[ML-55] [CPU] Add Naive Bayes

dev/codestyle/format-cpp.sh

@@ -21,7 +21,7 @@ if [ -z $CLANG_FORMAT ]; then
     exit 1
 fi
 
-if [ -f .clang-format ]; then
+if [ ! -f .clang-format ]; then
     echo .clang-format is not found in current directory, please generate it.
     exit 1
 fi

examples/naive-bayes/build.sh

@@ -0,0 +1,3 @@
+#!/usr/bin/env bash
+
+mvn clean package

examples/naive-bayes/pom.xml

@@ -0,0 +1,94 @@
+<project xmlns="http://maven.apache.org/POM/4.0.0" 
+  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+
+  <groupId>com.intel.oap</groupId>
+  <artifactId>oap-mllib-examples</artifactId>
+  <version>${oap.version}-with-spark-${spark.version}</version>  
+  <packaging>jar</packaging>
+
+  <name>NaiveBayesExample</name>
+  <url>https://github.com/oap-project/oap-mllib.git</url>
+
+  <properties>
+    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+    <oap.version>1.1.0</oap.version>
+    <scala.version>2.12.10</scala.version>
+    <scala.binary.version>2.12</scala.binary.version>
+    <spark.version>3.0.0</spark.version>
+  </properties>
+
+  <dependencies>
+
+    <dependency>
+      <groupId>org.scala-lang</groupId>
+      <artifactId>scala-library</artifactId>
+      <version>2.12.10</version>
+    </dependency>
+
+    <dependency>
+      <groupId>com.github.scopt</groupId>
+      <artifactId>scopt_2.12</artifactId>
+      <version>3.7.0</version>      
+    </dependency>
+
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-sql_2.12</artifactId>
+      <version>${spark.version}</version>
+      <scope>provided</scope>
+    </dependency>
+
+    <dependency>
+      <groupId>org.apache.spark</groupId>
+      <artifactId>spark-mllib_2.12</artifactId>
+      <version>${spark.version}</version>
+      <scope>provided</scope>
+    </dependency>
+
+  </dependencies>
+
+  <build>
+    <plugins>
+      <plugin>
+        <groupId>org.scala-tools</groupId>
+        <artifactId>maven-scala-plugin</artifactId>
+        <version>2.15.2</version>
+        <executions>
+          <execution>
+            <goals>
+              <goal>compile</goal>
+              <goal>testCompile</goal>
+            </goals>
+          </execution>
+        </executions>
+        <configuration>
+          <scalaVersion>${scala.version}</scalaVersion>
+          <args>
+            <arg>-target:jvm-1.8</arg>
+          </args>
+        </configuration>
+      </plugin>
+      <plugin>
+        <artifactId>maven-assembly-plugin</artifactId>
+        <version>3.0.0</version>
+        <configuration>
+          <appendAssemblyId>false</appendAssemblyId>
+          <descriptorRefs>
+            <descriptorRef>jar-with-dependencies</descriptorRef>
+          </descriptorRefs>
+        </configuration>
+        <executions>
+          <execution>
+            <id>assembly</id>
+            <phase>package</phase>
+            <goals>
+              <goal>single</goal>
+            </goals>
+          </execution>
+        </executions>
+      </plugin>
+    </plugins>
+  </build>
+
+</project>

examples/naive-bayes/run.sh

@@ -0,0 +1,26 @@
+#!/usr/bin/env bash
+
+source ../../conf/env.sh
+
+APP_JAR=target/oap-mllib-examples-$OAP_MLLIB_VERSION-with-spark-3.0.0.jar
+APP_CLASS=org.apache.spark.examples.ml.NaiveBayesExample
+DATA_FILE=data/sample_libsvm_data.txt
+
+time $SPARK_HOME/bin/spark-submit --master $SPARK_MASTER -v \
+    --num-executors $SPARK_NUM_EXECUTORS \
+    --driver-memory $SPARK_DRIVER_MEMORY \
+    --executor-cores $SPARK_EXECUTOR_CORES \
+    --executor-memory $SPARK_EXECUTOR_MEMORY \
+    --conf "spark.oap.mllib.enabled=true" \
+    --conf "spark.serializer=org.apache.spark.serializer.KryoSerializer" \
+    --conf "spark.default.parallelism=$SPARK_DEFAULT_PARALLELISM" \
+    --conf "spark.sql.shuffle.partitions=$SPARK_DEFAULT_PARALLELISM" \
+    --conf "spark.driver.extraClassPath=$SPARK_DRIVER_CLASSPATH" \
+    --conf "spark.executor.extraClassPath=$SPARK_EXECUTOR_CLASSPATH" \
+    --conf "spark.shuffle.reduceLocality.enabled=false" \
+    --conf "spark.network.timeout=1200s" \
+    --conf "spark.task.maxFailures=1" \
+    --jars $OAP_MLLIB_JAR \
+    --class $APP_CLASS \
+    $APP_JAR $DATA_FILE $K \
+    2>&1 | tee NaiveBayes-$(date +%m%d_%H_%M_%S).log

examples/naive-bayes/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala

@@ -0,0 +1,66 @@
+/*
+ * 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.
+ */
+
+// scalastyle:off println
+package org.apache.spark.examples.ml
+
+// $example on$
+import org.apache.spark.ml.classification.NaiveBayes
+import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
+// $example off$
+import org.apache.spark.sql.SparkSession
+
+object NaiveBayesExample {
+  def main(args: Array[String]): Unit = {
+    val spark = SparkSession
+      .builder
+      .appName("NaiveBayesExample")
+      .getOrCreate()
+
+    if (args.length != 1) {
+      println("Require data file path as input parameter")
+      sys.exit(1)
+    }
+
+    // $example on$
+    // Load the data stored in LIBSVM format as a DataFrame.
+    val data = spark.read.format("libsvm").load(args(0))
+
+    // Split the data into training and test sets (30% held out for testing)
+    val Array(trainingData, testData) = data.randomSplit(Array(0.7, 0.3), seed = 1234L)
+
+    // Train a NaiveBayes model.
+    val model = new NaiveBayes()
+      .fit(trainingData)
+
+    // Select example rows to display.
+    val predictions = model.transform(testData)
+    predictions.show()
+
+    // Select (prediction, true label) and compute test error
+    val evaluator = new MulticlassClassificationEvaluator()
+      .setLabelCol("label")
+      .setPredictionCol("prediction")
+      .setMetricName("accuracy")
+    val accuracy = evaluator.evaluate(predictions)
+    println(s"Test set accuracy = $accuracy")
+    // $example off$
+
+    spark.stop()
+  }
+}
+// scalastyle:on println

mllib-dal/src/main/java/org/apache/spark/ml/classification/NaiveBayesResult.java

@@ -0,0 +1,6 @@
+package org.apache.spark.ml.classification;
+
+public class NaiveBayesResult {
+    public long piNumericTable;
+    public long thetaNumericTable;
+}

mllib-dal/src/main/native/ALSDALImpl.cpp

@@ -30,8 +30,6 @@ using namespace daal;
 using namespace daal::algorithms;
 using namespace daal::algorithms::implicit_als;
 
-const int ccl_root = 0;
-
 typedef float algorithmFPType; /* Algorithm floating-point type */
 
 NumericTablePtr userOffset;

mllib-dal/src/main/native/KMeansDALImpl.cpp

@@ -27,8 +27,6 @@ using namespace std;
 using namespace daal;
 using namespace daal::algorithms;
 
-const int ccl_root = 0;
-
 typedef double algorithmFPType; /* Algorithm floating-point type */
 
 static NumericTablePtr kmeans_compute(int rankId, ccl::communicator &comm,

mllib-dal/src/main/native/Makefile

@@ -37,13 +37,15 @@ CPP_SRCS += \
   ./OneCCL.cpp ./OneDAL.cpp ./service.cpp ./error_handling.cpp \
   ./KMeansDALImpl.cpp \
   ./PCADALImpl.cpp \
-  ./ALSDALImpl.cpp ./ALSShuffle.cpp
+  ./ALSDALImpl.cpp ./ALSShuffle.cpp \
+  ./NaiveBayesDALImpl.cpp
 
 OBJS += \
   ./OneCCL.o ./OneDAL.o ./service.o ./error_handling.o \
   ./KMeansDALImpl.o \
   ./PCADALImpl.o \
-  ./ALSDALImpl.o ./ALSShuffle.o
+  ./ALSDALImpl.o ./ALSShuffle.o \
+  ./NaiveBayesDALImpl.o
 
 # Output Binary
 OUTPUT = ../../../target/libMLlibDAL.so