Fix quick start and misc changes

mostroverkhov · Sep 12, 2014 · 64250f6 · 64250f6
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diff --git a/docs/manual/_data/nav_gettingstarted.yml b/docs/manual/_data/nav_gettingstarted.yml
@@ -3,12 +3,12 @@
 
 - title: "Quick Start"
  href: "/tutorials/engines/quickstart.html"
- 
+
 - title: "Collecting Data"
  href: "/dataapi.html"
- 
+
 - title: "Launching an Engine Instance"
  href: "/engines/"
 
-- title: "PredictionIO: Concepts and Design"
- href: "/predictionio.html"
+- title: "System Concepts and Design"
+ href: "/predictionio.html"
diff --git a/docs/manual/predictionio.md b/docs/manual/predictionio.md
@@ -1,6 +1,6 @@
 ---
 layout: docs
-title:  PredictionIO - Concepts and System Design
+title: System Concepts and System Design
 ---
 
 # PredictionIO - Concepts
@@ -28,4 +28,4 @@ A number of built-in algorithms are available for use in each type of engine. An
 
 PredictionIO is mainly built with Scala. Scala runs on the JVM, so Java and Scala stacks can be freely mixed for totally seamless integration. PredictionIO Server consists of a few components:
 
-* (TODO)
+* (TODO)
diff --git a/docs/manual/tutorials/engines/quickstart.md b/docs/manual/tutorials/engines/quickstart.md
@@ -5,13 +5,16 @@ title: Quick Start - Using a Built-in Engine
 
 # Quick Start - Using a Built-in Engine
 
-This is a quick start guide of using a PredictionIO's built-in engine and its SDKs to write a very simple app. It assumes that you have [installed PredictionIO server](/install/).
+This is a quick start guide of using a PredictionIO's built-in engine and its
+SDKs to write a very simple app. It assumes that you have [installed
+PredictionIO server](/install/).
 
-Let's start with a classic example in Machine Learning - build a recommendation engine. We are going to launch a recommendation engine instance that can:
+Let's start with a classic example in Machine Learning - build a recommendation
+engine. We are going to launch a recommendation engine instance that can:
 
-* collect *real-time event data* from your app through REST API or SDKs
-* update the predictive model with *new data* regularly and automatically
-* answer *prediction query* through REST API or SDKs 
+* collect *real-time event data* from your app through REST API or SDKs;
+* update the predictive model with *new data* regularly and automatically;
+* answer *prediction query* through REST API or SDKs.
 
 # Create a Simple App Project
 
@@ -73,14 +76,15 @@ $ php composer.phar install
 ## Launch the Data API Server
 
 ```
-$ cd $PIO_HOME
-$ bin/pio dataapi
+$ $PIO_HOME/bin/pio dataapi
 ```
-As long as the Data API server is running, PredictionIO keeps listening to new data.
+where `$PIO_HOME` is the installation directory of PredictionIO. As long as the
+Data API server is running, PredictionIO keeps listening to new data.
 
 ## Import Data
 
-We are going to write a script that generates some random data and simulates data collection. Data API can collect data from your application in real-time.
+We are going to write a script that generates some random data and simulates
+data collection. Data API can collect data from your application in real-time.
 In the `quickstartapp` directory:
 
 <div class="codetabs">
@@ -149,28 +153,48 @@ $ php import.php
 
 # Launch an Engine Instance
 
-Each engine deals with one specific prediction problem. For instance, Item Recommendation Engine (itemrec) is responsible for making personalized item (e.g. product or content) recommendation to each user.
+Each engine deals with one specific prediction problem. For instance, Item
+Recommendation Engine (itemrec) is responsible for making personalized item
+(e.g. product or content) recommendation to each user.
 
 > **What is an Engine Instance?**
 >
-> You can launch one or more `engine instance` from an engine. It means that you can run multiple recommendation engine instances at the same time with different settings, or even for different projects.
+> You can launch one or more *engine instance* from an engine. It means that you
+can run multiple recommendation *engine instances* at the same time with
+different settings, or even for different projects.
 
-To launch an engine instance for this simple app:
+To launch an engine instance for this simple app, first create an engine
+project:
 
 ```
-$ cd $PIO_HOME/engines/<TODO>
-$ bin/pio <TODO>
+$ $PIO_HOME/bin/pio new io.prediction.engines.itemrec
+$ cd io.prediction.engines.itemrec
 ```
 
-You can kick start the predictive model training with:
+Edit `params/datasource.json` and modify the value of `appId` to fit your app.
+
+Now, you can kick start the predictive model training with:
+
+```
+$ $PIO_HOME/bin/pio train
+...
+2014-09-11 16:25:44,591 INFO spark.SparkContext - Job finished: collect at Workflow.scala:674, took 0.078664 s
+2014-09-11 16:25:44,737 INFO workflow.CoreWorkflow$ - Saved engine instance with ID: KxOsC2FRSdGGe1lv0oaHiw
+```
+
+If your training was successful, you should see the lines shown above. Now you are ready to deploy the instance:
 
 ```
-$ bin/pio <TODO>
+$ $PIO_HOME/bin/pio deploy
+...
+[INFO] [09/11/2014 16:26:16.525] [pio-server-akka.actor.default-dispatcher-2] [akka:https://pio-server/user/IO-HTTP/listener-0] Bound to localhost/127.0.0.1:8000
+[INFO] [09/11/2014 16:26:16.526] [pio-server-akka.actor.default-dispatcher-5] [akka:https://pio-server/user/master] Bind successful. Ready to serve.
 ```
 
-Now we are ready to take a look at the results!
+Notice that the `deploy` command runs the engine instance in the foreground. Now
+we are ready to take a look at the results!
 
-# Retrieve Prediction Result 
+# Retrieve Prediction Results
 
 <div class="codetabs">
 <div data-lang="PHP SDK">
@@ -234,7 +258,7 @@ $ php show.php
 </div>
 </div>
 
-Well done! You have created a simple, but production-ready, app with PredictionIO recommendation engine.
+Well done! You have created a simple, but production-ready app with PredictionIO
+recommendation engine.
 
 Next: Learn more about [collecting data using Data API](/dataapi.html).
-