add paper

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "paper"]
+	path = paper
+	url = https://github.com/sunyinqi0508/AQueryPaper

paper

@@ -0,0 +1 @@
+Subproject commit fa4e3f5a0606b2dda75faaacfb66cdaf42153260

rfdata_preproc.py

@@ -26,6 +26,7 @@ def process(f : str):
     with open(filename, 'rb') as ifile:
         icontents = ifile.read()
         with open(ofilename, 'wb') as ofile:
+            ofile.write(b'\n')
             for l in icontents.splitlines():
                 fields = l.strip().split(b' ')
                 subfields = fields[:-1]

sdk/irf.cpp

@@ -1,22 +1,26 @@
 #include "DecisionTree.h"
+#include "RF.h"
+
 // __AQ_NO_SESSION__
 #include "../server/table.h"
 #include "aquery.h"
 
 DecisionTree *dt = nullptr;
+RandomForest *rf = nullptr;
 
 __AQEXPORT__(bool)
-newtree(int height, long f, ColRef<int> sparse, double forget, long maxf, long noclasses, Evaluation e, long r, long rb)
+newtree(int height, long f, ColRef<int> X, double forget, long maxf, long noclasses, Evaluation e, long r, long rb)
 {
-	if (sparse.size != f)
+	if (X.size != f)
 		return false;
-	int *issparse = (int *)malloc(f * sizeof(int));
-	for (long i = 0; i < f; i++)
-		issparse[i] = sparse.container[i];
+	int *X_cpy = (int *)malloc(f * sizeof(int));
+	
+	memcpy(X_cpy, X.container, f);
 
 	if (maxf < 0)
 		maxf = f;
-	dt = new DecisionTree(f, issparse, forget, maxf, noclasses, e);
+	dt = new DecisionTree(f, X_cpy, forget, maxf, noclasses, e);
+	rf = new RandomForest(height, f, X_cpy, forget, noclasses, e)
 	return true;
 }
 
@@ -44,7 +48,8 @@ fit(vector_type<vector_type<double>> v, vector_type<long> res)
 	double **data = (double **)malloc(v.size * sizeof(double *));
 	for (int i = 0; i < v.size; ++i)
 		data[i] = v.container[i].container;
-	dt->fit(data, res.container, v.size);
+	// dt->fit(data, res.container, v.size);
+	rf->fit(data, res.container, v.size);
 	return true;
 }
 
@@ -54,8 +59,8 @@ predict(vector_type<vector_type<double>> v)
 	int *result = (int *)malloc(v.size * sizeof(int));
 
 	for (long i = 0; i < v.size; i++)
-		result[i] = dt->Test(v.container[i].container, dt->DTree);
-
+		//result[i] = dt->Test(v.container[i].container, dt->DTree);
+		result[i] = rf->Test(v.container, rf->DTrees);
 	auto container = (vector_type<int> *)malloc(sizeof(vector_type<int>));
 	container->size = v.size;
 	container->capacity = 0;

server/libaquery.cpp

@@ -286,10 +286,10 @@ class A{
 	std::chrono::high_resolution_clock::time_point tp;
 	A(){
 		tp = std::chrono::high_resolution_clock::now();
-		printf("A %llx created.\n", tp.time_since_epoch().count());
+		printf("A %llu created.\n", tp.time_since_epoch().count());
 	}
 	~A() {
-		printf("A %llx died after %lldns.\n", tp.time_since_epoch().count(),
+		printf("A %llu died after %lldns.\n", tp.time_since_epoch().count(),
 		 (std::chrono::high_resolution_clock::now() - tp).count());
 	}
 };

server/mariadb_conn.h

@@ -6,17 +6,17 @@
 struct Context;
 
 struct Server{
-    MYSQL *server = 0;
-    Context *cxt = 0;
-    bool status = 0;
+    MYSQL *server = nullptr;
+    Context *cxt = nullptr;
+    bool status = false;
     bool has_error = false;
-    char* query = 0;
+    char* query = nullptr;
     int type = 0;
     
     void connect(Context* cxt, const char* host = "bill.local",
         const char* user = "root", const char* passwd = "0508", 
         const char* db_name = "db", const unsigned int port = 3306, 
-        const char* unix_socket = 0, const unsigned long client_flag = 0
+        const char* unix_socket = nullptr, const unsigned long client_flag = 0
     );
     void exec(const char* q);
     void close();

server/monetdb_conn.cpp

@@ -18,8 +18,12 @@
     #include <atomic>
 #endif // _WIN32
 
+#ifdef ERROR
     #undef ERROR
+#endif
+#ifdef static_assert
     #undef static_assert
+#endif
 
 constexpr const char* monetdbe_type_str[] = {
 	"monetdbe_bool", "monetdbe_int8_t", "monetdbe_int16_t", "monetdbe_int32_t", "monetdbe_int64_t",
@@ -120,7 +124,7 @@ void Server::exec(const char* q){
     auto _res = static_cast<monetdbe_result*>(this->res);
     monetdbe_cnt _cnt = 0;
     auto qresult = monetdbe_query(*server, const_cast<char*>(q), &_res, &_cnt);
-    if (_res != 0){
+    if (_res != nullptr){
         this->cnt = _res->nrows;
         this->res = _res;
     }
@@ -162,6 +166,8 @@ void Server::print_results(const char* sep, const char* end){
             col_data[i] = static_cast<char *>(cols[i]->data);
             szs [i] = monetdbe_type_szs[cols[i]->type];
             header_string = header_string + cols[i]->name + sep + '|' + sep;
+            if (err_msg) [[unlikely]]
+                puts(err_msg);
         }
 		if (const size_t l_sep = strlen(sep) + 1; header_string.size() >= l_sep)
 			header_string.resize(header_string.size() - l_sep);
@@ -183,7 +189,7 @@ void Server::print_results(const char* sep, const char* end){
 void Server::close(){
     if(this->server){
         auto server = static_cast<monetdbe_database*>(this->server);
-        monetdbe_close(*(server));
+        monetdbe_close(*server);
         free(server);
         this->server = nullptr;
     }

server/monetdb_conn.h

@@ -4,18 +4,18 @@
 struct Context;
 
 struct Server{
-    void *server = 0;
-    Context *cxt = 0;
-    bool status = 0;
-    char* query = 0;
+    void *server = nullptr;
+    Context *cxt = nullptr;
+    bool status = false;
+    char* query = nullptr;
     int type = 1;
 
-    void* res = 0;
-    void* ret_col = 0;
+    void* res = nullptr;
+    void* ret_col = nullptr;
     long long cnt = 0;
-    char* last_error = 0;
+    char* last_error = nullptr;
     
-    Server(Context* cxt = nullptr);
+    explicit Server(Context* cxt = nullptr);
     void connect(Context* cxt);
     void exec(const char* q);
     void *getCol(int col_idx);

server/priority_vector.hpp

@@ -6,7 +6,7 @@ template <class Comparator, typename T = uint32_t>
 class priority_vector : public vector_type<T> {
 	const Comparator comp;
 public:
-	priority_vector(Comparator comp = std::less<T>{}) : 
+	explicit priority_vector(Comparator comp = std::less<T>{}) : 
 		comp(comp), vector_type<T>(0) {}
 	void emplace_back(T val) {
 		vector_type<T>::emplace_back(val);

tests/dt2.a

@@ -6,6 +6,8 @@ LOAD MODULE FROM "./libirf.so"
  );
 
 create table source(x1 double, x2 double, x3 double, x4 double, x5 int64);
+-- Create trigger 1 ~~ to predict whenever sz(source > ?)
+-- Create trigger 2 ~~ to auto feed ~
 load data infile "data/benchmark" into table source fields terminated by ",";
 
 create table sparse(x int);