Added documentation for trigger demo

README.md

@@ -1,4 +1,7 @@
 # AQuery++ Database
+## News:
+**Demo workflow for Triggers now available** See [**DEMO**](/demo/README.md)
+
 ## Introduction
 
 AQuery++ Database is a cross-platform, In-Memory Column-Store Database that incorporates compiled query execution. (**Note**: If you encounter any problems, feel free to contact me via ys3540@nyu.edu)

build.py

@@ -27,6 +27,7 @@ class checksums:
                     aquery_config.build_driver + 
                     compiler_name + 
                     aquery_config.version_string
+                    + str(os.environ['AQ_DEBUG'] == '1')
                 )
         for key in self.__dict__.keys():
             try:

demo/README.md

@@ -0,0 +1,28 @@
+# Triggers Demo
+
+This folder contains a demo workflow for the two types of triggers. 
+- An interval-based trigger will be set up to execute a stored procedure `demoi` defined in [demo/putdata.cpp](/demo/putdata.cpp) that inserts a .csv file from `data/electricity` to the table `source` every 5 seconds. 
+- A Conditional trigger will be triggered by condition `democq` defined in [demo/query.cpp](/demo/query.cpp) that checks and returns true when more than 200 rows of data are inserted into table `source`. Once triggered, it will execute a stored procedure `democa` defined in [demo/democa.cpp](/demo/action.cpp) that trains the incremental random forest by the new data. 
+- See [demo/prep.a](/demo/prep.a) for parameters of the random forest. 
+
+## Run the demo
+### Preparation 
+- Preprocess data
+  - Put `electricity` dataset to `/data/electricity_orig`
+  - Run `python3 rfdata_preproc.py` to generate .csv files to `data/electricity/`
+- Use [demo/setup.sh](/demo/setup.sh) to 
+  - setup stored procedures for this demo
+  - compile random forest user module used in this demo
+  - compile queries used in this demo 
+
+### Running the demo
+- Run AQuery prompt `python3 prompt.py` 
+- Use Automated AQuery script in [demo/demo.aquery](/demo/demo.aquery) to execute the workflow. It does the following things in order:
+  - Register user module, create a new random forest by running [`f demo/prep.a`](/demo/prep.a)
+  - Register stored procedures. 
+  - Create an Interval-based Trigger that executes payload `demoi` every 5 seconds
+  - Create a Conditional Trigger that executes payload `democa` whenever condition `democq` returns a true. While condition `democq` is tested every time new data is inserted to table `source`.
+  - Loads test data by running [demo/test.a](/demo/test.a)
+  - Use query `select predict(x) from test` to get predictions of the test data from current random forest.
+    - In AQuery prompt, an extra `exec` command after the query is needed to execute the query.
+  - Use query `select test(x, y) from test` will also calculate l2 error.

demo/demo.aquery

@@ -3,15 +3,15 @@
 f demo/prep.a
 exec
 
-procedure demoi run
-procedure democq run
-procedure democa run
+procedure demoi load
+procedure democq load
+procedure democa load
 
-create trigger t action demoi interval 15000
+create trigger t action demoi interval 5000
 exec
 
 create trigger c on source action democa when democq
 exec
 
-# f demo/test.a
-# exec
+f demo/test.a
+exec

demo/prep.a

@@ -1,13 +1,14 @@
 create table source(x vecdouble, y int64);
 LOAD MODULE FROM "./libirf.so"  FUNCTIONS (
-    newtree(height:int, f:int64, sparse:vecint, forget:double, maxf:int64, noclasses:int64, e:int) -> bool,
+    newtree(height:int, f:int64, sparse:vecint, forget:double, noclasses:int64, e:int) -> bool,
     fit_inc(X:vecvecdouble, y:vecint64) -> bool,
-    predict(X:vecvecdouble) -> vecint  
+    predict(X:vecvecdouble) -> vecint ,
+    test(X:vecvecdouble, y:vecint64) -> double  
 );
 
 create table elec_sparse(v int);    
 
 insert into elec_sparse values (0), (1), (1), (1), (1), (1), (1);
 
-select newtree(30, 7, elec_sparse.v, 0, 4, 2, 1) from elec_sparse
+select newtree(30, 7, elec_sparse.v, 0.3, 2, 1) from elec_sparse
 

demo/setup.sh

@@ -0,0 +1,6 @@
+#!/bin/sh 
+
+make -C ../sdk irf
+mkdir ../procedures 
+cp demo*.aqp ../procedures 
+make 

demo/test.a

@@ -1,3 +1,7 @@
+-- select predict(x) from test; 
+-- select test(x, y) from test; 
+
+
 create table test(x vecdouble, y int64);
 load complex data infile "data/electricity/electricity872.csv" into table test fields terminated by ',' element terminated by ';';
-select predict(x) from test
+

paper

@@ -1 +1 @@
-Subproject commit a61c3122c43293ff6f8bd01b4f65d7d03c5c4c54
+Subproject commit 0d0ec214297a3e46947cead37f887eb480043419

prompt.py

@@ -238,7 +238,7 @@ class PromptState():
     server_bin = 'server.bin' if server_mode == RunType.IPC else 'server.so'
     wait_engine = lambda: None
     wake_engine = lambda: None
-    get_storedproc = lambda : StoredProcedure()
+    get_storedproc = lambda *_: StoredProcedure()
     set_ready = lambda: None
     get_ready = lambda: None
     server_status = lambda: False

reconstruct/ast.py

@@ -1336,11 +1336,11 @@ class load(ast_node):
         self.context.postproc_begin(self.postproc_fname)
         
         table:TableInfo = self.context.tables_byname[node['table']]
-        self.sql = F"SELECT {', '.join([c.name for c in table.columns])} FROM {table.table_name};"
-        self.emit(self.sql+';\n')
-        self.context.sql_end()
-        length_name = 'len_' + base62uuid(6)
-        self.context.emitc(f'auto {length_name} = server->cnt;')
+        # self.sql = F"SELECT {', '.join([c.name for c in table.columns])} FROM {table.table_name};"
+        # self.emit(self.sql+';\n')
+        # self.context.sql_end()
+        # length_name = 'len_' + base62uuid(6)
+        # self.context.emitc(f'auto {length_name} = server->cnt;')
         
         out_typenames = [t.type.cname for t in table.columns]
         outtable_col_nameslist = ', '.join([f'"{c.name}"' for c in table.columns])
@@ -1353,7 +1353,8 @@ class load(ast_node):
         for i, c in enumerate(table.columns):
             c.cxt_name = 'c_' + base62uuid(6) 
             self.context.emitc(f'decltype(auto) {c.cxt_name} = {self.out_table}->get_col<{i}>();')
-            self.context.emitc(f'{c.cxt_name}.initfrom({length_name}, server->getCol({i}), "{table.columns[i].name}");')
+            self.context.emitc(f'{c.cxt_name}.init("{table.columns[i].name}");')
+            #self.context.emitc(f'{c.cxt_name}.initfrom({length_name}, server->getCol({i}), "{table.columns[i].name}");')
         csv_reader_name = 'csv_reader_' + base62uuid(6)
         col_types = [c.type.cname for c in table.columns]
         col_tmp_names = ['tmp_'+base62uuid(8) for _ in range(len(table.columns))]

sdk/irf.cpp

@@ -19,7 +19,7 @@ DecisionTree *dt = nullptr;
 RandomForest *rf = nullptr;
 
 __AQEXPORT__(bool)
-newtree(int ntree, long f, ColRef<int> sparse, double forget, long maxf, long nclasses, Evaluation e)
+newtree(int ntree, long f, ColRef<int> sparse, double forget, long nclasses, Evaluation e)
 {
 	if (sparse.size != f)
 		return false;
@@ -27,8 +27,6 @@ newtree(int ntree, long f, ColRef<int> sparse, double forget, long maxf, long nc
 	
 	memcpy(X_cpy, sparse.container, f);
 
-	if (maxf < 0)
-		maxf = f;
 	// dt = new DecisionTree(f, X_cpy, forget, maxf, noclasses, e);
 	rf = new RandomForest(ntree, f, X_cpy, forget, nclasses, e, true);
 	return true;
@@ -100,3 +98,22 @@ predict(vector_type<vector_type<double>> v)
 	auto ret = vectortype_cstorage{.container = container, .size = 1, .capacity = 0};
 	return ret;
 }
+template <typename T>
+constexpr T sq(const T x) {
+	return x * x;
+}
+__AQEXPORT__(double)
+test(vector_type<vector_type<double>> x, vector_type<long> y) {
+	int result = 0;
+	printf("y_hat = (");
+	double err = 0.;
+	for (uint32_t i = 0; i < x.size; i++) {
+		//result[i] = dt->Test(v.container[i].container, dt->DTree);
+		result = int(rf->Test(x[i].container));
+		err += sq(result - y.container[i]);
+		printf("%d ", result);
+	}
+	puts(")");
+	printf("error: %lf\n", err/=double(x.size));
+	return err;
+}

server/server.cpp

@@ -460,6 +460,7 @@ start:
                                     case 'S': // save procedure
                                     break;
                                     case 'L': // load procedure
+                                    current_procedure.name = copy_lpstr(proc_name);
                                     if (!load_proc_fromfile(current_procedure)) {
                                         cxt->stored_proc.insert_or_assign(proc_name, current_procedure);
                                     }

server/table_ext_monetdb.hpp

@@ -42,14 +42,14 @@ void TableInfo<Ts ...>::monetdb_append_table(void* srv, const char* alt_name) {
 	uint32_t i = 0;
 	constexpr auto n_vecs = count_vector_type((tuple_type*)(0));
 	void* gc_vecs[1 + n_vecs];
-	puts("getcols...");
+	// puts("getcols...");
 	uint32_t cnt = 0;
 	const auto get_col = [&monetdbe_cols, &i, *this, &gc_vecs, &cnt](auto v) {
 		// printf("%d %d\n", i, (ColRef<void>*)v - colrefs);
 		monetdbe_cols[i++] = (monetdbe_column*)v->monetdb_get_col(gc_vecs, cnt);
 	};
 	(get_col((ColRef<Ts>*)(colrefs + i)), ...);
-	puts("getcols done");
+	//puts("getcols done");
 	// for(int i = 0; i < sizeof...(Ts); ++i)
 	// {
 	// 	printf("no:%d name: %s count:%d data: %p type:%d \n", 
@@ -68,8 +68,8 @@ void TableInfo<Ts ...>::monetdb_append_table(void* srv, const char* alt_name) {
 	if (last_comma != static_cast<decltype(last_comma)>(-1)) {
 		create_table_str[last_comma] = ')';
 		Server* server = (Server*)srv;
-		puts("create table...");
-		puts(create_table_str.c_str());
+		// puts("create table...");
+		// puts(create_table_str.c_str());
 		server->exec(create_table_str.c_str());
 		if (!server->last_error) {
 			auto err = monetdbe_append(*((monetdbe_database*)server->server), "sys", alt_name, monetdbe_cols, sizeof...(Ts));