From 483eb2f56657e8e7f419ab1a4fab8dce9ade8609 Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Sat, 27 Apr 2024 20:24:20 +0200 Subject: Adding upstream version 14.2.21. Signed-off-by: Daniel Baumann --- src/pybind/mgr/balancer/__init__.py | 1 + src/pybind/mgr/balancer/module.py | 1324 +++++++++++++++++++++++++++++++++++ 2 files changed, 1325 insertions(+) create mode 100644 src/pybind/mgr/balancer/__init__.py create mode 100644 src/pybind/mgr/balancer/module.py (limited to 'src/pybind/mgr/balancer') diff --git a/src/pybind/mgr/balancer/__init__.py b/src/pybind/mgr/balancer/__init__.py new file mode 100644 index 00000000..8f210ac9 --- /dev/null +++ b/src/pybind/mgr/balancer/__init__.py @@ -0,0 +1 @@ +from .module import Module diff --git a/src/pybind/mgr/balancer/module.py b/src/pybind/mgr/balancer/module.py new file mode 100644 index 00000000..acca915d --- /dev/null +++ b/src/pybind/mgr/balancer/module.py @@ -0,0 +1,1324 @@ +""" +Balance PG distribution across OSDs. +""" + +import copy +import errno +import json +import math +import random +import six +import time +from mgr_module import MgrModule, CommandResult +from threading import Event +from mgr_module import CRUSHMap +import datetime + +TIME_FORMAT = '%Y-%m-%d_%H:%M:%S' + +class MappingState: + def __init__(self, osdmap, raw_pg_stats, raw_pool_stats, desc=''): + self.desc = desc + self.osdmap = osdmap + self.osdmap_dump = self.osdmap.dump() + self.crush = osdmap.get_crush() + self.crush_dump = self.crush.dump() + self.raw_pg_stats = raw_pg_stats + self.raw_pool_stats = raw_pool_stats + self.pg_stat = { + i['pgid']: i['stat_sum'] for i in raw_pg_stats.get('pg_stats', []) + } + osd_poolids = [p['pool'] for p in self.osdmap_dump.get('pools', [])] + pg_poolids = [p['poolid'] for p in raw_pool_stats.get('pool_stats', [])] + self.poolids = set(osd_poolids) & set(pg_poolids) + self.pg_up = {} + self.pg_up_by_poolid = {} + for poolid in self.poolids: + self.pg_up_by_poolid[poolid] = osdmap.map_pool_pgs_up(poolid) + for a,b in six.iteritems(self.pg_up_by_poolid[poolid]): + self.pg_up[a] = b + + def calc_misplaced_from(self, other_ms): + num = len(other_ms.pg_up) + misplaced = 0 + for pgid, before in six.iteritems(other_ms.pg_up): + if before != self.pg_up.get(pgid, []): + misplaced += 1 + if num > 0: + return float(misplaced) / float(num) + return 0.0 + +class Plan: + def __init__(self, name, ms, pools): + self.mode = 'unknown' + self.name = name + self.initial = ms + self.pools = pools + + self.osd_weights = {} + self.compat_ws = {} + self.inc = ms.osdmap.new_incremental() + + def final_state(self): + self.inc.set_osd_reweights(self.osd_weights) + self.inc.set_crush_compat_weight_set_weights(self.compat_ws) + return MappingState(self.initial.osdmap.apply_incremental(self.inc), + self.initial.raw_pg_stats, + self.initial.raw_pool_stats, + 'plan %s final' % self.name) + + def dump(self): + return json.dumps(self.inc.dump(), indent=4) + + def show(self): + ls = [] + ls.append('# starting osdmap epoch %d' % self.initial.osdmap.get_epoch()) + ls.append('# starting crush version %d' % + self.initial.osdmap.get_crush_version()) + ls.append('# mode %s' % self.mode) + if len(self.compat_ws) and \ + not CRUSHMap.have_default_choose_args(self.initial.crush_dump): + ls.append('ceph osd crush weight-set create-compat') + for osd, weight in six.iteritems(self.compat_ws): + ls.append('ceph osd crush weight-set reweight-compat %s %f' % + (osd, weight)) + for osd, weight in six.iteritems(self.osd_weights): + ls.append('ceph osd reweight osd.%d %f' % (osd, weight)) + incdump = self.inc.dump() + for pgid in incdump.get('old_pg_upmap_items', []): + ls.append('ceph osd rm-pg-upmap-items %s' % pgid) + for item in incdump.get('new_pg_upmap_items', []): + osdlist = [] + for m in item['mappings']: + osdlist += [m['from'], m['to']] + ls.append('ceph osd pg-upmap-items %s %s' % + (item['pgid'], ' '.join([str(a) for a in osdlist]))) + return '\n'.join(ls) + + +class Eval: + def __init__(self, ms): + self.ms = ms + self.root_ids = {} # root name -> id + self.pool_name = {} # pool id -> pool name + self.pool_id = {} # pool name -> id + self.pool_roots = {} # pool name -> root name + self.root_pools = {} # root name -> pools + self.target_by_root = {} # root name -> target weight map + self.count_by_pool = {} + self.count_by_root = {} + self.actual_by_pool = {} # pool -> by_* -> actual weight map + self.actual_by_root = {} # pool -> by_* -> actual weight map + self.total_by_pool = {} # pool -> by_* -> total + self.total_by_root = {} # root -> by_* -> total + self.stats_by_pool = {} # pool -> by_* -> stddev or avg -> value + self.stats_by_root = {} # root -> by_* -> stddev or avg -> value + + self.score_by_pool = {} + self.score_by_root = {} + + self.score = 0.0 + + def show(self, verbose=False): + if verbose: + r = self.ms.desc + '\n' + r += 'target_by_root %s\n' % self.target_by_root + r += 'actual_by_pool %s\n' % self.actual_by_pool + r += 'actual_by_root %s\n' % self.actual_by_root + r += 'count_by_pool %s\n' % self.count_by_pool + r += 'count_by_root %s\n' % self.count_by_root + r += 'total_by_pool %s\n' % self.total_by_pool + r += 'total_by_root %s\n' % self.total_by_root + r += 'stats_by_root %s\n' % self.stats_by_root + r += 'score_by_pool %s\n' % self.score_by_pool + r += 'score_by_root %s\n' % self.score_by_root + else: + r = self.ms.desc + ' ' + r += 'score %f (lower is better)\n' % self.score + return r + + def calc_stats(self, count, target, total): + num = max(len(target), 1) + r = {} + for t in ('pgs', 'objects', 'bytes'): + if total[t] == 0: + r[t] = { + 'avg': 0, + 'stddev': 0, + 'sum_weight': 0, + 'score': 0, + } + continue + + avg = float(total[t]) / float(num) + dev = 0.0 + + # score is a measure of how uneven the data distribution is. + # score lies between [0, 1), 0 means perfect distribution. + score = 0.0 + sum_weight = 0.0 + + for k, v in six.iteritems(count[t]): + # adjust/normalize by weight + if target[k]: + adjusted = float(v) / target[k] / float(num) + else: + adjusted = 0.0 + + # Overweighted devices and their weights are factors to calculate reweight_urgency. + # One 10% underfilled device with 5 2% overfilled devices, is arguably a better + # situation than one 10% overfilled with 5 2% underfilled devices + if adjusted > avg: + ''' + F(x) = 2*phi(x) - 1, where phi(x) = cdf of standard normal distribution + x = (adjusted - avg)/avg. + Since, we're considering only over-weighted devices, x >= 0, and so phi(x) lies in [0.5, 1). + To bring range of F(x) in range [0, 1), we need to make the above modification. + + In general, we need to use a function F(x), where x = (adjusted - avg)/avg + 1. which is bounded between 0 and 1, so that ultimately reweight_urgency will also be bounded. + 2. A larger value of x, should imply more urgency to reweight. + 3. Also, the difference between F(x) when x is large, should be minimal. + 4. The value of F(x) should get close to 1 (highest urgency to reweight) with steeply. + + Could have used F(x) = (1 - e^(-x)). But that had slower convergence to 1, compared to the one currently in use. + + cdf of standard normal distribution: https://stackoverflow.com/a/29273201 + ''' + score += target[k] * (math.erf(((adjusted - avg)/avg) / math.sqrt(2.0))) + sum_weight += target[k] + dev += (avg - adjusted) * (avg - adjusted) + stddev = math.sqrt(dev / float(max(num - 1, 1))) + score = score / max(sum_weight, 1) + r[t] = { + 'avg': avg, + 'stddev': stddev, + 'sum_weight': sum_weight, + 'score': score, + } + return r + +class Module(MgrModule): + MODULE_OPTIONS = [ + { + 'name': 'active', + 'type': 'bool', + 'default': False, + 'desc': 'automatically balance PGs across cluster', + 'runtime': True, + }, + { + 'name': 'begin_time', + 'type': 'str', + 'default': '0000', + 'desc': 'beginning time of day to automatically balance', + 'long_desc': 'This is a time of day in the format HHMM.', + 'runtime': True, + }, + { + 'name': 'end_time', + 'type': 'str', + 'default': '2400', + 'desc': 'ending time of day to automatically balance', + 'long_desc': 'This is a time of day in the format HHMM.', + 'runtime': True, + }, + { + 'name': 'begin_weekday', + 'type': 'uint', + 'default': 0, + 'min': 0, + 'max': 7, + 'desc': 'Restrict automatic balancing to this day of the week or later', + 'long_desc': '0 or 7 = Sunday, 1 = Monday, etc.', + 'runtime': True, + }, + { + 'name': 'end_weekday', + 'type': 'uint', + 'default': 7, + 'min': 0, + 'max': 7, + 'desc': 'Restrict automatic balancing to days of the week earlier than this', + 'long_desc': '0 or 7 = Sunday, 1 = Monday, etc.', + 'runtime': True, + }, + { + 'name': 'crush_compat_max_iterations', + 'type': 'uint', + 'default': 25, + 'min': 1, + 'max': 250, + 'desc': 'maximum number of iterations to attempt optimization', + 'runtime': True, + }, + { + 'name': 'crush_compat_metrics', + 'type': 'str', + 'default': 'pgs,objects,bytes', + 'desc': 'metrics with which to calculate OSD utilization', + 'long_desc': 'Value is a list of one or more of "pgs", "objects", or "bytes", and indicates which metrics to use to balance utilization.', + 'runtime': True, + }, + { + 'name': 'crush_compat_step', + 'type': 'float', + 'default': .5, + 'min': .001, + 'max': .999, + 'desc': 'aggressiveness of optimization', + 'long_desc': '.99 is very aggressive, .01 is less aggressive', + 'runtime': True, + }, + { + 'name': 'min_score', + 'type': 'float', + 'default': 0, + 'desc': 'minimum score, below which no optimization is attempted', + 'runtime': True, + }, + { + 'name': 'mode', + 'desc': 'Balancer mode', + 'default': 'none', + 'enum_allowed': ['none', 'crush-compat', 'upmap'], + 'runtime': True, + }, + { + 'name': 'sleep_interval', + 'type': 'secs', + 'default': 60, + 'desc': 'how frequently to wake up and attempt optimization', + 'runtime': True, + }, + { + 'name': 'upmap_max_iterations', + 'type': 'uint', + 'default': 10, + 'desc': 'maximum upmap optimization iterations', + 'runtime': True, + }, + { + 'name': 'upmap_max_deviation', + 'type': 'int', + 'default': 5, + 'min': 1, + 'desc': 'deviation below which no optimization is attempted', + 'long_desc': 'If the number of PGs are within this count then no optimization is attempted', + 'runtime': True, + }, + { + 'name': 'pool_ids', + 'type': 'str', + 'default': '', + 'desc': 'pools which the automatic balancing will be limited to', + 'runtime': True, + }, + ] + + COMMANDS = [ + { + "cmd": "balancer status", + "desc": "Show balancer status", + "perm": "r", + }, + { + "cmd": "balancer mode name=mode,type=CephChoices,strings=none|crush-compat|upmap", + "desc": "Set balancer mode", + "perm": "rw", + }, + { + "cmd": "balancer on", + "desc": "Enable automatic balancing", + "perm": "rw", + }, + { + "cmd": "balancer off", + "desc": "Disable automatic balancing", + "perm": "rw", + }, + { + "cmd": "balancer pool ls", + "desc": "List automatic balancing pools. " + "Note that empty list means all existing pools will be automatic balancing targets, " + "which is the default behaviour of balancer.", + "perm": "r", + }, + { + "cmd": "balancer pool add name=pools,type=CephString,n=N", + "desc": "Enable automatic balancing for specific pools", + "perm": "rw", + }, + { + "cmd": "balancer pool rm name=pools,type=CephString,n=N", + "desc": "Disable automatic balancing for specific pools", + "perm": "rw", + }, + { + "cmd": "balancer eval name=option,type=CephString,req=false", + "desc": "Evaluate data distribution for the current cluster or specific pool or specific plan", + "perm": "r", + }, + { + "cmd": "balancer eval-verbose name=option,type=CephString,req=false", + "desc": "Evaluate data distribution for the current cluster or specific pool or specific plan (verbosely)", + "perm": "r", + }, + { + "cmd": "balancer optimize name=plan,type=CephString name=pools,type=CephString,n=N,req=false", + "desc": "Run optimizer to create a new plan", + "perm": "rw", + }, + { + "cmd": "balancer show name=plan,type=CephString", + "desc": "Show details of an optimization plan", + "perm": "r", + }, + { + "cmd": "balancer rm name=plan,type=CephString", + "desc": "Discard an optimization plan", + "perm": "rw", + }, + { + "cmd": "balancer reset", + "desc": "Discard all optimization plans", + "perm": "rw", + }, + { + "cmd": "balancer dump name=plan,type=CephString", + "desc": "Show an optimization plan", + "perm": "r", + }, + { + "cmd": "balancer ls", + "desc": "List all plans", + "perm": "r", + }, + { + "cmd": "balancer execute name=plan,type=CephString", + "desc": "Execute an optimization plan", + "perm": "rw", + }, + ] + active = False + run = True + plans = {} + mode = '' + optimizing = False + last_optimize_started = '' + last_optimize_duration = '' + optimize_result = '' + success_string = 'Optimization plan created successfully' + in_progress_string = 'in progress' + + def __init__(self, *args, **kwargs): + super(Module, self).__init__(*args, **kwargs) + self.event = Event() + + def handle_command(self, inbuf, command): + self.log.warn("Handling command: '%s'" % str(command)) + if command['prefix'] == 'balancer status': + s = { + 'plans': list(self.plans.keys()), + 'active': self.active, + 'last_optimize_started': self.last_optimize_started, + 'last_optimize_duration': self.last_optimize_duration, + 'optimize_result': self.optimize_result, + 'mode': self.get_module_option('mode'), + } + return (0, json.dumps(s, indent=4), '') + elif command['prefix'] == 'balancer mode': + if command['mode'] == 'upmap': + min_compat_client = self.get_osdmap().dump().get('require_min_compat_client', '') + if min_compat_client < 'luminous': # works well because version is alphabetized.. + warn = 'min_compat_client "%s" ' \ + '< "luminous", which is required for pg-upmap. ' \ + 'Try "ceph osd set-require-min-compat-client luminous" ' \ + 'before enabling this mode' % min_compat_client + return (-errno.EPERM, '', warn) + elif command['mode'] == 'crush-compat': + ms = MappingState(self.get_osdmap(), + self.get("pg_stats"), + self.get("pool_stats"), + 'initialize compat weight-set') + self.get_compat_weight_set_weights(ms) # ignore error + self.set_module_option('mode', command['mode']) + return (0, '', '') + elif command['prefix'] == 'balancer on': + if not self.active: + self.set_module_option('active', 'true') + self.active = True + self.event.set() + return (0, '', '') + elif command['prefix'] == 'balancer off': + if self.active: + self.set_module_option('active', 'false') + self.active = False + self.event.set() + return (0, '', '') + elif command['prefix'] == 'balancer pool ls': + pool_ids = self.get_module_option('pool_ids') + if pool_ids == '': + return (0, '', '') + pool_ids = pool_ids.split(',') + pool_ids = [int(p) for p in pool_ids] + pool_name_by_id = dict((p['pool'], p['pool_name']) for p in self.get_osdmap().dump().get('pools', [])) + should_prune = False + final_ids = [] + final_names = [] + for p in pool_ids: + if p in pool_name_by_id: + final_ids.append(p) + final_names.append(pool_name_by_id[p]) + else: + should_prune = True + if should_prune: # some pools were gone, prune + self.set_module_option('pool_ids', ','.join(final_ids)) + return (0, json.dumps(final_names, indent=4), '') + elif command['prefix'] == 'balancer pool add': + raw_names = command['pools'] + pool_id_by_name = dict((p['pool_name'], p['pool']) for p in self.get_osdmap().dump().get('pools', [])) + invalid_names = [p for p in raw_names if p not in pool_id_by_name] + if invalid_names: + return (-errno.EINVAL, '', 'pool(s) %s not found' % invalid_names) + to_add = [str(pool_id_by_name[p]) for p in raw_names if p in pool_id_by_name] + existing = self.get_module_option('pool_ids') + final = to_add + if existing != '': + existing = existing.split(',') + final = set(to_add) | set(existing) + self.set_module_option('pool_ids', ','.join(final)) + return (0, '', '') + elif command['prefix'] == 'balancer pool rm': + raw_names = command['pools'] + existing = self.get_module_option('pool_ids') + if existing == '': # for idempotence + return (0, '', '') + existing = existing.split(',') + osdmap = self.get_osdmap() + pool_ids = [str(p['pool']) for p in osdmap.dump().get('pools', [])] + pool_id_by_name = dict((p['pool_name'], p['pool']) for p in osdmap.dump().get('pools', [])) + final = [p for p in existing if p in pool_ids] + to_delete = [str(pool_id_by_name[p]) for p in raw_names if p in pool_id_by_name] + final = set(final) - set(to_delete) + self.set_module_option('pool_ids', ','.join(final)) + return (0, '', '') + elif command['prefix'] == 'balancer eval' or command['prefix'] == 'balancer eval-verbose': + verbose = command['prefix'] == 'balancer eval-verbose' + pools = [] + if 'option' in command: + plan = self.plans.get(command['option']) + if not plan: + # not a plan, does it look like a pool? + osdmap = self.get_osdmap() + valid_pool_names = [p['pool_name'] for p in osdmap.dump().get('pools', [])] + option = command['option'] + if option not in valid_pool_names: + return (-errno.EINVAL, '', 'option "%s" not a plan or a pool' % option) + pools.append(option) + ms = MappingState(osdmap, self.get("pg_stats"), self.get("pool_stats"), 'pool "%s"' % option) + else: + pools = plan.pools + ms = plan.final_state() + else: + ms = MappingState(self.get_osdmap(), + self.get("pg_stats"), + self.get("pool_stats"), + 'current cluster') + return (0, self.evaluate(ms, pools, verbose=verbose), '') + elif command['prefix'] == 'balancer optimize': + # The GIL can be release by the active balancer, so disallow when active + if self.active: + return (-errno.EINVAL, '', 'Balancer enabled, disable to optimize manually') + if self.optimizing: + return (-errno.EINVAL, '', 'Balancer finishing up....try again') + pools = [] + if 'pools' in command: + pools = command['pools'] + osdmap = self.get_osdmap() + valid_pool_names = [p['pool_name'] for p in osdmap.dump().get('pools', [])] + invalid_pool_names = [] + for p in pools: + if p not in valid_pool_names: + invalid_pool_names.append(p) + if len(invalid_pool_names): + return (-errno.EINVAL, '', 'pools %s not found' % invalid_pool_names) + plan = self.plan_create(command['plan'], osdmap, pools) + self.last_optimize_started = time.asctime(time.localtime()) + self.optimize_result = self.in_progress_string + start = time.time() + r, detail = self.optimize(plan) + end = time.time() + self.last_optimize_duration = str(datetime.timedelta(seconds=(end - start))) + if r == 0: + # Add plan if an optimization was created + self.optimize_result = self.success_string + self.plans[command['plan']] = plan + else: + self.optimize_result = detail + return (r, '', detail) + elif command['prefix'] == 'balancer rm': + self.plan_rm(command['plan']) + return (0, '', '') + elif command['prefix'] == 'balancer reset': + self.plans = {} + return (0, '', '') + elif command['prefix'] == 'balancer ls': + return (0, json.dumps([p for p in self.plans], indent=4), '') + elif command['prefix'] == 'balancer dump': + plan = self.plans.get(command['plan']) + if not plan: + return (-errno.ENOENT, '', 'plan %s not found' % command['plan']) + return (0, plan.dump(), '') + elif command['prefix'] == 'balancer show': + plan = self.plans.get(command['plan']) + if not plan: + return (-errno.ENOENT, '', 'plan %s not found' % command['plan']) + return (0, plan.show(), '') + elif command['prefix'] == 'balancer execute': + # The GIL can be release by the active balancer, so disallow when active + if self.active: + return (-errno.EINVAL, '', 'Balancer enabled, disable to execute a plan') + if self.optimizing: + return (-errno.EINVAL, '', 'Balancer finishing up....try again') + plan = self.plans.get(command['plan']) + if not plan: + return (-errno.ENOENT, '', 'plan %s not found' % command['plan']) + r, detail = self.execute(plan) + self.plan_rm(command['plan']) + return (r, '', detail) + else: + return (-errno.EINVAL, '', + "Command not found '{0}'".format(command['prefix'])) + + def shutdown(self): + self.log.info('Stopping') + self.run = False + self.event.set() + + def time_permit(self): + local_time = time.localtime() + time_of_day = time.strftime('%H%M', local_time) + weekday = (local_time.tm_wday + 1) % 7 # be compatible with C + permit = False + + begin_time = self.get_module_option('begin_time') + end_time = self.get_module_option('end_time') + if begin_time <= end_time: + permit = begin_time <= time_of_day < end_time + else: + permit = time_of_day >= begin_time or time_of_day < end_time + if not permit: + self.log.debug("should run between %s - %s, now %s, skipping", + begin_time, end_time, time_of_day) + return False + + begin_weekday = self.get_module_option('begin_weekday') + end_weekday = self.get_module_option('end_weekday') + if begin_weekday <= end_weekday: + permit = begin_weekday <= weekday < end_weekday + else: + permit = weekday >= begin_weekday or weekday < end_weekday + if not permit: + self.log.debug("should run between weekday %d - %d, now %d, skipping", + begin_weekday, end_weekday, weekday) + return False + + return True + + def serve(self): + self.log.info('Starting') + while self.run: + self.active = self.get_module_option('active') + sleep_interval = self.get_module_option('sleep_interval') + self.log.debug('Waking up [%s, now %s]', + "active" if self.active else "inactive", + time.strftime(TIME_FORMAT, time.localtime())) + if self.active and self.time_permit(): + self.log.debug('Running') + name = 'auto_%s' % time.strftime(TIME_FORMAT, time.gmtime()) + osdmap = self.get_osdmap() + allow = self.get_module_option('pool_ids') + final = [] + if allow != '': + allow = allow.split(',') + valid = [str(p['pool']) for p in osdmap.dump().get('pools', [])] + final = set(allow) & set(valid) + if set(allow) - set(valid): # some pools were gone, prune + self.set_module_option('pool_ids', ','.join(final)) + pool_name_by_id = dict((p['pool'], p['pool_name']) for p in osdmap.dump().get('pools', [])) + final = [int(p) for p in final] + final = [pool_name_by_id[p] for p in final if p in pool_name_by_id] + plan = self.plan_create(name, osdmap, final) + self.optimizing = True + self.last_optimize_started = time.asctime(time.localtime()) + self.optimize_result = self.in_progress_string + start = time.time() + r, detail = self.optimize(plan) + end = time.time() + self.last_optimize_duration = str(datetime.timedelta(seconds=(end - start))) + if r == 0: + self.optimize_result = self.success_string + self.execute(plan) + else: + self.optimize_result = detail + self.optimizing = False + self.log.debug('Sleeping for %d', sleep_interval) + self.event.wait(sleep_interval) + self.event.clear() + + def plan_create(self, name, osdmap, pools): + plan = Plan(name, + MappingState(osdmap, + self.get("pg_stats"), + self.get("pool_stats"), + 'plan %s initial' % name), + pools) + return plan + + def plan_rm(self, name): + if name in self.plans: + del self.plans[name] + + def calc_eval(self, ms, pools): + pe = Eval(ms) + pool_rule = {} + pool_info = {} + for p in ms.osdmap_dump.get('pools',[]): + if len(pools) and p['pool_name'] not in pools: + continue + # skip dead or not-yet-ready pools too + if p['pool'] not in ms.poolids: + continue + pe.pool_name[p['pool']] = p['pool_name'] + pe.pool_id[p['pool_name']] = p['pool'] + pool_rule[p['pool_name']] = p['crush_rule'] + pe.pool_roots[p['pool_name']] = [] + pool_info[p['pool_name']] = p + if len(pool_info) == 0: + return pe + self.log.debug('pool_name %s' % pe.pool_name) + self.log.debug('pool_id %s' % pe.pool_id) + self.log.debug('pools %s' % pools) + self.log.debug('pool_rule %s' % pool_rule) + + osd_weight = { a['osd']: a['weight'] + for a in ms.osdmap_dump.get('osds',[]) if a['weight'] > 0 } + + # get expected distributions by root + actual_by_root = {} + rootids = ms.crush.find_takes() + roots = [] + for rootid in rootids: + ls = ms.osdmap.get_pools_by_take(rootid) + want = [] + # find out roots associating with pools we are passed in + for candidate in ls: + if candidate in pe.pool_name: + want.append(candidate) + if len(want) == 0: + continue + root = ms.crush.get_item_name(rootid) + pe.root_pools[root] = [] + for poolid in want: + pe.pool_roots[pe.pool_name[poolid]].append(root) + pe.root_pools[root].append(pe.pool_name[poolid]) + pe.root_ids[root] = rootid + roots.append(root) + weight_map = ms.crush.get_take_weight_osd_map(rootid) + adjusted_map = { + osd: cw * osd_weight[osd] + for osd,cw in six.iteritems(weight_map) if osd in osd_weight and cw > 0 + } + sum_w = sum(adjusted_map.values()) + assert len(adjusted_map) == 0 or sum_w > 0 + pe.target_by_root[root] = { osd: w / sum_w + for osd,w in six.iteritems(adjusted_map) } + actual_by_root[root] = { + 'pgs': {}, + 'objects': {}, + 'bytes': {}, + } + for osd in pe.target_by_root[root]: + actual_by_root[root]['pgs'][osd] = 0 + actual_by_root[root]['objects'][osd] = 0 + actual_by_root[root]['bytes'][osd] = 0 + pe.total_by_root[root] = { + 'pgs': 0, + 'objects': 0, + 'bytes': 0, + } + self.log.debug('pool_roots %s' % pe.pool_roots) + self.log.debug('root_pools %s' % pe.root_pools) + self.log.debug('target_by_root %s' % pe.target_by_root) + + # pool and root actual + for pool, pi in six.iteritems(pool_info): + poolid = pi['pool'] + pm = ms.pg_up_by_poolid[poolid] + pgs = 0 + objects = 0 + bytes = 0 + pgs_by_osd = {} + objects_by_osd = {} + bytes_by_osd = {} + for pgid, up in six.iteritems(pm): + for osd in [int(osd) for osd in up]: + if osd == CRUSHMap.ITEM_NONE: + continue + if osd not in pgs_by_osd: + pgs_by_osd[osd] = 0 + objects_by_osd[osd] = 0 + bytes_by_osd[osd] = 0 + pgs_by_osd[osd] += 1 + objects_by_osd[osd] += ms.pg_stat[pgid]['num_objects'] + bytes_by_osd[osd] += ms.pg_stat[pgid]['num_bytes'] + # pick a root to associate this pg instance with. + # note that this is imprecise if the roots have + # overlapping children. + # FIXME: divide bytes by k for EC pools. + for root in pe.pool_roots[pool]: + if osd in pe.target_by_root[root]: + actual_by_root[root]['pgs'][osd] += 1 + actual_by_root[root]['objects'][osd] += ms.pg_stat[pgid]['num_objects'] + actual_by_root[root]['bytes'][osd] += ms.pg_stat[pgid]['num_bytes'] + pgs += 1 + objects += ms.pg_stat[pgid]['num_objects'] + bytes += ms.pg_stat[pgid]['num_bytes'] + pe.total_by_root[root]['pgs'] += 1 + pe.total_by_root[root]['objects'] += ms.pg_stat[pgid]['num_objects'] + pe.total_by_root[root]['bytes'] += ms.pg_stat[pgid]['num_bytes'] + break + pe.count_by_pool[pool] = { + 'pgs': { + k: v + for k, v in six.iteritems(pgs_by_osd) + }, + 'objects': { + k: v + for k, v in six.iteritems(objects_by_osd) + }, + 'bytes': { + k: v + for k, v in six.iteritems(bytes_by_osd) + }, + } + pe.actual_by_pool[pool] = { + 'pgs': { + k: float(v) / float(max(pgs, 1)) + for k, v in six.iteritems(pgs_by_osd) + }, + 'objects': { + k: float(v) / float(max(objects, 1)) + for k, v in six.iteritems(objects_by_osd) + }, + 'bytes': { + k: float(v) / float(max(bytes, 1)) + for k, v in six.iteritems(bytes_by_osd) + }, + } + pe.total_by_pool[pool] = { + 'pgs': pgs, + 'objects': objects, + 'bytes': bytes, + } + for root in pe.total_by_root: + pe.count_by_root[root] = { + 'pgs': { + k: float(v) + for k, v in six.iteritems(actual_by_root[root]['pgs']) + }, + 'objects': { + k: float(v) + for k, v in six.iteritems(actual_by_root[root]['objects']) + }, + 'bytes': { + k: float(v) + for k, v in six.iteritems(actual_by_root[root]['bytes']) + }, + } + pe.actual_by_root[root] = { + 'pgs': { + k: float(v) / float(max(pe.total_by_root[root]['pgs'], 1)) + for k, v in six.iteritems(actual_by_root[root]['pgs']) + }, + 'objects': { + k: float(v) / float(max(pe.total_by_root[root]['objects'], 1)) + for k, v in six.iteritems(actual_by_root[root]['objects']) + }, + 'bytes': { + k: float(v) / float(max(pe.total_by_root[root]['bytes'], 1)) + for k, v in six.iteritems(actual_by_root[root]['bytes']) + }, + } + self.log.debug('actual_by_pool %s' % pe.actual_by_pool) + self.log.debug('actual_by_root %s' % pe.actual_by_root) + + # average and stddev and score + pe.stats_by_root = { + a: pe.calc_stats( + b, + pe.target_by_root[a], + pe.total_by_root[a] + ) for a, b in six.iteritems(pe.count_by_root) + } + self.log.debug('stats_by_root %s' % pe.stats_by_root) + + # the scores are already normalized + pe.score_by_root = { + r: { + 'pgs': pe.stats_by_root[r]['pgs']['score'], + 'objects': pe.stats_by_root[r]['objects']['score'], + 'bytes': pe.stats_by_root[r]['bytes']['score'], + } for r in pe.total_by_root.keys() + } + self.log.debug('score_by_root %s' % pe.score_by_root) + + # get the list of score metrics, comma separated + metrics = self.get_module_option('crush_compat_metrics').split(',') + + # total score is just average of normalized stddevs + pe.score = 0.0 + for r, vs in six.iteritems(pe.score_by_root): + for k, v in six.iteritems(vs): + if k in metrics: + pe.score += v + pe.score /= len(metrics) * len(roots) + return pe + + def evaluate(self, ms, pools, verbose=False): + pe = self.calc_eval(ms, pools) + return pe.show(verbose=verbose) + + def optimize(self, plan): + self.log.info('Optimize plan %s' % plan.name) + plan.mode = self.get_module_option('mode') + max_misplaced = float(self.get_ceph_option('target_max_misplaced_ratio')) + self.log.info('Mode %s, max misplaced %f' % + (plan.mode, max_misplaced)) + + info = self.get('pg_status') + unknown = info.get('unknown_pgs_ratio', 0.0) + degraded = info.get('degraded_ratio', 0.0) + inactive = info.get('inactive_pgs_ratio', 0.0) + misplaced = info.get('misplaced_ratio', 0.0) + self.log.debug('unknown %f degraded %f inactive %f misplaced %g', + unknown, degraded, inactive, misplaced) + if unknown > 0.0: + detail = 'Some PGs (%f) are unknown; try again later' % unknown + self.log.info(detail) + return -errno.EAGAIN, detail + elif degraded > 0.0: + detail = 'Some objects (%f) are degraded; try again later' % degraded + self.log.info(detail) + return -errno.EAGAIN, detail + elif inactive > 0.0: + detail = 'Some PGs (%f) are inactive; try again later' % inactive + self.log.info(detail) + return -errno.EAGAIN, detail + elif misplaced >= max_misplaced: + detail = 'Too many objects (%f > %f) are misplaced; ' \ + 'try again later' % (misplaced, max_misplaced) + self.log.info(detail) + return -errno.EAGAIN, detail + else: + if plan.mode == 'upmap': + return self.do_upmap(plan) + elif plan.mode == 'crush-compat': + return self.do_crush_compat(plan) + elif plan.mode == 'none': + detail = 'Please do "ceph balancer mode" to choose a valid mode first' + self.log.info('Idle') + return -errno.ENOEXEC, detail + else: + detail = 'Unrecognized mode %s' % plan.mode + self.log.info(detail) + return -errno.EINVAL, detail + ## + + def do_upmap(self, plan): + self.log.info('do_upmap') + max_iterations = self.get_module_option('upmap_max_iterations') + max_deviation = self.get_module_option('upmap_max_deviation') + + ms = plan.initial + if len(plan.pools): + pools = plan.pools + else: # all + pools = [str(i['pool_name']) for i in ms.osdmap_dump.get('pools',[])] + if len(pools) == 0: + detail = 'No pools available' + self.log.info(detail) + return -errno.ENOENT, detail + # shuffle pool list so they all get equal (in)attention + random.shuffle(pools) + self.log.info('pools %s' % pools) + + adjusted_pools = [] + inc = plan.inc + total_did = 0 + left = max_iterations + osdmap_dump = self.get_osdmap().dump() + pools_with_pg_merge = [p['pool_name'] for p in osdmap_dump.get('pools', []) + if p['pg_num'] > p['pg_num_target']] + crush_rule_by_pool_name = dict((p['pool_name'], p['crush_rule']) for p in osdmap_dump.get('pools', [])) + for pool in pools: + if pool not in crush_rule_by_pool_name: + self.log.info('pool %s does not exist' % pool) + continue + if pool in pools_with_pg_merge: + self.log.info('pool %s has pending PG(s) for merging, skipping for now' % pool) + continue + adjusted_pools.append(pool) + # shuffle so all pools get equal (in)attention + random.shuffle(adjusted_pools) + for pool in adjusted_pools: + did = ms.osdmap.calc_pg_upmaps(inc, max_deviation, left, [pool]) + total_did += did + left -= did + if left <= 0: + break + self.log.info('prepared %d/%d changes' % (total_did, max_iterations)) + if total_did == 0: + return -errno.EALREADY, 'Unable to find further optimization, ' \ + 'or pool(s) pg_num is decreasing, ' \ + 'or distribution is already perfect' + return 0, '' + + def do_crush_compat(self, plan): + self.log.info('do_crush_compat') + max_iterations = self.get_module_option('crush_compat_max_iterations') + if max_iterations < 1: + return -errno.EINVAL, '"crush_compat_max_iterations" must be >= 1' + step = self.get_module_option('crush_compat_step') + if step <= 0 or step >= 1.0: + return -errno.EINVAL, '"crush_compat_step" must be in (0, 1)' + max_misplaced = float(self.get_ceph_option('target_max_misplaced_ratio')) + min_pg_per_osd = 2 + + ms = plan.initial + osdmap = ms.osdmap + crush = osdmap.get_crush() + pe = self.calc_eval(ms, plan.pools) + min_score_to_optimize = self.get_module_option('min_score') + if pe.score <= min_score_to_optimize: + if pe.score == 0: + detail = 'Distribution is already perfect' + else: + detail = 'score %f <= min_score %f, will not optimize' \ + % (pe.score, min_score_to_optimize) + self.log.info(detail) + return -errno.EALREADY, detail + + # get current osd reweights + orig_osd_weight = { a['osd']: a['weight'] + for a in ms.osdmap_dump.get('osds',[]) } + reweighted_osds = [ a for a,b in six.iteritems(orig_osd_weight) + if b < 1.0 and b > 0.0 ] + + # get current compat weight-set weights + orig_ws = self.get_compat_weight_set_weights(ms) + if not orig_ws: + return -errno.EAGAIN, 'compat weight-set not available' + orig_ws = { a: b for a, b in six.iteritems(orig_ws) if a >= 0 } + + # Make sure roots don't overlap their devices. If so, we + # can't proceed. + roots = list(pe.target_by_root.keys()) + self.log.debug('roots %s', roots) + visited = {} + overlap = {} + root_ids = {} + for root, wm in six.iteritems(pe.target_by_root): + for osd in wm: + if osd in visited: + if osd not in overlap: + overlap[osd] = [ visited[osd] ] + overlap[osd].append(root) + visited[osd] = root + if len(overlap) > 0: + detail = 'Some osds belong to multiple subtrees: %s' % \ + overlap + self.log.error(detail) + return -errno.EOPNOTSUPP, detail + + # rebalance by pgs, objects, or bytes + metrics = self.get_module_option('crush_compat_metrics').split(',') + key = metrics[0] # balancing using the first score metric + if key not in ['pgs', 'bytes', 'objects']: + self.log.warn("Invalid crush_compat balancing key %s. Using 'pgs'." % key) + key = 'pgs' + + # go + best_ws = copy.deepcopy(orig_ws) + best_ow = copy.deepcopy(orig_osd_weight) + best_pe = pe + left = max_iterations + bad_steps = 0 + next_ws = copy.deepcopy(best_ws) + next_ow = copy.deepcopy(best_ow) + while left > 0: + # adjust + self.log.debug('best_ws %s' % best_ws) + random.shuffle(roots) + for root in roots: + pools = best_pe.root_pools[root] + osds = len(best_pe.target_by_root[root]) + min_pgs = osds * min_pg_per_osd + if best_pe.total_by_root[root][key] < min_pgs: + self.log.info('Skipping root %s (pools %s), total pgs %d ' + '< minimum %d (%d per osd)', + root, pools, + best_pe.total_by_root[root][key], + min_pgs, min_pg_per_osd) + continue + self.log.info('Balancing root %s (pools %s) by %s' % + (root, pools, key)) + target = best_pe.target_by_root[root] + actual = best_pe.actual_by_root[root][key] + queue = sorted(actual.keys(), + key=lambda osd: -abs(target[osd] - actual[osd])) + for osd in queue: + if orig_osd_weight[osd] == 0: + self.log.debug('skipping out osd.%d', osd) + else: + deviation = target[osd] - actual[osd] + if deviation == 0: + break + self.log.debug('osd.%d deviation %f', osd, deviation) + weight = best_ws[osd] + ow = orig_osd_weight[osd] + if actual[osd] > 0: + calc_weight = target[osd] / actual[osd] * weight * ow + else: + # for newly created osds, reset calc_weight at target value + # this way weight-set will end up absorbing *step* of its + # target (final) value at the very beginning and slowly catch up later. + # note that if this turns out causing too many misplaced + # pgs, then we'll reduce step and retry + calc_weight = target[osd] + new_weight = weight * (1.0 - step) + calc_weight * step + self.log.debug('Reweight osd.%d %f -> %f', osd, weight, + new_weight) + next_ws[osd] = new_weight + if ow < 1.0: + new_ow = min(1.0, max(step + (1.0 - step) * ow, + ow + .005)) + self.log.debug('Reweight osd.%d reweight %f -> %f', + osd, ow, new_ow) + next_ow[osd] = new_ow + + # normalize weights under this root + root_weight = crush.get_item_weight(pe.root_ids[root]) + root_sum = sum(b for a,b in six.iteritems(next_ws) + if a in target.keys()) + if root_sum > 0 and root_weight > 0: + factor = root_sum / root_weight + self.log.debug('normalizing root %s %d, weight %f, ' + 'ws sum %f, factor %f', + root, pe.root_ids[root], root_weight, + root_sum, factor) + for osd in actual.keys(): + next_ws[osd] = next_ws[osd] / factor + + # recalc + plan.compat_ws = copy.deepcopy(next_ws) + next_ms = plan.final_state() + next_pe = self.calc_eval(next_ms, plan.pools) + next_misplaced = next_ms.calc_misplaced_from(ms) + self.log.debug('Step result score %f -> %f, misplacing %f', + best_pe.score, next_pe.score, next_misplaced) + + if next_misplaced > max_misplaced: + if best_pe.score < pe.score: + self.log.debug('Step misplaced %f > max %f, stopping', + next_misplaced, max_misplaced) + break + step /= 2.0 + next_ws = copy.deepcopy(best_ws) + next_ow = copy.deepcopy(best_ow) + self.log.debug('Step misplaced %f > max %f, reducing step to %f', + next_misplaced, max_misplaced, step) + else: + if next_pe.score > best_pe.score * 1.0001: + bad_steps += 1 + if bad_steps < 5 and random.randint(0, 100) < 70: + self.log.debug('Score got worse, taking another step') + else: + step /= 2.0 + next_ws = copy.deepcopy(best_ws) + next_ow = copy.deepcopy(best_ow) + self.log.debug('Score got worse, trying smaller step %f', + step) + else: + bad_steps = 0 + best_pe = next_pe + best_ws = copy.deepcopy(next_ws) + best_ow = copy.deepcopy(next_ow) + if best_pe.score == 0: + break + left -= 1 + + # allow a small regression if we are phasing out osd weights + fudge = 0 + if best_ow != orig_osd_weight: + fudge = .001 + + if best_pe.score < pe.score + fudge: + self.log.info('Success, score %f -> %f', pe.score, best_pe.score) + plan.compat_ws = best_ws + for osd, w in six.iteritems(best_ow): + if w != orig_osd_weight[osd]: + self.log.debug('osd.%d reweight %f', osd, w) + plan.osd_weights[osd] = w + return 0, '' + else: + self.log.info('Failed to find further optimization, score %f', + pe.score) + plan.compat_ws = {} + return -errno.EDOM, 'Unable to find further optimization, ' \ + 'change balancer mode and retry might help' + + def get_compat_weight_set_weights(self, ms): + if not CRUSHMap.have_default_choose_args(ms.crush_dump): + # enable compat weight-set first + self.log.debug('ceph osd crush weight-set create-compat') + result = CommandResult('') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd crush weight-set create-compat', + 'format': 'json', + }), '') + r, outb, outs = result.wait() + if r != 0: + self.log.error('Error creating compat weight-set') + return + + result = CommandResult('') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd crush dump', + 'format': 'json', + }), '') + r, outb, outs = result.wait() + if r != 0: + self.log.error('Error dumping crush map') + return + try: + crushmap = json.loads(outb) + except: + raise RuntimeError('unable to parse crush map') + else: + crushmap = ms.crush_dump + + raw = CRUSHMap.get_default_choose_args(crushmap) + weight_set = {} + for b in raw: + bucket = None + for t in crushmap['buckets']: + if t['id'] == b['bucket_id']: + bucket = t + break + if not bucket: + raise RuntimeError('could not find bucket %s' % b['bucket_id']) + self.log.debug('bucket items %s' % bucket['items']) + self.log.debug('weight set %s' % b['weight_set'][0]) + if len(bucket['items']) != len(b['weight_set'][0]): + raise RuntimeError('weight-set size does not match bucket items') + for pos in range(len(bucket['items'])): + weight_set[bucket['items'][pos]['id']] = b['weight_set'][0][pos] + + self.log.debug('weight_set weights %s' % weight_set) + return weight_set + + def do_crush(self): + self.log.info('do_crush (not yet implemented)') + + def do_osd_weight(self): + self.log.info('do_osd_weight (not yet implemented)') + + def execute(self, plan): + self.log.info('Executing plan %s' % plan.name) + + commands = [] + + # compat weight-set + if len(plan.compat_ws) and \ + not CRUSHMap.have_default_choose_args(plan.initial.crush_dump): + self.log.debug('ceph osd crush weight-set create-compat') + result = CommandResult('') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd crush weight-set create-compat', + 'format': 'json', + }), '') + r, outb, outs = result.wait() + if r != 0: + self.log.error('Error creating compat weight-set') + return r, outs + + for osd, weight in six.iteritems(plan.compat_ws): + self.log.info('ceph osd crush weight-set reweight-compat osd.%d %f', + osd, weight) + result = CommandResult('') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd crush weight-set reweight-compat', + 'format': 'json', + 'item': 'osd.%d' % osd, + 'weight': [weight], + }), '') + commands.append(result) + + # new_weight + reweightn = {} + for osd, weight in six.iteritems(plan.osd_weights): + reweightn[str(osd)] = str(int(weight * float(0x10000))) + if len(reweightn): + self.log.info('ceph osd reweightn %s', reweightn) + result = CommandResult('') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd reweightn', + 'format': 'json', + 'weights': json.dumps(reweightn), + }), '') + commands.append(result) + + # upmap + incdump = plan.inc.dump() + for pgid in incdump.get('old_pg_upmap_items', []): + self.log.info('ceph osd rm-pg-upmap-items %s', pgid) + result = CommandResult('foo') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd rm-pg-upmap-items', + 'format': 'json', + 'pgid': pgid, + }), 'foo') + commands.append(result) + + for item in incdump.get('new_pg_upmap_items', []): + self.log.info('ceph osd pg-upmap-items %s mappings %s', item['pgid'], + item['mappings']) + osdlist = [] + for m in item['mappings']: + osdlist += [m['from'], m['to']] + result = CommandResult('foo') + self.send_command(result, 'mon', '', json.dumps({ + 'prefix': 'osd pg-upmap-items', + 'format': 'json', + 'pgid': item['pgid'], + 'id': osdlist, + }), 'foo') + commands.append(result) + + # wait for commands + self.log.debug('commands %s' % commands) + for result in commands: + r, outb, outs = result.wait() + if r != 0: + self.log.error('execute error: r = %d, detail = %s' % (r, outs)) + return r, outs + self.log.debug('done') + return 0, '' + + def gather_telemetry(self): + return { + 'active': self.active, + 'mode': self.mode, + } -- cgit v1.2.3