qiuxiafei commented on a change in pull request #9373: [FLINK-13596][ml] Add 
two utils for Table transformations
URL: https://github.com/apache/flink/pull/9373#discussion_r362156769
 
 

 ##########
 File path: 
flink-ml-parent/flink-ml-lib/src/main/java/org/apache/flink/ml/common/utils/DataSetConversionUtil.java
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+/*
+ * 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.flink.ml.common.utils;
+
+import org.apache.flink.api.common.functions.MapFunction;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.java.DataSet;
+import org.apache.flink.api.java.operators.SingleInputUdfOperator;
+import org.apache.flink.api.java.operators.TwoInputUdfOperator;
+import org.apache.flink.api.java.typeutils.RowTypeInfo;
+import org.apache.flink.ml.common.MLEnvironment;
+import org.apache.flink.ml.common.MLEnvironmentFactory;
+import org.apache.flink.table.api.Table;
+import org.apache.flink.table.api.TableSchema;
+import org.apache.flink.table.api.ValidationException;
+import org.apache.flink.types.Row;
+
+/**
+ * Provide functions of conversions between DataSet and Table.
+ */
+public class DataSetConversionUtil {
+       /**
+        * Convert the given Table to {@link DataSet}<{@link Row}>.
+        *
+        * @param sessionId the sessionId of {@link MLEnvironmentFactory}
+        * @param table the Table to convert.
+        * @return the converted DataSet.
+        */
+       public static DataSet <Row> fromTable(Long sessionId, Table table) {
+               return MLEnvironmentFactory
+                       .get(sessionId)
+                       .getBatchTableEnvironment()
+                       .toDataSet(table, Row.class);
+       }
+
+       /**
+        * Convert the given DataSet into a Table with specified TableSchema.
+        *
+        * @param sessionId the sessionId of {@link MLEnvironmentFactory}
+        * @param data   the DataSet to convert.
+        * @param schema the specified TableSchema.
+        * @return the converted Table.
+        */
+       public static Table toTable(Long sessionId, DataSet <Row> data, 
TableSchema schema) {
+               return toTable(sessionId, data, schema.getFieldNames(), 
schema.getFieldTypes());
+       }
+
+       /**
+        * Convert the given DataSet into a Table with specified colNames and 
colTypes.
+        *
+        * @param sessionId sessionId the sessionId of {@link 
MLEnvironmentFactory}.
+        * @param data     the DataSet to convert.
+        * @param colNames the specified colNames.
+        * @param colTypes the specified colTypes. This variable is used only 
when the
+        *                 DataSet is produced by a function and Flink cannot 
determine
+        *                 automatically what the produced type is.
+        * @return the converted Table.
+        */
+       public static Table toTable(Long sessionId, DataSet <Row> data, 
String[] colNames, TypeInformation <?>[] colTypes) {
+               return toTable(MLEnvironmentFactory.get(sessionId), data, 
colNames, colTypes);
+       }
+
+       /**
+        * Convert the given DataSet into a Table with specified colNames.
+        *
+        * @param sessionId sessionId the sessionId of {@link 
MLEnvironmentFactory}.
+        * @param data     the DataSet to convert.
+        * @param colNames the specified colNames.
+        * @return the converted Table.
+        */
+       public static Table toTable(Long sessionId, DataSet <Row> data, 
String[] colNames) {
+               return toTable(MLEnvironmentFactory.get(sessionId), data, 
colNames);
+       }
+
+       /**
+        * Convert the given DataSet into a Table with specified colNames and 
colTypes.
+        *
+        * @param session the MLEnvironment using to convert DataSet to Table.
+        * @param data     the DataSet to convert.
+        * @param colNames the specified colNames.
+        * @param colTypes the specified colTypes. This variable is used only 
when the
+        *                 DataSet is produced by a function and Flink cannot 
determine
+        *                 automatically what the produced type is.
+        * @return the converted Table.
+        */
+       public static Table toTable(MLEnvironment session, DataSet <Row> data, 
String[] colNames, TypeInformation <?>[] colTypes) {
+               try {
+                       // Try to add row type information for the dataset to 
be converted.
+                       // In most case, this keeps us from the rolling back 
logic in the catch block,
+                       // which adds an unnecessary map function just in order 
to add row type information.
+                       if (data instanceof SingleInputUdfOperator) {
 
 Review comment:
   There're two lines confuse me in `testE2E`, 
     1. The line `thrown.expect(ValidationException.class);` , why is an 
`ValidationException` expected?
     2. The line `env.execute();` seems have nothing to execute because of the 
previous `print()` ,am I right?
   
   So I just comment them out, add the heuristic lines back and move ahead. I 
do reproduce the exception you mentioned, in the 3rd `toTable` invocation. I 
think that's because type information has been added to `input` in the 2nd 
invocation already. Flink complains about this when the same thing applied to 
the identical `input` object in the 3rd invocation. So I think at least it 
proves that our heuristic works. And it also reveals a corner case we missed, 
in which an identical `DataSet` object is passed to `toTable` more than once.  
UT will pass after adding `IllegalStateException` to catch block. The new 
`toTable` mothod now looks like:
   ```java
        public static Table toTable(MLEnvironment session, DataSet <Row> data, 
String[] colNames, TypeInformation <?>[] colTypes) {
                try {
                        if (data instanceof SingleInputUdfOperator) {
                                ((SingleInputUdfOperator) data).returns(new 
RowTypeInfo(colTypes, colNames));
                        } else if (data instanceof TwoInputUdfOperator) {
                                ((TwoInputUdfOperator) data).returns(new 
RowTypeInfo(colTypes, colNames));
                        }
                        return toTable(session, data, colNames);
                } catch (ValidationException | IllegalStateException ex) {
                        // currently ValidationException will be thrown and 
caught for further processing.
                        // Because the getType() API of the Transformation can 
only be accessed once.
                        // This can be improve if we add "isTypeSet()" API to 
the Transformation class.
                        if (null == colTypes) {
                                throw ex;
                        } else {
                                DataSet <Row> t = 
fallbackToExplicitTypeDefine(data, colNames, colTypes);
                                return toTable(session, t, colNames);
                        }
                }
   ```
   
   I just wanna make sure it ok to add another exception to the origin 
anti-pattern code ^_^ ..

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