From a63ad11ee7915fb367cec80f18fb2c35d025d6d4 Mon Sep 17 00:00:00 2001
From: Alexander Kozhikhov <alex37ko@yandex.ru>
Date: Sat, 25 May 2019 02:18:44 +0300
Subject: [PATCH] LinearRegression without -State modifier now simply returns
 its weights

---
 .../AggregateFunctions/AggregateFunctionMLMethod.cpp  | 11 +++++++++++
 .../AggregateFunctions/AggregateFunctionMLMethod.h    |  8 +++++---
 .../tests/queries/0_stateless/00947_ml_test.reference |  3 +++
 dbms/tests/queries/0_stateless/00947_ml_test.sql      | 10 ++++++++++
 4 files changed, 29 insertions(+), 3 deletions(-)

diff --git a/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.cpp b/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.cpp
index c7162f04b51..29f6b700d76 100644
--- a/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.cpp
+++ b/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.cpp
@@ -3,6 +3,7 @@
 #include <IO/ReadHelpers.h>
 #include <IO/WriteHelpers.h>
 #include <Interpreters/castColumn.h>
+#include <Columns/ColumnArray.h>
 #include <Common/FieldVisitors.h>
 #include <Common/typeid_cast.h>
 #include "AggregateFunctionFactory.h"
@@ -149,6 +150,16 @@ void LinearModelData::predict(
     gradient_computer->predict(container, block, arguments, weights, bias, context);
 }
 
+void LinearModelData::return_weights(IColumn & to) const
+{
+    auto & column = static_cast<ColumnVector<Float64> &>(to);
+    for (auto weight_value : weights)
+    {
+        column.getData().push_back(weight_value);
+    }
+    column.getData().push_back(bias);
+}
+
 void LinearModelData::read(ReadBuffer & buf)
 {
     readBinary(bias, buf);
diff --git a/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.h b/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.h
index 3c4660f14f5..2ee2c1fe415 100644
--- a/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.h
+++ b/dbms/src/AggregateFunctions/AggregateFunctionMLMethod.h
@@ -218,6 +218,7 @@ public:
     void
     predict(ColumnVector<Float64>::Container & container, Block & block, const ColumnNumbers & arguments, const Context & context) const;
 
+    void return_weights(IColumn & to) const;
 private:
     std::vector<Float64> weights;
     Float64 bias{0.0};
@@ -301,11 +302,12 @@ public:
         this->data(place).predict(column.getData(), block, arguments, context);
     }
 
+    /** This function is called if aggregate function without State modifier is selected in a query.
+     *  Inserts all weights of the model into the column 'to', so user may use such information if needed
+     */
     void insertResultInto(ConstAggregateDataPtr place, IColumn & to) const override
     {
-        std::ignore = place;
-        std::ignore = to;
-        throw std::runtime_error("not implemented");
+        this->data(place).return_weights(to);
     }
 
     const char * getHeaderFilePath() const override { return __FILE__; }
diff --git a/dbms/tests/queries/0_stateless/00947_ml_test.reference b/dbms/tests/queries/0_stateless/00947_ml_test.reference
index d00491fd7e5..98fb6a68656 100644
--- a/dbms/tests/queries/0_stateless/00947_ml_test.reference
+++ b/dbms/tests/queries/0_stateless/00947_ml_test.reference
@@ -1 +1,4 @@
 1
+1
+1
+1
diff --git a/dbms/tests/queries/0_stateless/00947_ml_test.sql b/dbms/tests/queries/0_stateless/00947_ml_test.sql
index b5a602f6826..923fa1ff357 100644
--- a/dbms/tests/queries/0_stateless/00947_ml_test.sql
+++ b/dbms/tests/queries/0_stateless/00947_ml_test.sql
@@ -15,3 +15,13 @@ create table test.model engine = Memory as select linearRegressionState(0.03, 0.
 
 select ans > -67.0 and ans < -66.9 from
 (with (select state from test.model) as model select evalMLMethod(model, predict1, predict2) as ans from test.defaults limit 1);
+
+-- Check that returned weights are close to real
+select ans > 0.49 and ans < 0.51 from
+(select linearRegression(0.03, 0.00001, 2, 'Nesterov')(target, param1, param2) as ans from test.defaults limit 0, 1);
+
+select ans > -2.01 and ans < -1.99 from
+(select linearRegression(0.03, 0.00001, 2, 'Nesterov')(target, param1, param2) as ans from test.defaults limit 1, 1);
+
+select ans > 2.99 and ans < 3.01 from
+(select linearRegression(0.03, 0.00001, 2, 'Nesterov')(target, param1, param2) as ans from test.defaults limit 2, 1);