feat(hotspot): new algorithm of hotspot detection

src/server/info_collector.cpp

@@ -77,6 +77,10 @@ info_collector::info_collector()
                                               "storage_size_fetch_interval_seconds",
                                               3600, // default value 1h
                                               "storage size fetch interval seconds");
+    _hotspot_detect_algorithm = dsn_config_get_value_string("pegasus.collector",
+                                                            "hotspot_detect_algorithm",
+                                                            "hotspot_algo_qps_variance",
+                                                            "hotspot_detect_algorithm");
     // _storage_size_retry_wait_seconds is in range of [1, 60]
     _storage_size_retry_wait_seconds =
         std::min(60u, std::max(1u, _storage_size_fetch_interval_seconds / 10));
@@ -148,6 +152,9 @@ void info_collector::on_app_stat()
         // hotspot_calculator is to detect hotspots
         hotspot_calculator *hotspot_calculator =
             get_hotspot_calculator(app_rows.first, app_rows.second.size());
+        if (!hotspot_calculator) {
+            continue;
+        }
         hotspot_calculator->aggregate(app_rows.second);
         // new policy can be designed by strategy pattern in hotspot_partition_data.h
         hotspot_calculator->start_alg();
@@ -285,9 +292,20 @@ hotspot_calculator *info_collector::get_hotspot_calculator(const std::string &ap
     if (iter != _hotspot_calculator_store.end()) {
         return iter->second;
     }
-    hotspot_calculator *calculator_address = new hotspot_calculator(app_name, partition_num);
-    _hotspot_calculator_store[app_name] = calculator_address;
-    return calculator_address;
+    std::unique_ptr<hotspot_policy> policy;
+    if (_hotspot_detect_algorithm == "hotspot_algo_qps_variance") {
+        policy.reset(new hotspot_algo_qps_variance());
+    } else if (_hotspot_detect_algorithm == "hotspot_algo_qps_skew") {
+        policy.reset(new hotspot_algo_qps_skew());
+    } else {
+        dwarn("hotspot detection is disabled");
+        _hotspot_calculator_store[app_name] = nullptr;
+        return nullptr;
+    }
+    hotspot_calculator *calculator =
+        new hotspot_calculator(app_name, partition_num, std::move(policy));
+    _hotspot_calculator_store[app_name] = calculator;
+    return calculator;
 }
 
 } // namespace server

src/server/info_collector.h

@@ -132,6 +132,7 @@ class info_collector
     uint32_t _storage_size_fetch_interval_seconds;
     uint32_t _storage_size_retry_wait_seconds;
     uint32_t _storage_size_retry_max_count;
+    std::string _hotspot_detect_algorithm;
     ::dsn::task_ptr _storage_size_stat_timer_task;
     ::dsn::utils::ex_lock_nr _capacity_unit_update_info_lock;
     // mapping 'node address' --> 'last updated timestamp'

src/server/table_hotspot_policy.h

@@ -8,6 +8,8 @@
 
 #include <algorithm>
 #include <gtest/gtest_prod.h>
+#include <math.h>
+
 #include <dsn/perf_counter/perf_counter.h>
 
 namespace pegasus {
@@ -20,24 +22,71 @@ class hotspot_policy
     // vector is used to save the partitions' data of this app
     // hotspot_partition_data is used to save data of one partition
     virtual void analysis(const std::queue<std::vector<hotspot_partition_data>> &hotspot_app_data,
-                          std::vector<::dsn::perf_counter_wrapper> &hot_points) = 0;
+                          std::vector<::dsn::perf_counter_wrapper> &perf_counters) = 0;
 };
 
 class hotspot_algo_qps_skew : public hotspot_policy
 {
 public:
     void analysis(const std::queue<std::vector<hotspot_partition_data>> &hotspot_app_data,
-                  std::vector<::dsn::perf_counter_wrapper> &hot_points)
+                  std::vector<::dsn::perf_counter_wrapper> &perf_counters)
     {
         const auto &anly_data = hotspot_app_data.back();
         double min_total_qps = INT_MAX;
         for (auto partition_anly_data : anly_data) {
             min_total_qps = std::min(min_total_qps, partition_anly_data.total_qps);
         }
         min_total_qps = std::max(1.0, min_total_qps);
-        dassert(anly_data.size() == hot_points.size(), "partition counts error, please check");
-        for (int i = 0; i < hot_points.size(); i++) {
-            hot_points[i]->set(anly_data[i].total_qps / min_total_qps);
+        dassert(anly_data.size() == perf_counters.size(), "partition counts error, please check");
+        for (int i = 0; i < perf_counters.size(); i++) {
+            perf_counters[i]->set(anly_data[i].total_qps / min_total_qps);
+        }
+    }
+};
+
+// PauTa Criterion
+class hotspot_algo_qps_variance : public hotspot_policy
+{
+public:
+    void analysis(const std::queue<std::vector<hotspot_partition_data>> &hotspot_app_data,
+                  std::vector<::dsn::perf_counter_wrapper> &perf_counters)
+    {
+        dassert(hotspot_app_data.back().size() == perf_counters.size(),
+                "partition counts error, please check");
+        std::vector<double> data_samples;
+        data_samples.reserve(hotspot_app_data.size() * perf_counters.size());
+        auto temp_data = hotspot_app_data;
+        double total = 0, sd = 0, avg = 0;
+        int sample_count = 0;
+        // avg: Average number
+        // sd: Standard deviation
+        // sample_count: Number of samples
+        while (!temp_data.empty()) {
+            for (auto partition_data : temp_data.front()) {
+                if (partition_data.total_qps - 1.00 > 0) {
+                    data_samples.push_back(partition_data.total_qps);
+                    total += partition_data.total_qps;
+                    sample_count++;
+                }
+            }
+            temp_data.pop();
+        }
+        if (sample_count == 0) {
+            ddebug("hotspot_app_data size == 0");
+            return;
+        }
+        avg = total / sample_count;
+        for (auto data_sample : data_samples) {
+            sd += pow((data_sample - avg), 2);
+        }
+        sd = sqrt(sd / sample_count);
+        const auto &anly_data = hotspot_app_data.back();
+        for (int i = 0; i < perf_counters.size(); i++) {
+            double hot_point = (anly_data[i].total_qps - avg) / sd;
+            // perf_counter->set can only be unsigned __int64
+            // use ceil to guarantee conversion results
+            hot_point = ceil(std::max(hot_point, double(0)));
+            perf_counters[i]->set(hot_point);
         }
     }
 };
@@ -46,8 +95,10 @@ class hotspot_algo_qps_skew : public hotspot_policy
 class hotspot_calculator
 {
 public:
-    hotspot_calculator(const std::string &app_name, const int partition_num)
-        : _app_name(app_name), _points(partition_num), _policy(new hotspot_algo_qps_skew())
+    hotspot_calculator(const std::string &app_name,
+                       const int partition_num,
+                       std::unique_ptr<hotspot_policy> policy)
+        : _app_name(app_name), _points(partition_num), _policy(std::move(policy))
     {
         init_perf_counter(partition_num);
     }
@@ -62,6 +113,7 @@ class hotspot_calculator
     std::unique_ptr<hotspot_policy> _policy;
     static const int kMaxQueueSize = 100;
 
+    FRIEND_TEST(table_hotspot_policy, hotspot_algo_qps_variance);
     FRIEND_TEST(table_hotspot_policy, hotspot_algo_qps_skew);
 };
 } // namespace server

src/server/test/pegasus_tablehotspot_test.cpp

@@ -14,7 +14,8 @@ TEST(table_hotspot_policy, hotspot_algo_qps_skew)
     std::vector<row_data> test_rows(2);
     test_rows[0].get_qps = 1234.0;
     test_rows[1].get_qps = 4321.0;
-    hotspot_calculator test_hotspot_calculator("TEST", 2);
+    std::unique_ptr<hotspot_policy> policy(new hotspot_algo_qps_skew());
+    hotspot_calculator test_hotspot_calculator("TEST", 2, std::move(policy));
     test_hotspot_calculator.aggregate(test_rows);
     test_hotspot_calculator.start_alg();
     std::vector<double> result(2);
@@ -25,5 +26,28 @@ TEST(table_hotspot_policy, hotspot_algo_qps_skew)
     ASSERT_EQ(expect_vector, result);
 }
 
+TEST(table_hotspot_policy, hotspot_algo_qps_variance)
+{
+    std::vector<row_data> test_rows(8);
+    test_rows[0].get_qps = 1000.0;
+    test_rows[1].get_qps = 1000.0;
+    test_rows[2].get_qps = 1000.0;
+    test_rows[3].get_qps = 1000.0;
+    test_rows[4].get_qps = 1000.0;
+    test_rows[5].get_qps = 1000.0;
+    test_rows[6].get_qps = 1000.0;
+    test_rows[7].get_qps = 5000.0;
+    std::unique_ptr<hotspot_policy> policy(new hotspot_algo_qps_variance());
+    hotspot_calculator test_hotspot_calculator("TEST", 8, std::move(policy));
+    test_hotspot_calculator.aggregate(test_rows);
+    test_hotspot_calculator.start_alg();
+    std::vector<double> result(8);
+    for (int i = 0; i < test_hotspot_calculator._points.size(); i++) {
+        result[i] = test_hotspot_calculator._points[i]->get_value();
+    }
+    std::vector<double> expect_vector{0, 0, 0, 0, 0, 0, 0, 3};
+    ASSERT_EQ(expect_vector, result);
+}
+
 } // namespace server
 } // namespace pegasus