subject:"\[jira\] \[Updated\] \(IGNITE\-12331\) \[ML\] ML Preprocessing doesn't work on SQL Tables"

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

2020-12-29 Thread Maxim Muzafarov (Jira)



 [ 
https://issues.apache.org/jira/browse/IGNITE-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Maxim Muzafarov updated IGNITE-12331:
-
Fix Version/s: (was: 2.10)

> [ML] ML Preprocessing doesn't work on SQL Tables
> 
>
> Key: IGNITE-12331
> URL: https://issues.apache.org/jira/browse/IGNITE-12331
> Project: Ignite
>  Issue Type: Bug
>  Components: ml
>Affects Versions: 2.8
>Reporter: Alexey Zinoviev
>Assignee: Alexey Zinoviev
>Priority: Major
>
> {code:java}
> /*
>  * Licensed to the Apache Software Foundation (ASF) under one or more
>  * contributor license agreements.  See the NOTICE file distributed with
>  * this work for additional information regarding copyright ownership.
>  * The ASF licenses this file to You under the Apache License, Version 2.0
>  * (the "License"); you may not use this file except in compliance with
>  * the License.  You may obtain a copy of the License at
>  *
>  *  http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.ignite.examples.ml.tutorial.sql;
> import java.util.List;
> import org.apache.ignite.Ignite;
> import org.apache.ignite.IgniteCache;
> import org.apache.ignite.Ignition;
> import org.apache.ignite.cache.query.QueryCursor;
> import org.apache.ignite.cache.query.SqlFieldsQuery;
> import org.apache.ignite.configuration.CacheConfiguration;
> import org.apache.ignite.internal.util.IgniteUtils;
> import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
> import 
> org.apache.ignite.ml.dataset.feature.extractor.impl.BinaryObjectVectorizer;
> import org.apache.ignite.ml.math.primitives.vector.Vector;
> import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
> import org.apache.ignite.ml.preprocessing.Preprocessor;
> import org.apache.ignite.ml.preprocessing.minmaxscaling.MinMaxScalerTrainer;
> import org.apache.ignite.ml.preprocessing.normalization.NormalizationTrainer;
> import org.apache.ignite.ml.sql.SqlDatasetBuilder;
> import org.apache.ignite.ml.tree.DecisionTreeClassificationTrainer;
> import org.apache.ignite.ml.tree.DecisionTreeNode;
> /**
>  * Example of using distributed {@link DecisionTreeClassificationTrainer} on 
> a data stored in SQL table.
>  */
> public class PreprocessingAndTrainingSQLTableExample {
> /**
>  * Dummy cache name.
>  */
> private static final String DUMMY_CACHE_NAME = "dummy_cache";
> /**
>  * Training data.
>  */
> private static final String TRAIN_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_train.csv";
> /**
>  * Test data.
>  */
> private static final String TEST_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_test.csv";
> /**
>  * Run example.
>  */
> public static void main(String[] args) {
> System.out.println(">>> Decision tree classification trainer example 
> started.");
> // Start ignite grid.
> try (Ignite ignite = 
> Ignition.start("examples/config/example-ignite.xml")) {
> System.out.println(">>> Ignite grid started.");
> // Dummy cache is required to perform SQL queries.
> CacheConfiguration cacheCfg = new 
> CacheConfiguration<>(DUMMY_CACHE_NAME)
> .setSqlSchema("PUBLIC");
> IgniteCache cache = null;
> try {
> cache = ignite.getOrCreateCache(cacheCfg);
> System.out.println(">>> Creating table with training 
> data...");
> cache.query(new SqlFieldsQuery("create table titanic_train 
> (\n" +
> "passengerid int primary key,\n" +
> "survived int,\n" +
> "pclass int,\n" +
> "name varchar(255),\n" +
> "sex varchar(255),\n" +
> "age float,\n" +
> "sibsp int,\n" +
> "parch int,\n" +
> "ticket varchar(255),\n" +
> "fare float,\n" +
> "cabin varchar(255),\n" +
> "embarked varchar(255)\n" +
> ") with \"template=partitioned\";")).getAll();
> System.out.println(">>> Filling training data...");
> cache.query(new SqlFieldsQuery("insert into titanic_train 
> select * from csvread('" +
> 
> IgniteUtils.resolveIgnitePath(TRAIN_DATA_RES).getAbsolutePath() + 
>

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

2020-06-26 Thread Alexey Zinoviev (Jira)



 [ 
https://issues.apache.org/jira/browse/IGNITE-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Alexey Zinoviev updated IGNITE-12331:
-
Fix Version/s: (was: 2.9)
   2.10

> [ML] ML Preprocessing doesn't work on SQL Tables
> 
>
> Key: IGNITE-12331
> URL: https://issues.apache.org/jira/browse/IGNITE-12331
> Project: Ignite
>  Issue Type: Bug
>  Components: ml
>Affects Versions: 2.8
>Reporter: Alexey Zinoviev
>Assignee: Alexey Zinoviev
>Priority: Major
> Fix For: 2.10
>
>
> {code:java}
> /*
>  * Licensed to the Apache Software Foundation (ASF) under one or more
>  * contributor license agreements.  See the NOTICE file distributed with
>  * this work for additional information regarding copyright ownership.
>  * The ASF licenses this file to You under the Apache License, Version 2.0
>  * (the "License"); you may not use this file except in compliance with
>  * the License.  You may obtain a copy of the License at
>  *
>  *  http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.ignite.examples.ml.tutorial.sql;
> import java.util.List;
> import org.apache.ignite.Ignite;
> import org.apache.ignite.IgniteCache;
> import org.apache.ignite.Ignition;
> import org.apache.ignite.cache.query.QueryCursor;
> import org.apache.ignite.cache.query.SqlFieldsQuery;
> import org.apache.ignite.configuration.CacheConfiguration;
> import org.apache.ignite.internal.util.IgniteUtils;
> import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
> import 
> org.apache.ignite.ml.dataset.feature.extractor.impl.BinaryObjectVectorizer;
> import org.apache.ignite.ml.math.primitives.vector.Vector;
> import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
> import org.apache.ignite.ml.preprocessing.Preprocessor;
> import org.apache.ignite.ml.preprocessing.minmaxscaling.MinMaxScalerTrainer;
> import org.apache.ignite.ml.preprocessing.normalization.NormalizationTrainer;
> import org.apache.ignite.ml.sql.SqlDatasetBuilder;
> import org.apache.ignite.ml.tree.DecisionTreeClassificationTrainer;
> import org.apache.ignite.ml.tree.DecisionTreeNode;
> /**
>  * Example of using distributed {@link DecisionTreeClassificationTrainer} on 
> a data stored in SQL table.
>  */
> public class PreprocessingAndTrainingSQLTableExample {
> /**
>  * Dummy cache name.
>  */
> private static final String DUMMY_CACHE_NAME = "dummy_cache";
> /**
>  * Training data.
>  */
> private static final String TRAIN_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_train.csv";
> /**
>  * Test data.
>  */
> private static final String TEST_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_test.csv";
> /**
>  * Run example.
>  */
> public static void main(String[] args) {
> System.out.println(">>> Decision tree classification trainer example 
> started.");
> // Start ignite grid.
> try (Ignite ignite = 
> Ignition.start("examples/config/example-ignite.xml")) {
> System.out.println(">>> Ignite grid started.");
> // Dummy cache is required to perform SQL queries.
> CacheConfiguration cacheCfg = new 
> CacheConfiguration<>(DUMMY_CACHE_NAME)
> .setSqlSchema("PUBLIC");
> IgniteCache cache = null;
> try {
> cache = ignite.getOrCreateCache(cacheCfg);
> System.out.println(">>> Creating table with training 
> data...");
> cache.query(new SqlFieldsQuery("create table titanic_train 
> (\n" +
> "passengerid int primary key,\n" +
> "survived int,\n" +
> "pclass int,\n" +
> "name varchar(255),\n" +
> "sex varchar(255),\n" +
> "age float,\n" +
> "sibsp int,\n" +
> "parch int,\n" +
> "ticket varchar(255),\n" +
> "fare float,\n" +
> "cabin varchar(255),\n" +
> "embarked varchar(255)\n" +
> ") with \"template=partitioned\";")).getAll();
> System.out.println(">>> Filling training data...");
> cache.query(new SqlFieldsQuery("insert into titanic_train 
> select * from csvread('" +
> 
>

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

2020-01-23 Thread Alexey Zinoviev (Jira)



 [ 
https://issues.apache.org/jira/browse/IGNITE-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Alexey Zinoviev updated IGNITE-12331:
-
Affects Version/s: (was: 3.0)
   2.8

> [ML] ML Preprocessing doesn't work on SQL Tables
> 
>
> Key: IGNITE-12331
> URL: https://issues.apache.org/jira/browse/IGNITE-12331
> Project: Ignite
>  Issue Type: Bug
>  Components: ml
>Affects Versions: 2.8
>Reporter: Alexey Zinoviev
>Assignee: Alexey Zinoviev
>Priority: Major
> Fix For: 3.0
>
>
> {code:java}
> /*
>  * Licensed to the Apache Software Foundation (ASF) under one or more
>  * contributor license agreements.  See the NOTICE file distributed with
>  * this work for additional information regarding copyright ownership.
>  * The ASF licenses this file to You under the Apache License, Version 2.0
>  * (the "License"); you may not use this file except in compliance with
>  * the License.  You may obtain a copy of the License at
>  *
>  *  http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.ignite.examples.ml.tutorial.sql;
> import java.util.List;
> import org.apache.ignite.Ignite;
> import org.apache.ignite.IgniteCache;
> import org.apache.ignite.Ignition;
> import org.apache.ignite.cache.query.QueryCursor;
> import org.apache.ignite.cache.query.SqlFieldsQuery;
> import org.apache.ignite.configuration.CacheConfiguration;
> import org.apache.ignite.internal.util.IgniteUtils;
> import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
> import 
> org.apache.ignite.ml.dataset.feature.extractor.impl.BinaryObjectVectorizer;
> import org.apache.ignite.ml.math.primitives.vector.Vector;
> import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
> import org.apache.ignite.ml.preprocessing.Preprocessor;
> import org.apache.ignite.ml.preprocessing.minmaxscaling.MinMaxScalerTrainer;
> import org.apache.ignite.ml.preprocessing.normalization.NormalizationTrainer;
> import org.apache.ignite.ml.sql.SqlDatasetBuilder;
> import org.apache.ignite.ml.tree.DecisionTreeClassificationTrainer;
> import org.apache.ignite.ml.tree.DecisionTreeNode;
> /**
>  * Example of using distributed {@link DecisionTreeClassificationTrainer} on 
> a data stored in SQL table.
>  */
> public class PreprocessingAndTrainingSQLTableExample {
> /**
>  * Dummy cache name.
>  */
> private static final String DUMMY_CACHE_NAME = "dummy_cache";
> /**
>  * Training data.
>  */
> private static final String TRAIN_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_train.csv";
> /**
>  * Test data.
>  */
> private static final String TEST_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_test.csv";
> /**
>  * Run example.
>  */
> public static void main(String[] args) {
> System.out.println(">>> Decision tree classification trainer example 
> started.");
> // Start ignite grid.
> try (Ignite ignite = 
> Ignition.start("examples/config/example-ignite.xml")) {
> System.out.println(">>> Ignite grid started.");
> // Dummy cache is required to perform SQL queries.
> CacheConfiguration cacheCfg = new 
> CacheConfiguration<>(DUMMY_CACHE_NAME)
> .setSqlSchema("PUBLIC");
> IgniteCache cache = null;
> try {
> cache = ignite.getOrCreateCache(cacheCfg);
> System.out.println(">>> Creating table with training 
> data...");
> cache.query(new SqlFieldsQuery("create table titanic_train 
> (\n" +
> "passengerid int primary key,\n" +
> "survived int,\n" +
> "pclass int,\n" +
> "name varchar(255),\n" +
> "sex varchar(255),\n" +
> "age float,\n" +
> "sibsp int,\n" +
> "parch int,\n" +
> "ticket varchar(255),\n" +
> "fare float,\n" +
> "cabin varchar(255),\n" +
> "embarked varchar(255)\n" +
> ") with \"template=partitioned\";")).getAll();
> System.out.println(">>> Filling training data...");
> cache.query(new SqlFieldsQuery("insert into titanic_train 
> select * from csvread('" +
> 
>

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

2020-01-23 Thread Alexey Zinoviev (Jira)



 [ 
https://issues.apache.org/jira/browse/IGNITE-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Alexey Zinoviev updated IGNITE-12331:
-
Fix Version/s: (was: 3.0)
   2.9

> [ML] ML Preprocessing doesn't work on SQL Tables
> 
>
> Key: IGNITE-12331
> URL: https://issues.apache.org/jira/browse/IGNITE-12331
> Project: Ignite
>  Issue Type: Bug
>  Components: ml
>Affects Versions: 2.8
>Reporter: Alexey Zinoviev
>Assignee: Alexey Zinoviev
>Priority: Major
> Fix For: 2.9
>
>
> {code:java}
> /*
>  * Licensed to the Apache Software Foundation (ASF) under one or more
>  * contributor license agreements.  See the NOTICE file distributed with
>  * this work for additional information regarding copyright ownership.
>  * The ASF licenses this file to You under the Apache License, Version 2.0
>  * (the "License"); you may not use this file except in compliance with
>  * the License.  You may obtain a copy of the License at
>  *
>  *  http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.ignite.examples.ml.tutorial.sql;
> import java.util.List;
> import org.apache.ignite.Ignite;
> import org.apache.ignite.IgniteCache;
> import org.apache.ignite.Ignition;
> import org.apache.ignite.cache.query.QueryCursor;
> import org.apache.ignite.cache.query.SqlFieldsQuery;
> import org.apache.ignite.configuration.CacheConfiguration;
> import org.apache.ignite.internal.util.IgniteUtils;
> import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
> import 
> org.apache.ignite.ml.dataset.feature.extractor.impl.BinaryObjectVectorizer;
> import org.apache.ignite.ml.math.primitives.vector.Vector;
> import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
> import org.apache.ignite.ml.preprocessing.Preprocessor;
> import org.apache.ignite.ml.preprocessing.minmaxscaling.MinMaxScalerTrainer;
> import org.apache.ignite.ml.preprocessing.normalization.NormalizationTrainer;
> import org.apache.ignite.ml.sql.SqlDatasetBuilder;
> import org.apache.ignite.ml.tree.DecisionTreeClassificationTrainer;
> import org.apache.ignite.ml.tree.DecisionTreeNode;
> /**
>  * Example of using distributed {@link DecisionTreeClassificationTrainer} on 
> a data stored in SQL table.
>  */
> public class PreprocessingAndTrainingSQLTableExample {
> /**
>  * Dummy cache name.
>  */
> private static final String DUMMY_CACHE_NAME = "dummy_cache";
> /**
>  * Training data.
>  */
> private static final String TRAIN_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_train.csv";
> /**
>  * Test data.
>  */
> private static final String TEST_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_test.csv";
> /**
>  * Run example.
>  */
> public static void main(String[] args) {
> System.out.println(">>> Decision tree classification trainer example 
> started.");
> // Start ignite grid.
> try (Ignite ignite = 
> Ignition.start("examples/config/example-ignite.xml")) {
> System.out.println(">>> Ignite grid started.");
> // Dummy cache is required to perform SQL queries.
> CacheConfiguration cacheCfg = new 
> CacheConfiguration<>(DUMMY_CACHE_NAME)
> .setSqlSchema("PUBLIC");
> IgniteCache cache = null;
> try {
> cache = ignite.getOrCreateCache(cacheCfg);
> System.out.println(">>> Creating table with training 
> data...");
> cache.query(new SqlFieldsQuery("create table titanic_train 
> (\n" +
> "passengerid int primary key,\n" +
> "survived int,\n" +
> "pclass int,\n" +
> "name varchar(255),\n" +
> "sex varchar(255),\n" +
> "age float,\n" +
> "sibsp int,\n" +
> "parch int,\n" +
> "ticket varchar(255),\n" +
> "fare float,\n" +
> "cabin varchar(255),\n" +
> "embarked varchar(255)\n" +
> ") with \"template=partitioned\";")).getAll();
> System.out.println(">>> Filling training data...");
> cache.query(new SqlFieldsQuery("insert into titanic_train 
> select * from csvread('" +
> 
>

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

2019-10-28 Thread Alexey Zinoviev (Jira)



 [ 
https://issues.apache.org/jira/browse/IGNITE-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Alexey Zinoviev updated IGNITE-12331:
-
Affects Version/s: 3.0

> [ML] ML Preprocessing doesn't work on SQL Tables
> 
>
> Key: IGNITE-12331
> URL: https://issues.apache.org/jira/browse/IGNITE-12331
> Project: Ignite
>  Issue Type: Bug
>  Components: ml
>Affects Versions: 3.0
>Reporter: Alexey Zinoviev
>Assignee: Alexey Zinoviev
>Priority: Major
>
> {code:java}
> /*
>  * Licensed to the Apache Software Foundation (ASF) under one or more
>  * contributor license agreements.  See the NOTICE file distributed with
>  * this work for additional information regarding copyright ownership.
>  * The ASF licenses this file to You under the Apache License, Version 2.0
>  * (the "License"); you may not use this file except in compliance with
>  * the License.  You may obtain a copy of the License at
>  *
>  *  http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.ignite.examples.ml.tutorial.sql;
> import java.util.List;
> import org.apache.ignite.Ignite;
> import org.apache.ignite.IgniteCache;
> import org.apache.ignite.Ignition;
> import org.apache.ignite.cache.query.QueryCursor;
> import org.apache.ignite.cache.query.SqlFieldsQuery;
> import org.apache.ignite.configuration.CacheConfiguration;
> import org.apache.ignite.internal.util.IgniteUtils;
> import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
> import 
> org.apache.ignite.ml.dataset.feature.extractor.impl.BinaryObjectVectorizer;
> import org.apache.ignite.ml.math.primitives.vector.Vector;
> import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
> import org.apache.ignite.ml.preprocessing.Preprocessor;
> import org.apache.ignite.ml.preprocessing.minmaxscaling.MinMaxScalerTrainer;
> import org.apache.ignite.ml.preprocessing.normalization.NormalizationTrainer;
> import org.apache.ignite.ml.sql.SqlDatasetBuilder;
> import org.apache.ignite.ml.tree.DecisionTreeClassificationTrainer;
> import org.apache.ignite.ml.tree.DecisionTreeNode;
> /**
>  * Example of using distributed {@link DecisionTreeClassificationTrainer} on 
> a data stored in SQL table.
>  */
> public class PreprocessingAndTrainingSQLTableExample {
> /**
>  * Dummy cache name.
>  */
> private static final String DUMMY_CACHE_NAME = "dummy_cache";
> /**
>  * Training data.
>  */
> private static final String TRAIN_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_train.csv";
> /**
>  * Test data.
>  */
> private static final String TEST_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_test.csv";
> /**
>  * Run example.
>  */
> public static void main(String[] args) {
> System.out.println(">>> Decision tree classification trainer example 
> started.");
> // Start ignite grid.
> try (Ignite ignite = 
> Ignition.start("examples/config/example-ignite.xml")) {
> System.out.println(">>> Ignite grid started.");
> // Dummy cache is required to perform SQL queries.
> CacheConfiguration cacheCfg = new 
> CacheConfiguration<>(DUMMY_CACHE_NAME)
> .setSqlSchema("PUBLIC");
> IgniteCache cache = null;
> try {
> cache = ignite.getOrCreateCache(cacheCfg);
> System.out.println(">>> Creating table with training 
> data...");
> cache.query(new SqlFieldsQuery("create table titanic_train 
> (\n" +
> "passengerid int primary key,\n" +
> "survived int,\n" +
> "pclass int,\n" +
> "name varchar(255),\n" +
> "sex varchar(255),\n" +
> "age float,\n" +
> "sibsp int,\n" +
> "parch int,\n" +
> "ticket varchar(255),\n" +
> "fare float,\n" +
> "cabin varchar(255),\n" +
> "embarked varchar(255)\n" +
> ") with \"template=partitioned\";")).getAll();
> System.out.println(">>> Filling training data...");
> cache.query(new SqlFieldsQuery("insert into titanic_train 
> select * from csvread('" +
> 
> IgniteUtils.resolveIgnitePath(TRAIN_DATA_RES).getAbsolutePath() + 
>

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

2019-10-28 Thread Alexey Zinoviev (Jira)



 [ 
https://issues.apache.org/jira/browse/IGNITE-12331?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Alexey Zinoviev updated IGNITE-12331:
-
Fix Version/s: 3.0

> [ML] ML Preprocessing doesn't work on SQL Tables
> 
>
> Key: IGNITE-12331
> URL: https://issues.apache.org/jira/browse/IGNITE-12331
> Project: Ignite
>  Issue Type: Bug
>  Components: ml
>Affects Versions: 3.0
>Reporter: Alexey Zinoviev
>Assignee: Alexey Zinoviev
>Priority: Major
> Fix For: 3.0
>
>
> {code:java}
> /*
>  * Licensed to the Apache Software Foundation (ASF) under one or more
>  * contributor license agreements.  See the NOTICE file distributed with
>  * this work for additional information regarding copyright ownership.
>  * The ASF licenses this file to You under the Apache License, Version 2.0
>  * (the "License"); you may not use this file except in compliance with
>  * the License.  You may obtain a copy of the License at
>  *
>  *  http://www.apache.org/licenses/LICENSE-2.0
>  *
>  * Unless required by applicable law or agreed to in writing, software
>  * distributed under the License is distributed on an "AS IS" BASIS,
>  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
>  * See the License for the specific language governing permissions and
>  * limitations under the License.
>  */
> package org.apache.ignite.examples.ml.tutorial.sql;
> import java.util.List;
> import org.apache.ignite.Ignite;
> import org.apache.ignite.IgniteCache;
> import org.apache.ignite.Ignition;
> import org.apache.ignite.cache.query.QueryCursor;
> import org.apache.ignite.cache.query.SqlFieldsQuery;
> import org.apache.ignite.configuration.CacheConfiguration;
> import org.apache.ignite.internal.util.IgniteUtils;
> import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
> import 
> org.apache.ignite.ml.dataset.feature.extractor.impl.BinaryObjectVectorizer;
> import org.apache.ignite.ml.math.primitives.vector.Vector;
> import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
> import org.apache.ignite.ml.preprocessing.Preprocessor;
> import org.apache.ignite.ml.preprocessing.minmaxscaling.MinMaxScalerTrainer;
> import org.apache.ignite.ml.preprocessing.normalization.NormalizationTrainer;
> import org.apache.ignite.ml.sql.SqlDatasetBuilder;
> import org.apache.ignite.ml.tree.DecisionTreeClassificationTrainer;
> import org.apache.ignite.ml.tree.DecisionTreeNode;
> /**
>  * Example of using distributed {@link DecisionTreeClassificationTrainer} on 
> a data stored in SQL table.
>  */
> public class PreprocessingAndTrainingSQLTableExample {
> /**
>  * Dummy cache name.
>  */
> private static final String DUMMY_CACHE_NAME = "dummy_cache";
> /**
>  * Training data.
>  */
> private static final String TRAIN_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_train.csv";
> /**
>  * Test data.
>  */
> private static final String TEST_DATA_RES = 
> "examples/src/main/resources/datasets/titanic_test.csv";
> /**
>  * Run example.
>  */
> public static void main(String[] args) {
> System.out.println(">>> Decision tree classification trainer example 
> started.");
> // Start ignite grid.
> try (Ignite ignite = 
> Ignition.start("examples/config/example-ignite.xml")) {
> System.out.println(">>> Ignite grid started.");
> // Dummy cache is required to perform SQL queries.
> CacheConfiguration cacheCfg = new 
> CacheConfiguration<>(DUMMY_CACHE_NAME)
> .setSqlSchema("PUBLIC");
> IgniteCache cache = null;
> try {
> cache = ignite.getOrCreateCache(cacheCfg);
> System.out.println(">>> Creating table with training 
> data...");
> cache.query(new SqlFieldsQuery("create table titanic_train 
> (\n" +
> "passengerid int primary key,\n" +
> "survived int,\n" +
> "pclass int,\n" +
> "name varchar(255),\n" +
> "sex varchar(255),\n" +
> "age float,\n" +
> "sibsp int,\n" +
> "parch int,\n" +
> "ticket varchar(255),\n" +
> "fare float,\n" +
> "cabin varchar(255),\n" +
> "embarked varchar(255)\n" +
> ") with \"template=partitioned\";")).getAll();
> System.out.println(">>> Filling training data...");
> cache.query(new SqlFieldsQuery("insert into titanic_train 
> select * from csvread('" +
> 
>

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

[jira] [Updated] (IGNITE-12331) [ML] ML Preprocessing doesn't work on SQL Tables

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