing done during deletion. Additionally I've added timeline_id to the `update_gc_info` span, because `debug_assert_current_span_has_tenant_and_timeline_id` in `download_remote_layer` was firing when `update_gc_info` lead to on-demand downloads via `find_lsn_for_timestamp` (caught by @problame). This is not directly related to the PR but fixes possible flakiness. Another smaller set of changes involves deletion wrapper used in python tests. Now there is a simpler wrapper that waits for deletions to complete `timeline_delete_wait_completed`. Most of the test_delete_timeline.py tests make negative tests, i.e., "does ps_http.timeline_delete() fail in this and that scenario". These can be left alone. Other places when we actually do the deletions, we need to use the helper that polls for completion. Discussion https://neondb.slack.com/archives/C03F5SM1N02/p1686668007396639 resolves #4496 --------- Co-authored-by: Christian Schwarz <christian@neon.tech>
598 lines
20 KiB
Python
598 lines
20 KiB
Python
from __future__ import annotations
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import json
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import time
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from collections import defaultdict
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from dataclasses import dataclass
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from typing import Any, Dict, List, Optional, Tuple
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import requests
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from fixtures.log_helper import log
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from fixtures.metrics import Metrics, parse_metrics
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from fixtures.pg_version import PgVersion
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from fixtures.types import Lsn, TenantId, TimelineId
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from fixtures.utils import Fn
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class PageserverApiException(Exception):
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def __init__(self, message, status_code: int):
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super().__init__(message)
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self.status_code = status_code
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@dataclass
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class InMemoryLayerInfo:
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kind: str
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lsn_start: str
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lsn_end: Optional[str]
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@classmethod
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def from_json(cls, d: Dict[str, Any]) -> InMemoryLayerInfo:
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return InMemoryLayerInfo(
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kind=d["kind"],
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lsn_start=d["lsn_start"],
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lsn_end=d.get("lsn_end"),
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)
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@dataclass(frozen=True)
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class HistoricLayerInfo:
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kind: str
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layer_file_name: str
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layer_file_size: Optional[int]
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lsn_start: str
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lsn_end: Optional[str]
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remote: bool
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@classmethod
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def from_json(cls, d: Dict[str, Any]) -> HistoricLayerInfo:
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return HistoricLayerInfo(
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kind=d["kind"],
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layer_file_name=d["layer_file_name"],
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layer_file_size=d.get("layer_file_size"),
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lsn_start=d["lsn_start"],
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lsn_end=d.get("lsn_end"),
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remote=d["remote"],
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)
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@dataclass
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class LayerMapInfo:
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in_memory_layers: List[InMemoryLayerInfo]
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historic_layers: List[HistoricLayerInfo]
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@classmethod
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def from_json(cls, d: Dict[str, Any]) -> LayerMapInfo:
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info = LayerMapInfo(in_memory_layers=[], historic_layers=[])
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json_in_memory_layers = d["in_memory_layers"]
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assert isinstance(json_in_memory_layers, List)
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for json_in_memory_layer in json_in_memory_layers:
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info.in_memory_layers.append(InMemoryLayerInfo.from_json(json_in_memory_layer))
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json_historic_layers = d["historic_layers"]
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assert isinstance(json_historic_layers, List)
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for json_historic_layer in json_historic_layers:
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info.historic_layers.append(HistoricLayerInfo.from_json(json_historic_layer))
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return info
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def kind_count(self) -> Dict[str, int]:
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counts: Dict[str, int] = defaultdict(int)
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for inmem_layer in self.in_memory_layers:
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counts[inmem_layer.kind] += 1
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for hist_layer in self.historic_layers:
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counts[hist_layer.kind] += 1
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return counts
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@dataclass
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class TenantConfig:
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tenant_specific_overrides: Dict[str, Any]
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effective_config: Dict[str, Any]
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@classmethod
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def from_json(cls, d: Dict[str, Any]) -> TenantConfig:
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return TenantConfig(
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tenant_specific_overrides=d["tenant_specific_overrides"],
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effective_config=d["effective_config"],
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)
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class PageserverHttpClient(requests.Session):
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def __init__(self, port: int, is_testing_enabled_or_skip: Fn, auth_token: Optional[str] = None):
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super().__init__()
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self.port = port
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self.auth_token = auth_token
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self.is_testing_enabled_or_skip = is_testing_enabled_or_skip
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if auth_token is not None:
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self.headers["Authorization"] = f"Bearer {auth_token}"
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@property
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def base_url(self) -> str:
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return f"http://localhost:{self.port}"
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def verbose_error(self, res: requests.Response):
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try:
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res.raise_for_status()
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except requests.RequestException as e:
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try:
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msg = res.json()["msg"]
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except: # noqa: E722
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msg = ""
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raise PageserverApiException(msg, res.status_code) from e
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def check_status(self):
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self.get(f"http://localhost:{self.port}/v1/status").raise_for_status()
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def configure_failpoints(self, config_strings: Tuple[str, str] | List[Tuple[str, str]]):
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self.is_testing_enabled_or_skip()
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if isinstance(config_strings, tuple):
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pairs = [config_strings]
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else:
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pairs = config_strings
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log.info(f"Requesting config failpoints: {repr(pairs)}")
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res = self.put(
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f"http://localhost:{self.port}/v1/failpoints",
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json=[{"name": name, "actions": actions} for name, actions in pairs],
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)
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log.info(f"Got failpoints request response code {res.status_code}")
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is None
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return res_json
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def tenant_list(self) -> List[Dict[Any, Any]]:
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res = self.get(f"http://localhost:{self.port}/v1/tenant")
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self.verbose_error(res)
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res_json = res.json()
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assert isinstance(res_json, list)
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return res_json
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def tenant_create(
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self, new_tenant_id: TenantId, conf: Optional[Dict[str, Any]] = None
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) -> TenantId:
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if conf is not None:
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assert "new_tenant_id" not in conf.keys()
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res = self.post(
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f"http://localhost:{self.port}/v1/tenant",
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json={
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"new_tenant_id": str(new_tenant_id),
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**(conf or {}),
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},
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)
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self.verbose_error(res)
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if res.status_code == 409:
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raise Exception(f"could not create tenant: already exists for id {new_tenant_id}")
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new_tenant_id = res.json()
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assert isinstance(new_tenant_id, str)
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return TenantId(new_tenant_id)
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def tenant_attach(
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self, tenant_id: TenantId, config: None | Dict[str, Any] = None, config_null: bool = False
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):
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if config_null:
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assert config is None
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body = "null"
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else:
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# null-config is prohibited by the API
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if config is None:
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config = {}
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body = json.dumps({"config": config})
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res = self.post(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/attach",
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data=body,
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headers={"Content-Type": "application/json"},
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)
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self.verbose_error(res)
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def tenant_detach(self, tenant_id: TenantId, detach_ignored=False):
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params = {}
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if detach_ignored:
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params["detach_ignored"] = "true"
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res = self.post(f"http://localhost:{self.port}/v1/tenant/{tenant_id}/detach", params=params)
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self.verbose_error(res)
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def tenant_load(self, tenant_id: TenantId):
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res = self.post(f"http://localhost:{self.port}/v1/tenant/{tenant_id}/load")
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self.verbose_error(res)
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def tenant_ignore(self, tenant_id: TenantId):
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res = self.post(f"http://localhost:{self.port}/v1/tenant/{tenant_id}/ignore")
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self.verbose_error(res)
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def tenant_status(self, tenant_id: TenantId) -> Dict[Any, Any]:
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res = self.get(f"http://localhost:{self.port}/v1/tenant/{tenant_id}")
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self.verbose_error(res)
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res_json = res.json()
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assert isinstance(res_json, dict)
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return res_json
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def tenant_config(self, tenant_id: TenantId) -> TenantConfig:
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res = self.get(f"http://localhost:{self.port}/v1/tenant/{tenant_id}/config")
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self.verbose_error(res)
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return TenantConfig.from_json(res.json())
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def set_tenant_config(self, tenant_id: TenantId, config: dict[str, Any]):
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assert "tenant_id" not in config.keys()
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res = self.put(
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f"http://localhost:{self.port}/v1/tenant/config",
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json={**config, "tenant_id": str(tenant_id)},
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)
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self.verbose_error(res)
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def patch_tenant_config_client_side(
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self,
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tenant_id: TenantId,
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inserts: Optional[Dict[str, Any]] = None,
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removes: Optional[List[str]] = None,
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):
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current = self.tenant_config(tenant_id).tenant_specific_overrides
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if inserts is not None:
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current.update(inserts)
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if removes is not None:
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for key in removes:
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del current[key]
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self.set_tenant_config(tenant_id, current)
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def tenant_size(self, tenant_id: TenantId) -> int:
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return self.tenant_size_and_modelinputs(tenant_id)[0]
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def tenant_size_and_modelinputs(self, tenant_id: TenantId) -> Tuple[int, Dict[str, Any]]:
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"""
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Returns the tenant size, together with the model inputs as the second tuple item.
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"""
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res = self.get(f"http://localhost:{self.port}/v1/tenant/{tenant_id}/synthetic_size")
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self.verbose_error(res)
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res = res.json()
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assert isinstance(res, dict)
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assert TenantId(res["id"]) == tenant_id
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size = res["size"]
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assert type(size) == int
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inputs = res["inputs"]
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assert type(inputs) is dict
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return (size, inputs)
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def tenant_size_debug(self, tenant_id: TenantId) -> str:
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"""
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Returns the tenant size debug info, as an HTML string
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"""
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res = self.get(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/synthetic_size",
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headers={"Accept": "text/html"},
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)
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return res.text
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def timeline_list(
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self,
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tenant_id: TenantId,
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include_non_incremental_logical_size: bool = False,
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include_timeline_dir_layer_file_size_sum: bool = False,
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) -> List[Dict[str, Any]]:
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params = {}
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if include_non_incremental_logical_size:
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params["include-non-incremental-logical-size"] = "true"
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if include_timeline_dir_layer_file_size_sum:
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params["include-timeline-dir-layer-file-size-sum"] = "true"
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res = self.get(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline", params=params
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)
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self.verbose_error(res)
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res_json = res.json()
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assert isinstance(res_json, list)
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return res_json
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def timeline_create(
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self,
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pg_version: PgVersion,
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tenant_id: TenantId,
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new_timeline_id: TimelineId,
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ancestor_timeline_id: Optional[TimelineId] = None,
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ancestor_start_lsn: Optional[Lsn] = None,
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**kwargs,
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) -> Dict[Any, Any]:
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body: Dict[str, Any] = {
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"new_timeline_id": str(new_timeline_id),
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"ancestor_start_lsn": str(ancestor_start_lsn) if ancestor_start_lsn else None,
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"ancestor_timeline_id": str(ancestor_timeline_id) if ancestor_timeline_id else None,
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}
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if pg_version != PgVersion.NOT_SET:
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body["pg_version"] = int(pg_version)
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res = self.post(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline", json=body, **kwargs
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)
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self.verbose_error(res)
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if res.status_code == 409:
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raise Exception(f"could not create timeline: already exists for id {new_timeline_id}")
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res_json = res.json()
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assert isinstance(res_json, dict)
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return res_json
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def timeline_detail(
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self,
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tenant_id: TenantId,
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timeline_id: TimelineId,
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include_non_incremental_logical_size: bool = False,
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include_timeline_dir_layer_file_size_sum: bool = False,
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**kwargs,
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) -> Dict[Any, Any]:
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params = {}
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if include_non_incremental_logical_size:
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params["include-non-incremental-logical-size"] = "true"
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if include_timeline_dir_layer_file_size_sum:
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params["include-timeline-dir-layer-file-size-sum"] = "true"
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res = self.get(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}",
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params=params,
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**kwargs,
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)
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self.verbose_error(res)
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res_json = res.json()
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assert isinstance(res_json, dict)
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return res_json
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def timeline_delete(self, tenant_id: TenantId, timeline_id: TimelineId, **kwargs):
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"""
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Note that deletion is not instant, it is scheduled and performed mostly in the background.
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So if you need to wait for it to complete use `timeline_delete_wait_completed`.
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For longer description consult with pageserver openapi spec.
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"""
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res = self.delete(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}", **kwargs
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)
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is None
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def timeline_gc(
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self, tenant_id: TenantId, timeline_id: TimelineId, gc_horizon: Optional[int]
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) -> dict[str, Any]:
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self.is_testing_enabled_or_skip()
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log.info(
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f"Requesting GC: tenant {tenant_id}, timeline {timeline_id}, gc_horizon {repr(gc_horizon)}"
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)
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res = self.put(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/do_gc",
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json={"gc_horizon": gc_horizon},
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)
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log.info(f"Got GC request response code: {res.status_code}")
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is not None
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assert isinstance(res_json, dict)
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return res_json
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def timeline_compact(self, tenant_id: TenantId, timeline_id: TimelineId):
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self.is_testing_enabled_or_skip()
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log.info(f"Requesting compact: tenant {tenant_id}, timeline {timeline_id}")
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res = self.put(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/compact"
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)
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log.info(f"Got compact request response code: {res.status_code}")
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is None
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def timeline_get_lsn_by_timestamp(
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self, tenant_id: TenantId, timeline_id: TimelineId, timestamp
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):
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log.info(
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f"Requesting lsn by timestamp {timestamp}, tenant {tenant_id}, timeline {timeline_id}"
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)
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res = self.get(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/get_lsn_by_timestamp?timestamp={timestamp}",
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)
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self.verbose_error(res)
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res_json = res.json()
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return res_json
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def timeline_checkpoint(self, tenant_id: TenantId, timeline_id: TimelineId):
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self.is_testing_enabled_or_skip()
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log.info(f"Requesting checkpoint: tenant {tenant_id}, timeline {timeline_id}")
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res = self.put(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/checkpoint"
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)
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log.info(f"Got checkpoint request response code: {res.status_code}")
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is None
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def timeline_spawn_download_remote_layers(
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self,
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tenant_id: TenantId,
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timeline_id: TimelineId,
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max_concurrent_downloads: int,
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) -> dict[str, Any]:
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body = {
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"max_concurrent_downloads": max_concurrent_downloads,
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}
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res = self.post(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/download_remote_layers",
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json=body,
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)
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is not None
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assert isinstance(res_json, dict)
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return res_json
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def timeline_poll_download_remote_layers_status(
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self,
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tenant_id: TenantId,
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timeline_id: TimelineId,
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spawn_response: dict[str, Any],
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poll_state=None,
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) -> None | dict[str, Any]:
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res = self.get(
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f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/download_remote_layers",
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)
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self.verbose_error(res)
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res_json = res.json()
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assert res_json is not None
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assert isinstance(res_json, dict)
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# assumption in this API client here is that nobody else spawns the task
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assert res_json["task_id"] == spawn_response["task_id"]
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if poll_state is None or res_json["state"] == poll_state:
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return res_json
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return None
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def timeline_download_remote_layers(
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|
self,
|
|
tenant_id: TenantId,
|
|
timeline_id: TimelineId,
|
|
max_concurrent_downloads: int,
|
|
errors_ok=False,
|
|
at_least_one_download=True,
|
|
):
|
|
res = self.timeline_spawn_download_remote_layers(
|
|
tenant_id, timeline_id, max_concurrent_downloads
|
|
)
|
|
while True:
|
|
completed = self.timeline_poll_download_remote_layers_status(
|
|
tenant_id, timeline_id, res, poll_state="Completed"
|
|
)
|
|
if not completed:
|
|
time.sleep(0.1)
|
|
continue
|
|
if not errors_ok:
|
|
assert completed["failed_download_count"] == 0
|
|
if at_least_one_download:
|
|
assert completed["successful_download_count"] > 0
|
|
return completed
|
|
|
|
def get_metrics_str(self) -> str:
|
|
"""You probably want to use get_metrics() instead."""
|
|
res = self.get(f"http://localhost:{self.port}/metrics")
|
|
self.verbose_error(res)
|
|
return res.text
|
|
|
|
def get_metrics(self) -> Metrics:
|
|
res = self.get_metrics_str()
|
|
return parse_metrics(res)
|
|
|
|
def get_timeline_metric(
|
|
self, tenant_id: TenantId, timeline_id: TimelineId, metric_name: str
|
|
) -> float:
|
|
metrics = self.get_metrics()
|
|
return metrics.query_one(
|
|
metric_name,
|
|
filter={
|
|
"tenant_id": str(tenant_id),
|
|
"timeline_id": str(timeline_id),
|
|
},
|
|
).value
|
|
|
|
def get_remote_timeline_client_metric(
|
|
self,
|
|
metric_name: str,
|
|
tenant_id: TenantId,
|
|
timeline_id: TimelineId,
|
|
file_kind: str,
|
|
op_kind: str,
|
|
) -> Optional[float]:
|
|
metrics = self.get_metrics()
|
|
matches = metrics.query_all(
|
|
name=metric_name,
|
|
filter={
|
|
"tenant_id": str(tenant_id),
|
|
"timeline_id": str(timeline_id),
|
|
"file_kind": str(file_kind),
|
|
"op_kind": str(op_kind),
|
|
},
|
|
)
|
|
if len(matches) == 0:
|
|
value = None
|
|
elif len(matches) == 1:
|
|
value = matches[0].value
|
|
assert value is not None
|
|
else:
|
|
assert len(matches) < 2, "above filter should uniquely identify metric"
|
|
return value
|
|
|
|
def get_metric_value(
|
|
self, name: str, filter: Optional[Dict[str, str]] = None
|
|
) -> Optional[float]:
|
|
metrics = self.get_metrics()
|
|
results = metrics.query_all(name, filter=filter)
|
|
if not results:
|
|
log.info(f'could not find metric "{name}"')
|
|
return None
|
|
assert len(results) == 1, f"metric {name} with given filters is not unique, got: {results}"
|
|
return results[0].value
|
|
|
|
def layer_map_info(
|
|
self,
|
|
tenant_id: TenantId,
|
|
timeline_id: TimelineId,
|
|
) -> LayerMapInfo:
|
|
res = self.get(
|
|
f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/layer/",
|
|
)
|
|
self.verbose_error(res)
|
|
return LayerMapInfo.from_json(res.json())
|
|
|
|
def download_layer(self, tenant_id: TenantId, timeline_id: TimelineId, layer_name: str):
|
|
res = self.get(
|
|
f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/layer/{layer_name}",
|
|
)
|
|
self.verbose_error(res)
|
|
|
|
assert res.status_code == 200
|
|
|
|
def download_all_layers(self, tenant_id: TenantId, timeline_id: TimelineId):
|
|
info = self.layer_map_info(tenant_id, timeline_id)
|
|
for layer in info.historic_layers:
|
|
if not layer.remote:
|
|
continue
|
|
self.download_layer(tenant_id, timeline_id, layer.layer_file_name)
|
|
|
|
def evict_layer(self, tenant_id: TenantId, timeline_id: TimelineId, layer_name: str):
|
|
res = self.delete(
|
|
f"http://localhost:{self.port}/v1/tenant/{tenant_id}/timeline/{timeline_id}/layer/{layer_name}",
|
|
)
|
|
self.verbose_error(res)
|
|
|
|
assert res.status_code == 200
|
|
|
|
def evict_all_layers(self, tenant_id: TenantId, timeline_id: TimelineId):
|
|
info = self.layer_map_info(tenant_id, timeline_id)
|
|
for layer in info.historic_layers:
|
|
self.evict_layer(tenant_id, timeline_id, layer.layer_file_name)
|
|
|
|
def disk_usage_eviction_run(self, request: dict[str, Any]):
|
|
res = self.put(
|
|
f"http://localhost:{self.port}/v1/disk_usage_eviction/run",
|
|
json=request,
|
|
)
|
|
self.verbose_error(res)
|
|
return res.json()
|
|
|
|
def tenant_break(self, tenant_id: TenantId):
|
|
res = self.put(f"http://localhost:{self.port}/v1/tenant/{tenant_id}/break")
|
|
self.verbose_error(res)
|
|
|
|
def post_tracing_event(self, level: str, message: str):
|
|
res = self.post(
|
|
f"http://localhost:{self.port}/v1/tracing/event",
|
|
json={
|
|
"level": level,
|
|
"message": message,
|
|
},
|
|
)
|
|
self.verbose_error(res)
|