+++ /dev/null
-// -*- mode:C++; tab-width:8; c-basic-offset:2; indent-tabs-mode:t -*-
-// vim: ts=8 sw=2 smarttab
-
-#include "gtest/gtest.h"
-#include "common/PrioritizedQueue.h"
-
-#include <numeric>
-#include <vector>
-#include <algorithm>
-
-using std::vector;
-
-class PrioritizedQueueTest : public testing::Test
-{
-protected:
- typedef int Klass;
- typedef unsigned Item;
- typedef PrioritizedQueue<Item, Klass> PQ;
- enum { item_size = 100, };
- vector<Item> items;
-
- void SetUp() override {
- for (int i = 0; i < item_size; i++) {
- items.push_back(Item(i));
- }
- std::random_shuffle(items.begin(), items.end());
- }
- void TearDown() override {
- items.clear();
- }
-};
-
-TEST_F(PrioritizedQueueTest, capacity) {
- const unsigned min_cost = 10;
- const unsigned max_tokens_per_subqueue = 50;
- PQ pq(max_tokens_per_subqueue, min_cost);
- EXPECT_TRUE(pq.empty());
- EXPECT_EQ(0u, pq.length());
-
- pq.enqueue_strict(Klass(1), 0, Item(0));
- EXPECT_FALSE(pq.empty());
- EXPECT_EQ(1u, pq.length());
-
- for (int i = 0; i < 3; i++) {
- pq.enqueue(Klass(1), 0, 10, Item(0));
- }
- for (unsigned i = 4; i > 0; i--) {
- EXPECT_FALSE(pq.empty());
- EXPECT_EQ(i, pq.length());
- pq.dequeue();
- }
- EXPECT_TRUE(pq.empty());
- EXPECT_EQ(0u, pq.length());
-}
-
-TEST_F(PrioritizedQueueTest, strict_pq) {
- const unsigned min_cost = 1;
- const unsigned max_tokens_per_subqueue = 50;
- PQ pq(max_tokens_per_subqueue, min_cost);
- // 0 .. item_size-1
- for (unsigned i = 0; i < item_size; i++) {
- unsigned priority = items[i];
- pq.enqueue_strict(Klass(0), priority, items[i]);
- }
- // item_size-1 .. 0
- for (unsigned i = item_size; i > 0; i--) {
- Item item = pq.dequeue();
- unsigned priority = item;
- EXPECT_EQ(i - 1, priority);
- }
-}
-
-TEST_F(PrioritizedQueueTest, lowest_among_eligible_otherwise_highest) {
- // to minimize the effect of `distribute_tokens()`
- // all eligible items will be assigned with cost of min_cost
- const unsigned min_cost = 0;
- const unsigned max_tokens_per_subqueue = 100;
- PQ pq(max_tokens_per_subqueue, min_cost);
-
-#define ITEM_TO_COST(item_) (item_ % 5 ? min_cost : max_tokens_per_subqueue)
- unsigned num_low_cost = 0, num_high_cost = 0;
- for (int i = 0; i < item_size; i++) {
- const Item& item = items[i];
- unsigned cost = ITEM_TO_COST(item);
- unsigned priority = item;
- if (cost == min_cost) {
- num_low_cost++;
- } else {
- num_high_cost++;
- }
- pq.enqueue(Klass(0), priority, cost, item);
- }
- // the token in all buckets is 0 at the beginning, so dequeue() should pick
- // the first one with the highest priority.
- unsigned highest_priority;
- {
- Item item = pq.dequeue();
- unsigned cost = ITEM_TO_COST(item);
- unsigned priority = item;
- if (cost == min_cost) {
- num_low_cost--;
- } else {
- num_high_cost--;
- }
- EXPECT_EQ(item_size - 1u, priority);
- highest_priority = priority;
- }
- unsigned lowest_priority = 0;
- for (unsigned i = 0; i < num_low_cost; i++) {
- Item item = pq.dequeue();
- unsigned cost = ITEM_TO_COST(item);
- unsigned priority = item;
- EXPECT_EQ(min_cost, cost);
- EXPECT_GT(priority, lowest_priority);
- lowest_priority = priority;
- }
- for (unsigned i = 0; i < num_high_cost; i++) {
- Item item = pq.dequeue();
- unsigned cost = ITEM_TO_COST(item);
- unsigned priority = item;
- EXPECT_EQ(max_tokens_per_subqueue, cost);
- EXPECT_LT(priority, highest_priority);
- highest_priority = priority;
- }
-#undef ITEM_TO_COST
-}
-
-static const unsigned num_classes = 4;
-// just a determinitic number
-#define ITEM_TO_CLASS(item_) Klass((item_ + 43) % num_classes)
-
-TEST_F(PrioritizedQueueTest, fairness_by_class) {
- // dequeue should be fair to all classes in a certain bucket
- const unsigned min_cost = 1;
- const unsigned max_tokens_per_subqueue = 50;
- PQ pq(max_tokens_per_subqueue, min_cost);
-
- for (int i = 0; i < item_size; i++) {
- const Item& item = items[i];
- Klass k = ITEM_TO_CLASS(item);
- unsigned priority = 0;
- unsigned cost = 1;
- pq.enqueue(k, priority, cost, item);
- }
- // just sample first 1/2 of the items
- // if i pick too small a dataset, the result won't be statisitcally
- // significant. if the sample dataset is too large, it will converge to the
- // distribution of the full set.
- vector<unsigned> num_picked_in_class(num_classes, 0u);
- for (int i = 0; i < item_size / 2; i++) {
- Item item = pq.dequeue();
- Klass k = ITEM_TO_CLASS(item);
- num_picked_in_class[k]++;
- }
- unsigned total = std::accumulate(num_picked_in_class.begin(),
- num_picked_in_class.end(),
- 0);
- float avg = float(total) / num_classes;
- for (unsigned i = 0; i < num_classes; i++) {
- EXPECT_NEAR(avg, num_picked_in_class[i], 0.5);
- }
-}
-
-
-TEST_F(PrioritizedQueueTest, remove_by_class) {
- const unsigned min_cost = 1;
- const unsigned max_tokens_per_subqueue = 50;
- PQ pq(max_tokens_per_subqueue, min_cost);
- const Klass class_to_remove(2);
- unsigned num_to_remove = 0;
- for (int i = 0; i < item_size; i++) {
- const Item& item = items[i];
- Klass k = ITEM_TO_CLASS(item);
- pq.enqueue(k, 0, 0, item);
- if (k == class_to_remove) {
- num_to_remove++;
- }
- }
- std::list<Item> removed;
- pq.remove_by_class(class_to_remove, &removed);
-
- // see if the removed items are expected ones.
- for (std::list<Item>::iterator it = removed.begin();
- it != removed.end();
- ++it) {
- const Item& item = *it;
- Klass k = ITEM_TO_CLASS(item);
- EXPECT_EQ(class_to_remove, k);
- items.erase(remove(items.begin(), items.end(), item), items.end());
- }
- EXPECT_EQ(num_to_remove, removed.size());
- EXPECT_EQ(item_size - num_to_remove, pq.length());
- EXPECT_EQ(item_size - num_to_remove, items.size());
- // see if the remainder are expeceted also.
- while (!pq.empty()) {
- const Item item = pq.dequeue();
- Klass k = ITEM_TO_CLASS(item);
- EXPECT_NE(class_to_remove, k);
- items.erase(remove(items.begin(), items.end(), item), items.end());
- }
- EXPECT_TRUE(items.empty());
-}
Code Review / stor4nfv.git / blobdiff