[docs] fix typos in quickstart and CEP docs

This closes apache#1663

docs/apis/streaming/libs/cep.md

@@ -60,7 +60,7 @@ Pattern<Event, ?> pattern = Pattern.begin("start").where(evt -> evt.getId() == 4
     .next("middle").subtype(SubEvent.class).where(subEvt -> subEvt.getVolume() >= 10.0)
     .followedBy("end").where(evt -> evt.getName().equals("end"));
 
-PatternStream<Event> patternStream = CEP.from(input, pattern);
+PatternStream<Event> patternStream = CEP.pattern(input, pattern);
 
 DataStream<Alert> result = patternStream.select(pattern -> {
     return createAlertFrom(pattern);
@@ -216,7 +216,7 @@ Given an input stream `input` and a pattern `pattern`, you create the `PatternSt
 DataStream<Event> input = ...
 Pattern<Event, ?> pattern = ...
 
-PatternStream<Event> patternStream = CEP.from(input, pattern);
+PatternStream<Event> patternStream = CEP.pattern(input, pattern);
 {% endhighlight %}
 
 ### Selecting from Patterns
@@ -280,7 +280,7 @@ Pattern<Event, ?> pattern = Pattern.<Event>begin("start")
 	.next("middle").where(new FilterFunction<Event>() {
 		@Override
 		public boolean filter(Event value) throws Exception {
-			return value.getName().equals("name");
+			return value.getName().equals("error");
 		}
 	}).followedBy("end").where(new FilterFunction<Event>() {
 		@Override

docs/quickstart/java_api_quickstart.md

@@ -65,21 +65,21 @@ There will be a new directory in your working directory. If you've used the _cur
 
 The sample project is a __Maven project__, which contains two classes. _Job_ is a basic skeleton program and _WordCountJob_ a working example. Please note that the _main_ method of both classes allow you to start Flink in a development/testing mode.
 
-We recommend to __import this project into your IDE__ to develop and test it. If you use Eclipse, the [m2e plugin](http://www.eclipse.org/m2e/) allows to [import Maven projects](http://books.sonatype.com/m2eclipse-book/reference/creating-sect-importing-projects.html#fig-creating-import). Some Eclipse bundles include that plugin by default, other require you to install it manually. The IntelliJ IDE also supports Maven projects out of the box.
+We recommend to __import this project into your IDE__ to develop and test it. If you use Eclipse, the [m2e plugin](http://www.eclipse.org/m2e/) allows to [import Maven projects](http://books.sonatype.com/m2eclipse-book/reference/creating-sect-importing-projects.html#fig-creating-import). Some Eclipse bundles include that plugin by default, others require you to install it manually. The IntelliJ IDE also supports Maven projects out of the box.
 
 
 A note to Mac OS X users: The default JVM heapsize for Java is too small for Flink. You have to manually increase it. Choose "Run Configurations" -> Arguments and write into the "VM Arguments" box: "-Xmx800m" in Eclipse.
 
 ## Build Project
 
-If you want to __build your project__, go to your project directory and issue the`mvn clean install -Pbuild-jar` command. You will __find a jar__ that runs on every Flink cluster in __target/your-artifact-id-1.0-SNAPSHOT.jar__. There is also a fat-jar,  __target/your-artifact-id-1.0-SNAPSHOT-flink-fat-jar.jar__. This
+If you want to __build your project__, go to your project directory and issue the `mvn clean install -Pbuild-jar` command. You will __find a jar__ that runs on every Flink cluster in __target/your-artifact-id-1.0-SNAPSHOT.jar__. There is also a fat-jar,  __target/your-artifact-id-1.0-SNAPSHOT-flink-fat-jar.jar__. This
 also contains all dependencies that get added to the maven project.
 
 ## Next Steps
 
 Write your application!
 
-The quickstart project contains a WordCount implementation, the "Hello World" of Big Data processing systems. The goal of WordCount is to determine the frequencies of words in a text, e.g., how often do the terms "the" or "house" occurs in all Wikipedia texts.
+The quickstart project contains a WordCount implementation, the "Hello World" of Big Data processing systems. The goal of WordCount is to determine the frequencies of words in a text, e.g., how often do the terms "the" or "house" occur in all Wikipedia texts.
 
 __Sample Input__:
 
@@ -95,7 +95,7 @@ data 1
 is 1
 ~~~
 
-The following code shows the WordCount implementation from the Quickstart which processes some text lines with two operators (FlatMap and Reduce), and writes the prints the resulting words and counts to std-out.
+The following code shows the WordCount implementation from the Quickstart which processes some text lines with two operators (FlatMap and Reduce), and prints the resulting words and counts to std-out.
 
 ~~~java
 public class WordCount {
@@ -122,9 +122,6 @@ public class WordCount {
 
     // emit result
     counts.print();
-
-    // execute program
-    env.execute("WordCount Example");
   }
 }
 ~~~

docs/quickstart/scala_api_quickstart.md

@@ -90,7 +90,7 @@ also contains all dependencies that get added to the maven project.
 
 Write your application!
 
-The quickstart project contains a WordCount implementation, the "Hello World" of Big Data processing systems. The goal of WordCount is to determine the frequencies of words in a text, e.g., how often do the terms "the" or "house" occurs in all Wikipedia texts.
+The quickstart project contains a WordCount implementation, the "Hello World" of Big Data processing systems. The goal of WordCount is to determine the frequencies of words in a text, e.g., how often do the terms "the" or "house" occur in all Wikipedia texts.
 
 __Sample Input__:
 
@@ -106,7 +106,7 @@ data 1
 is 1
 ~~~
 
-The following code shows the WordCount implementation from the Quickstart which processes some text lines with two operators (FlatMap and Reduce), and writes the prints the resulting words and counts to std-out.
+The following code shows the WordCount implementation from the Quickstart which processes some text lines with two operators (FlatMap and Reduce), and prints the resulting words and counts to std-out.
 
 ~~~scala
 object WordCountJob {