Documentation

Change-Id: I9ba95e63ebc9f9d73847ff899517719a2ebc7502

doc/CLUSTERING.doc

+#搭建预测服务集群
+
+从[客户端配置](CLIENT_CONFIGURE.md)中我们已经知道，通过在客户端SDK的配置文件predictors.prototxt适当配置，可以搭建多副本和多Variant的预测集群。以下以图像分类任务为例，在单机上模拟搭建单Variant的多副本、和多Variant的预测集群
+
+## 1. 单Variant多副本的预测集群
+
+### 1.1 在本机创建一个serving副本
+
+首先复制一个sering目录
+
+```shell
+$ cd /path/to/paddle-serving/build/output/demo
+$ cp -r serving/ serving_new/
+$ cd serving_new/
+
+```
+
+在serving_new目录中，在conf/gflags.conf中增加如下一行，修改其启动端口为8011，这是为了让该副本监听不同端口
+
+```shell
+--port=8011
+```
+
+然后启动新副本
+
+```shell
+$ bin/serving&
+```
+
+### 1.2 修改client端配置，将新副本地址加入ip列表：
+
+```shell
+$ cd /path/to/paddle-serving/build/output/demo/client/image_classification
+```
+
+修改conf/predictors.prototxt ImageClassifyService部分如下所示
+
+```JSON
+predictors {
+  name: "ximage"
+  service_name: "baidu.paddle_serving.predictor.image_classification.ImageClassifyService"
+  endpoint_router: "WeightedRandomRender"
+  weighted_random_render_conf {
+    variant_weight_list: "50"
+  }
+  variants {
+    tag: "var1"
+    naming_conf {
+      cluster: "list://127.0.0.1:8010, 127.0.0.1:8011"  # 在这里增加一个新的副本地址
+    }
+  }
+}
+```
+
+重启client端
+
+```shell
+$ bin/ximage&
+```
+
+查看2个serving副本目录下是否均有收到请求：
+
+```shell
+$ cd /path/to/paddle-serving/build/output/demo/serving
+$ tail -f log/serving.INFO
+
+$ cd /path/to/paddle-serving/build/output/demo/serving_new
+$ tail -f log/serving.INFO
+```
+
+## 2. 多Variant
+
+### 2.1 本机创建新的serving副本
+
+步骤同1.1节，略过
+
+### 2.2 修改client配置，增加一个Variant
+
+```shell
+$ cd /path/to/paddle-serving/build/output/demo/client/image_classification
+```
+
+修改conf/predictors.prototxt ImageClassifyService部分如下所示
+
+```JSON
+predictors {
+  name: "ximage"
+  service_name: "baidu.paddle_serving.predictor.image_classification.ImageClassifyService"
+  endpoint_router: "WeightedRandomRender"
+  weighted_random_render_conf {
+    variant_weight_list: "50 | 50"      # 一共2个variant，代表模型的2个版本。这里的权重代表调度的流量比例关系
+  }
+  variants {
+    tag: "var1"
+    naming_conf {
+      cluster: "list://127.0.0.1:8010"
+    }
+  }
+  variants {                            # 增加一个variant
+    tag: "var2"
+    naming_conf {
+      cluster: "list://127.0.0.1:8011"
+    }
+  }
+}
+```
+
+重启client端
+
+```shell
+$ bin/ximage&
+```
+
+查看2个serving副本目录下是否均有收到请求：
+
+```shell
+$ cd /path/to/paddle-serving/build/output/demo/serving
+$ tail -f log/serving.INFO
+
+$ cd /path/to/paddle-serving/build/output/demo/serving_new
+$ tail -f log/serving.INFO
+```
+
+查看client端是否有收到来自Variant1和Variant2的响应
+
+```shell
+$ cd /path/to/paddle-serving/build/output/demo/client/image_classification
+$ tail -f log/ximage.INFO
+
+```
+
+以下是正常的输出
+
+```
+I0307 17:54:22.862087 24719 ximage.cpp:172] Debug string: 
+I0307 17:54:22.862650 24719 ximage.cpp:110] sample-0's classify result: n02112018,博美犬, prop: 0.522815
+I0307 17:54:22.862666 24719 ximage.cpp:114] Succ call predictor[ximage], the tag is: var1, elapse_ms: 333
+
+I0307 17:54:23.194780 24719 ximage.cpp:172] Debug string: 
+I0307 17:54:23.195322 24719 ximage.cpp:110] sample-0's classify result: n02112018,博美犬, prop: 0.522815
+I0307 17:54:23.195334 24719 ximage.cpp:114] Succ call predictor[ximage], the tag is: var2, elapse_ms: 332
+```

doc/INDEX.md

 
 [Client Configure](CLIENT_CONFIGURE.md)
 
+[How to Configure a Clustered Service](CLUSTERING.md)
+
 [Creating a Prediction Service](CREATING.md)
 
 [Design](DESIGN.md)