from typing import (Dict, Iterator, Generic, List, Optional, Set, Tuple, TypeVar, Union) import collections import itertools import numpy as np import pulp T = TypeVar('T') class Expr(Generic[T]): def quorums(self) -> Iterator[Set[T]]: raise NotImplementedError def is_quorum(self, xs: Set[T]) -> bool: raise NotImplementedError def dual(self) -> 'Expr[T]': raise NotImplementedError def __add__(self, rhs: 'Expr[T]') -> 'Expr[T]': return _or(self, rhs) def __mul__(self, rhs: 'Expr[T]') -> 'Expr[T]': return _and(self, rhs) class Node(Expr[T]): def __init__(self, x: T) -> None: self.x = x def __str__(self) -> str: return str(self.x) def __repr__(self) -> str: return f'Node({self.x})' def quorums(self) -> Iterator[Set[T]]: yield {self.x} def is_quorum(self, xs: Set[T]) -> bool: return self.x in xs def dual(self) -> Expr: return self class Or(Expr[T]): def __init__(self, es: List[Expr[T]]) -> None: if len(es) == 0: raise ValueError(f'Or cannot be constructed with an empty list') self.es = es def __str__(self) -> str: return '(' + ' + '.join(str(e) for e in self.es) + ')' def __repr__(self) -> str: return f'Or({self.es})' def quorums(self) -> Iterator[Set[T]]: for e in self.es: yield from e.quorums() def is_quorum(self, xs: Set[T]) -> bool: return any(e.is_quorum(xs) for e in self.es) def dual(self) -> Expr: return And([e.dual() for e in self.es]) class And(Expr[T]): def __init__(self, es: List[Expr[T]]) -> None: if len(es) == 0: raise ValueError(f'And cannot be constructed with an empty list') self.es = es def __str__(self) -> str: return '(' + ' * '.join(str(e) for e in self.es) + ')' def __repr__(self) -> str: return f'And({self.es})' def quorums(self) -> Iterator[Set[T]]: for subquorums in itertools.product(*[e.quorums() for e in self.es]): yield set.union(*subquorums) def is_quorum(self, xs: Set[T]) -> bool: return all(e.is_quorum(xs) for e in self.es) def dual(self) -> Expr: return Or([e.dual() for e in self.es]) class Choose(Expr[T]): def __init__(self, k: int, es: List[Expr[T]]) -> None: if k <= 0 or k > len(es): raise ValueError(f'k must be in the range [1, {len(es)}]') self.k = k self.es = es def __str__(self) -> str: return f'choose{self.k}(' + ', '.join(str(e) for e in self.es) + ')' def __repr__(self) -> str: return f'Chose({self.k}, {self.es})' def quorums(self) -> Iterator[Set[T]]: for combo in itertools.combinations(self.es, self.k): for subquorums in itertools.product(*[e.quorums() for e in combo]): yield set.union(*subquorums) def is_quorum(self, xs: Set[T]) -> bool: return sum(1 if e.is_quorum(xs) else 0 for e in self.es) >= self.k def dual(self) -> Expr: # TODO(mwhittaker): Prove that this is in fact the dual. return Choose(len(self.es) - self.k + 1, [e.dual() for e in self.es]) def _and(lhs: Expr[T], rhs: Expr[T]) -> 'And[T]': if isinstance(lhs, And) and isinstance(rhs, And): return And(lhs.es + rhs.es) elif isinstance(lhs, And): return And(lhs.es + [rhs]) elif isinstance(rhs, And): return And([lhs] + rhs.es) else: return And([lhs, rhs]) def _or(lhs: Expr[T], rhs: Expr[T]) -> 'Or[T]': if isinstance(lhs, Or) and isinstance(rhs, Or): return Or(lhs.es + rhs.es) elif isinstance(lhs, Or): return Or(lhs.es + [rhs]) elif isinstance(rhs, Or): return Or([lhs] + rhs.es) else: return Or([lhs, rhs]) def choose(k: int, es: List[Expr[T]]) -> Expr[T]: if k == 1: return Or(es) elif k == len(es): return And(es) else: return Choose(k, es) def majority(es: List[Expr[T]]) -> Expr[T]: return choose(len(es) // 2 + 1, es) Distribution = Union[int, float, Dict[float, float], List[Tuple[float, float]]] def _canonicalize_distribution(d: Distribution) -> Dict[float, float]: if isinstance(d, int): if d < 0 or d > 1: raise ValueError('distribution must be in the range [0, 1]') return {float(d): 1.} elif isinstance(d, float): if d < 0 or d > 1: raise ValueError('distribution must be in the range [0, 1]') return {d: 1.} elif isinstance(d, dict): if len(d) == 0: raise ValueError('distribution cannot empty') if any(weight < 0 for weight in d.values()): raise ValueError('distribution cannot have negative weights') total_weight = sum(d.values()) if total_weight == 0: raise ValueError('distribution cannot have zero weight') return {float(f): weight / total_weight for (f, weight) in d.items() if weight > 0} elif isinstance(d, list): return _canonicalize_distribution({f: weight for (f, weight) in d}) else: raise ValueError('distribution must be an int, a float, a Dict[float, ' 'float] or a List[Tuple[float, float]]') class QuorumSystem(Generic[T]): def __init__(self, reads: Optional[Expr[T]] = None, writes: Optional[Expr[T]] = None) -> None: if reads is not None and writes is not None: # TODO(mwhittaker): Think of ways to make this more efficient. assert all(len(r & w) > 0 for (r, w) in itertools.product(reads.quorums(), writes.quorums())) self.reads = reads self.writes = writes elif reads is not None and writes is None: self.reads = reads self.writes = reads.dual() elif reads is None and writes is not None: self.reads = writes.dual() self.writes = writes else: raise ValueError('A QuorumSystem must be instantiated with a set ' 'of read quorums or a set of write quorums') def __repr__(self) -> str: return f'QuorumSystem(reads={self.reads}, writes={self.writes})' def strategy(self, read_fraction: Distribution) -> 'Strategy[T]': # TODO(mwhittaker): Allow read_fraction or write_fraction. # TODO(mwhittaker): Implement independent strategy. return self._load_optimal_strategy( _canonicalize_distribution(read_fraction)) def is_read_quorum(self, xs: Set[T]) -> bool: return self.reads.is_quorum(xs) def read_quorums(self) -> Iterator[Set[T]]: return self.reads.quorums() def write_quorums(self) -> Iterator[Set[T]]: return self.writes.quorums() def _load_optimal_strategy(self, read_fraction: Dict[float, float]) -> \ 'Strategy[T]': fr = sum(f * weight for (f, weight) in read_fraction.items()) reads = list(self.read_quorums()) writes = list(self.write_quorums()) read_load: Dict[T, List[pulp.LpVariable]] = collections.defaultdict(list) read_weights: List[pulp.LpVariable] = [] for (i, r) in enumerate(reads): v = pulp.LpVariable(f'r{i}', 0, 1) read_weights.append(v) for node in r: read_load[node].append(v) write_load: Dict[T, List[pulp.LpVariable]] = collections.defaultdict(list) write_weights: List[pulp.LpVariable] = [] for (i, r) in enumerate(writes): v = pulp.LpVariable(f'w{i}', 0, 1) write_weights.append(v) for node in r: write_load[node].append(v) # Form the linear program to find the load. problem = pulp.LpProblem("load", pulp.LpMinimize) # If we're trying to balance the strategy, then we want to minimize the # pairwise absolute differences between the read probabilities and the # write probabilities. l = pulp.LpVariable('l', 0, 1) problem += l problem += (sum(read_weights) == 1, 'valid read strategy') problem += (sum(write_weights) == 1, 'valid write strategy') for node in read_load.keys() | write_load.keys(): node_load: pulp.LpAffineExpression = 0 if node in read_load: node_load += fr * sum(read_load[node]) if node in write_load: node_load += (1 - fr) * sum(write_load[node]) problem += (node_load <= l, node) # print(problem) problem.solve(pulp.apis.PULP_CBC_CMD(msg=False)) return ExplicitStrategy(reads, [v.varValue for v in read_weights], writes, [v.varValue for v in write_weights]) # for v in read_weights + write_weights: # print(f'{v.name} = {v.varValue}') # return l.varValue class Strategy(Generic[T]): def load(self, read_fraction: Distribution) -> float: raise NotImplementedError def get_read_quorum(self) -> Set[T]: raise NotImplementedError def get_write_quorum(self) -> Set[T]: raise NotImplementedError class ExplicitStrategy(Strategy[T]): def __init__(self, reads: List[Set[T]], read_weights: List[float], writes: List[Set[T]], write_weights: List[float]) -> None: self.reads = reads self.read_weights = read_weights self.writes = writes self.write_weights = write_weights def __str__(self) -> str: non_zero_reads = {tuple(r): p for (r, p) in zip(self.reads, self.read_weights) if p > 0} non_zero_writes = {tuple(w): p for (w, p) in zip(self.writes, self.write_weights) if p > 0} return (f'ExplicitStrategy(reads={non_zero_reads}, ' + f'writes={non_zero_writes})') def __repr__(self) -> str: return (f'ExplicitStrategy(reads={self.reads}, ' + f'read_weights={self.read_weights},' + f'writes={self.writes}, ' + f'write_weights={self.write_weights})') # TODO(mwhittaker): Implement __str__ and __repr__. def load(self, read_fraction: Distribution) -> float: d = _canonicalize_distribution(read_fraction) fr = sum(f * weight for (f, weight) in d.items()) read_load: Dict[T, float] = collections.defaultdict(float) for (r, p) in zip(self.reads, self.read_weights): for node in r: read_load[node] += p write_load: Dict[T, float] = collections.defaultdict(float) for (w, p) in zip(self.writes, self.write_weights): for node in w: write_load[node] += p node_loads: List[float] = [] for node in read_load.keys() | write_load.keys(): node_load = 0.0 if node in read_load: node_load += fr * read_load[node] if node in write_load: node_load += (1 - fr) * write_load[node] node_loads.append(node_load) return max(node_loads) def get_read_quorum(self) -> Set[T]: return np.random.choice(self.reads, p=self.read_weights) def get_write_quorum(self) -> Set[T]: return np.random.choice(self.writes, p=self.write_weights) a = Node('a') b = Node('b') c = Node('c') d = Node('d') e = Node('e') f = Node('f') g = Node('g') h = Node('h') i = Node('i') # grid = QuorumSystem(reads=a*b*c + d*e*f + g*h*i) # sigma = grid.strategy(0.1) # print(grid) # print(sigma) wpaxos = QuorumSystem(reads=majority([majority([a, b, c]), majority([d, e, f]), majority([g, h, i])])) sigma_1 = wpaxos.strategy(read_fraction=0.1) sigma_5 = wpaxos.strategy(read_fraction=0.5) sigma_9 = wpaxos.strategy(read_fraction=0.9) sigma_even = wpaxos.strategy(read_fraction={0.1: 2, 0.5: 2, 0.9: 1}) for sigma in [sigma_1, sigma_5, sigma_9, sigma_even]: frs = [0.1, 0.5, 0.9, {0.1: 2, 0.5: 2, 0.9: 1}] print([sigma.load(fr) for fr in frs]) # - num_quorums # - has dups? # - optimal schedule # - independent schedule # - node read and write throughputs