[JVM-PKG] add distributed test simple case

jvm-packages/xgboost4j-demo/src/main/java/ml/dmlc/xgboost4j/demo/DistTrain.java

@@ -0,0 +1,49 @@
+package ml.dmlc.xgboost4j.demo;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.HashMap;
+
+import ml.dmlc.xgboost4j.Rabit;
+import ml.dmlc.xgboost4j.Booster;
+import ml.dmlc.xgboost4j.DMatrix;
+import ml.dmlc.xgboost4j.XGBoost;
+import ml.dmlc.xgboost4j.XGBoostError;
+
+/**
+ * Distributed training example, used to quick test distributed training.
+ *
+ * @author tqchen
+ */
+public class DistTrain {
+
+  public static void main(String[] args) throws IOException, XGBoostError {
+    // always initialize rabit module before training.
+    Rabit.init(new HashMap<String, String>());
+
+    // load file from text file, also binary buffer generated by xgboost4j
+    DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
+    DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
+
+    HashMap<String, Object> params = new HashMap<String, Object>();
+    params.put("eta", 1.0);
+    params.put("max_depth", 2);
+    params.put("silent", 1);
+    params.put("objective", "binary:logistic");
+
+
+    HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
+    watches.put("train", trainMat);
+    watches.put("test", testMat);
+
+    //set round
+    int round = 2;
+
+    //train a boost model
+    Booster booster = XGBoost.train(params, trainMat, round, watches, null, null);
+
+    // always shutdown rabit module after training.
+    Rabit.shutdown();
+  }
+}