add doc for JAVA_SDK

doc/JAVA_SDK.md

+# Paddle Serving Client Java SDK
+
+([简体中文](JAVA_SDK_CN.md)|English)
+
+Paddle Serving provides Java SDK，which supports predict on the Client side with Java language. This document shows how to use the Java SDK.
+
+## Getting started
+
+### Prerequisites
+
+```
+- Java 8 or higher
+- Apache Maven
+```
+
+The following table shows compatibilities between Paddle Serving Server and Java SDK.
+
+| Paddle Serving Server version | Java SDK version |
+| :---------------------------: | :--------------: |
+|             0.3.2             |      0.0.1       |
+
+### Install Java SDK
+
+You can use Apache Maven to download the SDK.
+
+```shell
+ <dependency>
+     <groupId>io.paddle.serving.client</groupId>
+     <artifactId>paddle-serving-sdk-java</artifactId>
+     <version>0.0.1</version>
+ </dependency>
+```
+
+
+
+## Example
+
+Here we will show how to use Java SDK for Boston house price prediction. Please refer to [examples](../java/examples) folder for more examples.
+
+### Get model
+
+```shell
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/uci_housing.tar.gz
+tar -xzf uci_housing.tar.gz
+```
+
+### Start Python Server
+
+```shell
+python -m paddle_serving_server.serve --model uci_housing_model --port 9393 --use_multilang 
+```
+
+#### Client side code example
+
+```java
+import io.paddle.serving.client.*;
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.factory.Nd4j;
+import java.util.*;
+
+public class PaddleServingClientExample {
+    public static void main( String[] args ) {
+        float[] data = {0.0137f, -0.1136f, 0.2553f, -0.0692f,
+            0.0582f, -0.0727f, -0.1583f, -0.0584f,
+            0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f};
+        INDArray npdata = Nd4j.createFromArray(data);
+        HashMap<String, INDArray> feed_data
+            = new HashMap<String, INDArray>() {{
+                put("x", npdata);
+            }};
+        List<String> fetch = Arrays.asList("price");
+
+        Client client = new Client();
+        String target = "localhost:9393";
+        boolean succ = client.connect(target);
+        if (succ != true) {
+            System.out.println("connect failed.");
+            return ;
+        }
+
+        Map<String, INDArray> fetch_map = client.predict(feed_data, fetch);
+        if (fetch_map == null) {
+            System.out.println("predict failed.");
+            return ;
+        }
+
+        for (Map.Entry<String, INDArray> e : fetch_map.entrySet()) {
+            System.out.println("Key = " + e.getKey() + ", Value = " + e.getValue());
+        }
+        return ;
+    }
+}
+```
+

doc/JAVA_SDK_CN.md

+# Paddle Serving Client Java SDK
+
+(简体中文|[English](JAVA_SDK.md))
+
+Paddle Serving 提供了 Java SDK，支持 Client 端用 Java 语言进行预测，本文档说明了如何使用 Java SDK。
+
+
+
+## 快速开始
+
+### 环境要求
+
+```
+- Java 8 or higher
+- Apache Maven
+```
+
+下表显示了 Paddle Serving Server 和 Java SDK 之间的兼容性
+
+| Paddle Serving Server version | Java SDK version |
+| :---------------------------: | :--------------: |
+|             0.3.2             |      0.0.1       |
+
+### 安装
+
+您可以使用 Apache Maven 下载该 SDK。 
+
+```shell
+ <dependency>
+     <groupId>io.paddle.serving.client</groupId>
+     <artifactId>paddle-serving-sdk-java</artifactId>
+     <version>0.0.1</version>
+ </dependency>
+```
+
+
+## 使用样例
+
+这里将展示如何使用 Java SDK 进行房价预测，更多例子详见 [examples](../java/examples) 文件夹。
+
+### 获取房价预测模型
+
+```shell
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/uci_housing.tar.gz
+tar -xzf uci_housing.tar.gz
+```
+
+### 启动 Python 端 Server
+
+```shell
+python -m paddle_serving_server.serve --model uci_housing_model --port 9393 --use_multilang 
+```
+
+### Client 端代码示例
+
+```java
+import io.paddle.serving.client.*;
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.factory.Nd4j;
+import java.util.*;
+
+public class PaddleServingClientExample {
+    public static void main( String[] args ) {
+        float[] data = {0.0137f, -0.1136f, 0.2553f, -0.0692f,
+            0.0582f, -0.0727f, -0.1583f, -0.0584f,
+            0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f};
+        INDArray npdata = Nd4j.createFromArray(data);
+        HashMap<String, INDArray> feed_data
+            = new HashMap<String, INDArray>() {{
+                put("x", npdata);
+            }};
+        List<String> fetch = Arrays.asList("price");
+
+        Client client = new Client();
+        String target = "localhost:9393";
+        boolean succ = client.connect(target);
+        if (succ != true) {
+            System.out.println("connect failed.");
+            return ;
+        }
+
+        Map<String, INDArray> fetch_map = client.predict(feed_data, fetch);
+        if (fetch_map == null) {
+            System.out.println("predict failed.");
+            return ;
+        }
+
+        for (Map.Entry<String, INDArray> e : fetch_map.entrySet()) {
+            System.out.println("Key = " + e.getKey() + ", Value = " + e.getValue());
+        }
+        return ;
+    }
+}
+```
+