Implement NGram (ML Feature) (#734)

Author: SARAVANA1501

src/csharp/Microsoft.Spark.E2ETest/IpcTests/ML/Feature/NGramTests.cs

@@ -0,0 +1,69 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using System.IO;
+using Microsoft.Spark.ML.Feature;
+using Microsoft.Spark.Sql;
+using Microsoft.Spark.Sql.Types;
+using Microsoft.Spark.UnitTest.TestUtils;
+using Xunit;
+
+namespace Microsoft.Spark.E2ETest.IpcTests.ML.Feature
+{
+    /// <summary>
+    /// Test suite for <see cref="NGram"/> class.
+    /// </summary>
+    [Collection("Spark E2E Tests")]
+    public class NGramTests : FeatureBaseTests<NGram>
+    {
+        private readonly SparkSession _spark;
+
+        public NGramTests(SparkFixture fixture) : base(fixture)
+        {
+            _spark = fixture.Spark;
+        }
+
+        /// <summary>
+        /// Test case to test the methods in <see cref="NGram"/> class.
+        /// </summary>
+        [Fact]
+        public void TestNGram()
+        {
+            string expectedUid = "theUid";
+            string expectedInputCol = "input_col";
+            string expectedOutputCol = "output_col";
+            int expectedN = 2;
+
+            DataFrame input = _spark.Sql("SELECT split('Hi I heard about Spark', ' ') as input_col");
+
+            NGram nGram = new NGram(expectedUid)
+                .SetInputCol(expectedInputCol)
+                .SetOutputCol(expectedOutputCol)
+                .SetN(expectedN);
+
+            StructType outputSchema = nGram.TransformSchema(input.Schema());
+
+            DataFrame output = nGram.Transform(input);
+
+            Assert.Contains(output.Schema().Fields, (f => f.Name == expectedOutputCol));
+            Assert.Contains(outputSchema.Fields, (f => f.Name == expectedOutputCol));
+            Assert.Equal(expectedInputCol, nGram.GetInputCol());
+            Assert.Equal(expectedOutputCol, nGram.GetOutputCol());
+            Assert.Equal(expectedN, nGram.GetN());
+
+            using (var tempDirectory = new TemporaryDirectory())
+            {
+                string savePath = Path.Join(tempDirectory.Path, "NGram");
+                nGram.Save(savePath);
+
+                NGram loadedNGram = NGram.Load(savePath);
+                Assert.Equal(nGram.Uid(), loadedNGram.Uid());
+            }
+
+            Assert.Equal(expectedUid, nGram.Uid());
+
+            TestFeatureBase(nGram, "inputCol", "input_col");
+        }
+    }
+}

src/csharp/Microsoft.Spark/ML/Feature/NGram.cs

@@ -0,0 +1,131 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using Microsoft.Spark.Interop;
+using Microsoft.Spark.Interop.Ipc;
+using Microsoft.Spark.Sql;
+using Microsoft.Spark.Sql.Types;
+
+namespace Microsoft.Spark.ML.Feature
+{
+    /// <summary>
+    /// Class <see cref="NGram"/> transformer that converts the input array of strings into
+    /// an array of n-grams. Null values in the input array are ignored. It returns an array
+    /// of n-grams where each n-gram is represented by a space-separated string of words.
+    /// </summary>
+    public class NGram : FeatureBase<NGram>, IJvmObjectReferenceProvider
+    {
+        private static readonly string s_nGramClassName =
+            "org.apache.spark.ml.feature.NGram";
+
+        /// <summary>
+        /// Create a <see cref="NGram"/> without any parameters.
+        /// </summary>
+        public NGram() : base(s_nGramClassName)
+        {
+        }
+
+        /// <summary>
+        /// Create a <see cref="NGram"/> with a UID that is used to give the
+        /// <see cref="NGram"/> a unique ID.
+        /// </summary>
+        /// <param name="uid">An immutable unique ID for the object and its derivatives.
+        /// </param>
+        public NGram(string uid) : base(s_nGramClassName, uid)
+        {
+        }
+
+        internal NGram(JvmObjectReference jvmObject) : base(jvmObject)
+        {
+        }
+
+        JvmObjectReference IJvmObjectReferenceProvider.Reference => _jvmObject;
+
+        /// <summary>
+        /// Gets the column that the <see cref="NGram"/> should read from.
+        /// </summary>
+        /// <returns>string, input column</returns>
+        public string GetInputCol() => (string)_jvmObject.Invoke("getInputCol");
+
+        /// <summary>
+        /// Sets the column that the <see cref="NGram"/> should read from.
+        /// </summary>
+        /// <param name="value">The name of the column to as the source</param>
+        /// <returns>New <see cref="NGram"/> object</returns>
+        public NGram SetInputCol(string value) => WrapAsNGram(_jvmObject.Invoke("setInputCol", value));
+
+        /// <summary>
+        /// Gets the output column that the <see cref="NGram"/> writes.
+        /// </summary>
+        /// <returns>string, the output column</returns>
+        public string GetOutputCol() => (string)_jvmObject.Invoke("getOutputCol");
+
+        /// <summary>
+        /// Sets the output column that the <see cref="NGram"/> writes.
+        /// </summary>
+        /// <param name="value">The name of the new column</param>
+        /// <returns>New <see cref="NGram"/> object</returns>
+        public NGram SetOutputCol(string value) => WrapAsNGram(_jvmObject.Invoke("setOutputCol", value));
+
+        /// <summary>
+        /// Gets N value for <see cref="NGram"/>.
+        /// </summary>
+        /// <returns>int, N value</returns>
+        public int GetN() => (int)_jvmObject.Invoke("getN");
+
+        /// <summary>
+        /// Sets N value for <see cref="NGram"/>.
+        /// </summary>
+        /// <param name="value">N value</param>
+        /// <returns>New <see cref="NGram"/> object</returns>
+        public NGram SetN(int value) => WrapAsNGram(_jvmObject.Invoke("setN", value));
+
+        /// <summary>
+        /// Executes the <see cref="NGram"/> and transforms the DataFrame to include the new
+        /// column.
+        /// </summary>
+        /// <param name="source">The DataFrame to transform</param>
+        /// <returns>
+        /// New <see cref="DataFrame"/> object with the source <see cref="DataFrame"/> transformed.
+        /// </returns>
+        public DataFrame Transform(DataFrame source) =>
+            new DataFrame((JvmObjectReference)_jvmObject.Invoke("transform", source));
+
+        /// <summary>
+        /// Check transform validity and derive the output schema from the input schema.
+        /// 
+        /// This checks for validity of interactions between parameters during Transform and
+        /// raises an exception if any parameter value is invalid.
+        ///
+        /// Typical implementation should first conduct verification on schema change and parameter
+        /// validity, including complex parameter interaction checks.
+        /// </summary>
+        /// <param name="value">
+        /// The <see cref="StructType"/> of the <see cref="DataFrame"/> which will be transformed.
+        /// </param>
+        /// <returns>
+        /// The <see cref="StructType"/> of the output schema that would have been derived from the
+        /// input schema, if Transform had been called.
+        /// </returns>
+        public StructType TransformSchema(StructType value) =>
+            new StructType(
+                (JvmObjectReference)_jvmObject.Invoke(
+                    "transformSchema",
+                    DataType.FromJson(_jvmObject.Jvm, value.Json)));
+
+        /// <summary>
+        /// Loads the <see cref="NGram"/> that was previously saved using Save.
+        /// </summary>
+        /// <param name="path">The path the previous <see cref="NGram"/> was saved to</param>
+        /// <returns>New <see cref="NGram"/> object, loaded from path</returns>
+        public static NGram Load(string path) =>
+            WrapAsNGram(
+                SparkEnvironment.JvmBridge.CallStaticJavaMethod(
+                    s_nGramClassName,
+                    "load",
+                    path));
+
+        private static NGram WrapAsNGram(object obj) => new NGram((JvmObjectReference)obj);
+    }
+}