Merge branch 'colored-errors' into wescheme2012-master

.settings/com.google.appengine.eclipse.core.prefs

@@ -1,6 +1,5 @@
-#Mon Jun 18 14:30:52 EDT 2012
 eclipse.preferences.version=1
-filesCopiedToWebInfLib=jsr107cache-1.1.jar|appengine-jsr107cache-1.6.6.jar|appengine-api-labs-1.6.6.jar|appengine-api-1.0-sdk-1.6.6.jar|geronimo-jta_1.1_spec-1.1.1.jar|datanucleus-jpa-1.1.5.jar|datanucleus-appengine-1.0.10.final.jar|datanucleus-core-1.1.5.jar|geronimo-jpa_3.0_spec-1.1.1.jar|jdo2-api-2.3-eb.jar
+filesCopiedToWebInfLib=appengine-api-labs.jar|appengine-endpoints.jar|jsr107cache-1.1.jar|appengine-jsr107cache-1.7.0.jar|appengine-api-1.0-sdk-1.7.0.jar|geronimo-jta_1.1_spec-1.1.1.jar|datanucleus-jpa-1.1.5.jar|datanucleus-appengine-1.0.10.final.jar|datanucleus-core-1.1.5.jar|geronimo-jpa_3.0_spec-1.1.1.jar|jdo2-api-2.3-eb.jar
 gaeDeployDialogSettings=
 gaeIsEclipseDefaultInstPath=true
 googleCloudSqlEnabled=false

cost-analysis.txt

@@ -0,0 +1,32 @@
+We make estimates based on previous usage, in particular blips where
+our usage went past free limits.  I'm paying about $2.10 a week at the
+moment.
+
+
+
+According to AppEngine's logs, we do exceed these limits fairly
+frequently.  Especially on:
+
+2012-06-20
+2012-06-21
+2012-06-22
+2012-06-14
+
+On the week of 6/18-6-22, I paid $2.65.
+
+
+
+On those days, the most significant costs were:
+
+    frontend instance hours (around 40 hours)
+    datastore reads (about half a million read requests)
+
+Frontend instance hours being high means multiple AppEngine servers
+needed to be spun up to support the load at that time, and corresponds
+roughly with server load.  It contributes the highest amount (70%) of
+our costs.  Datastore reads cover the next largest chunk of our costs
+(28%).
+
+
+On our worst day (2012-06-22), we used $1.19 out of our reserved
+$2.00.

doc/ec2-auto-scaling-notes.txt

@@ -0,0 +1,61 @@
+EC2 Auto scaling notes
+
+
+Creating the launch configuration:
+
+    $ as-create-launch-config LaunchConfig-East-20120808 --image-id ami-9fde74f6 --instance-type m1.medium --group quicklaunch-1 --region us-east-1
+    $ as-create-launch-config LaunchConfig-West-20120808 --image-id ami-a8038c98 --instance-type m1.medium --group quicklaunch-1 --region us-west-2
+
+
+
+
+Creating the auto-scaling groups, attached to a particular load balancer:
+
+    $ as-create-auto-scaling-group WeSchemeCompilerGroup-West --launch-configuration LaunchConfig-West-20120808 --availability-zones us-west-2a --min-size 1 --max-size 10 --load-balancers balanced-wescheme-compilers
+
+    $ as-create-auto-scaling-group WeSchemeCompilerGroup-East --launch-configuration LaunchConfig-East-20120808 --availability-zones us-east-1c --min-size 1 --max-size 10 --load-balancers LoadBalancerEast --region us-east-1
+
+
+
+
+Creating the policies for adding a new instances to these group:
+
+    $ as-put-scaling-policy MyScaleUpPolicy --auto-scaling-group WeSchemeCompilerGroup-West --adjustment=1 --type ChangeInCapacity --cooldown 300 --region us-west-2
+
+    $ as-put-scaling-policy MyScaleUpPolicy --auto-scaling-group WeSchemeCompilerGroup-East --adjustment=1 --type ChangeInCapacity --cooldown 300 --region us-east-1
+
+
+
+Adding a CloudWatch alarm that will trigger this scaling-up policy on high load.  5 minutes at 80% CPU:
+
+    $ mon-put-metric-alarm MyHighCPUAlarm --comparison-operator GreaterThanThreshold --evaluation-periods 1 --metric-name CPUUtilization --namespace "AWS/EC2" --period 300 --statistic Average --threshold 80 --alarm-actions  arn:aws:autoscaling:us-west-2:093537034380:scalingPolicy:0c0d1a8a-8828-4395-99ae-8fb35b098e85:autoScalingGroupName/WeSchemeCompilerGroup:policyName/MyScaleUpPolicy --dimensions "AutoScalingGroupName=WeSchemeCompilerGroup" --region us-west-2
+
+    $ mon-put-metric-alarm MyHighCPUAlarm --comparison-operator GreaterThanThreshold --evaluation-periods 1 --metric-name CPUUtilization --namespace "AWS/EC2" --period 300 --statistic Average --threshold 80 --alarm-actions arn:aws:autoscaling:us-east-1:093537034380:scalingPolicy:62cdf7ae-1d9e-4436-bc77-603c00f63e5f:autoScalingGroupName/WeSchemeCompilerGroup-East:policyName/MyScaleUpPolicy --dimensions "AutoScalingGroupName=WeSchemeCompilerGroup-East" --region us-east-1
+
+
+
+
+Creating the other policy for dropping instances:
+
+    $ as-put-scaling-policy MyScaleDownPolicy --auto-scaling-group WeSchemeCompilerGroup-West --adjustment=-1 --type ChangeInCapacity --cooldown 300 --region us-west-2
+
+    $ as-put-scaling-policy MyScaleDownPolicy --auto-scaling-group WeSchemeCompilerGroup-East --adjustment=-1 --type ChangeInCapacity --cooldown 300 --region us-east-1
+
+and adding the corresponding CloudWatch alarms on idleness:
+
+
+    $ mon-put-metric-alarm MyLowCPUAlarm --comparison-operator LessThanThreshold --evaluation-periods=1 --metric-name CPUUtilization --namespace "AWS/EC2" --period 300 --statistic Average --threshold 40 --alarm-actions arn:aws:autoscaling:us-west-2:093537034380:scalingPolicy:3a6b57eb-c9c2-4360-8de8-5056b414c66b:autoScalingGroupName/WeSchemeCompilerGroup:policyName/MyScaleDownPolicy --dimensions "AutoScalingGroupName=WeSchemeCompilerGroup" --region us-west-2
+
+    $ mon-put-metric-alarm MyLowCPUAlarm --comparison-operator LessThanThreshold --evaluation-periods=1 --metric-name CPUUtilization --namespace "AWS/EC2" --period 300 --statistic Average --threshold 40 --alarm-actions arn:aws:autoscaling:us-east-1:093537034380:scalingPolicy:b09438e3-8e77-4e20-9e03-40484c295922:autoScalingGroupName/WeSchemeCompilerGroup-East:policyName/MyScaleDownPolicy --dimensions "AutoScalingGroupName=WeSchemeCompilerGroup-East" --region us-east-1
+
+
+----------------------------------------------------------------------
+
+Changing the launch configuration:
+
+1.  Make sure to add an instance to each load balancer to account for
+    the disappearance of the auto-scaling group.
+
+2.  Shut down existing instances by updating the max and min size of
+    the groups down to zero.
+

src/org/wescheme/data/DAO.java

@@ -0,0 +1,20 @@
+package org.wescheme.data;
+
+import com.googlecode.objectify.ObjectifyService;
+import com.googlecode.objectify.util.DAOBase;
+
+/** Data Access Object for all the data we're managing with Objectify.
+ * 
+ * @author dyoo
+ *
+ */
+
+public class DAO extends DAOBase {
+	static {
+		ObjectifyService.register(Feedback.class);
+	}
+
+	public void saveFeedback(Feedback feedback) {
+		ofy().put(feedback);
+	}	
+}

src/org/wescheme/data/Feedback.java

@@ -0,0 +1,53 @@
+package org.wescheme.data;
+
+import java.util.Date;
+
+import javax.persistence.Id;
+
+import org.json.simple.JSONObject;
+
+import com.googlecode.objectify.annotation.Unindexed;
+
+
+/** Represents feedback we get back from WeScheme users.
+ *  The content is unstructured for the most part; we may want
+ *  to enforce some structure later one to help with data mining.
+ * @author dyoo
+ *
+ */
+
+public class Feedback {
+	@Id Long id;
+	@Unindexed String author;
+	String type;
+	@Unindexed String feedbackText;
+	Date date;
+
+	// NoArg constructor for Objectify.
+	Feedback() {}
+
+	public Feedback(String author, String type, String feedbackText) {
+		this.author = author;
+		this.type = type;
+		this.feedbackText = feedbackText;
+		this.date = new Date();
+	}
+
+
+
+	public String getAuthor() { return this.author; }
+	public String getType() { return this.type; }
+	public String getFeedbackText() { return this.feedbackText; }
+
+
+	public JSONObject toJSONObject() {
+		JSONObject obj = new JSONObject();
+		obj.put("id", this.id);
+		obj.put("author", this.author);
+		obj.put("type", this.type);
+		obj.put("feedbackText", this.feedbackText);
+		// date is represented at amount of milliseconds since the epoch.
+		obj.put("date", this.date.getTime());
+		return obj;
+	}
+}

src/org/wescheme/keys/Schedule.java

@@ -23,7 +23,6 @@ public class Schedule implements Serializable {
 	 * 
 	 */
 	private static final long serialVersionUID = -1498658908860600498L;
-	@SuppressWarnings("unused")
 	@PrimaryKey
 	@Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY)
 	private Key key;

src/org/wescheme/project/AndroidPackage.java

@@ -21,7 +21,6 @@ public class AndroidPackage implements Serializable {
 	 */
 	private static final long serialVersionUID = 1636299813888198554L;
 
-	@SuppressWarnings("unused")
 	@PrimaryKey
     @Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY)
     private Key key;

src/org/wescheme/project/AndroidPackageJob.java

@@ -29,7 +29,6 @@ public class AndroidPackageJob implements Serializable {
 	 */
 	private static final long serialVersionUID = 2257895943724927957L;
 
-	@SuppressWarnings("unused")
 	@PrimaryKey
     @Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY)
     private Long id;

src/org/wescheme/project/SourceCode.java

@@ -21,7 +21,6 @@ public class SourceCode implements Serializable{
 	 */
 	private static final long serialVersionUID = -6657496787529704087L;
 
-	@SuppressWarnings("unused")
 	@PrimaryKey
     @Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY)
     private Key key;

src/org/wescheme/servlet/AddFeedback.java

@@ -0,0 +1,29 @@
+package org.wescheme.servlet;
+
+import java.io.IOException;
+
+import javax.servlet.ServletException;
+import javax.servlet.http.HttpServlet;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import org.wescheme.data.DAO;
+import org.wescheme.data.Feedback;
+
+public class AddFeedback extends HttpServlet {
+	/**
+	 * 
+	 */
+	private static final long serialVersionUID = -7686196925524722519L;
+
+	public void doPost(HttpServletRequest request, HttpServletResponse response) throws IOException, ServletException {
+		String author = request.getParameter("author");
+		String type = request.getParameter("type");
+		String feedbackText = request.getParameter("feedbackText");
+		Feedback feedback = new Feedback(author, type, feedbackText);
+		new DAO().saveFeedback(feedback);
+
+		response.setContentType("text/plain");
+		response.getWriter().write("ok");
+	}
+}

src/org/wescheme/servlet/DumpFeedback.java

@@ -0,0 +1,87 @@
+package org.wescheme.servlet;
+
+import java.io.IOException;
+
+import javax.servlet.ServletException;
+import javax.servlet.http.HttpServlet;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import org.json.simple.JSONArray;
+import org.json.simple.JSONObject;
+import org.wescheme.data.DAO;
+import org.wescheme.data.Feedback;
+import org.wescheme.user.Session;
+import org.wescheme.user.SessionManager;
+
+import com.google.appengine.api.datastore.Cursor;
+import com.google.appengine.api.datastore.QueryResultIterator;
+import com.googlecode.objectify.Objectify;
+import com.googlecode.objectify.ObjectifyService;
+import com.googlecode.objectify.Query;
+
+/**
+ * Retrieve all the feedback we get back from users.
+ * Output is represented as an JSON string:
+ * { feedbacks: [{ author: string, type: string: feedbackText: string, date: string} ...],
+ *   cursor: string }
+ *
+ * The optional "cursor" argument here will allow us to stream
+ * the table, just in case it gets large enough to hit against
+ * the compute ceiling enforced by AppEngine.
+ *
+ * Only admins should be allowed to get at this information.
+ * 
+ * This code is adapted from http://code.google.com/p/objectify-appengine/wiki/IntroductionToObjectify
+ * @author dyoo
+ *
+ */
+public class DumpFeedback extends HttpServlet {
+
+	public static final long LIMIT_MILLIS = 1000 * 25; // provide a little leeway
+
+
+	public void doGet(HttpServletRequest request, HttpServletResponse response) throws IOException, ServletException {
+		// First, check that the person is admin.
+		SessionManager sm = new SessionManager();
+		Session userSession = sm.authenticate(request, response);
+		if (!userSession.isAdmin()) {
+			response.sendError(401);
+			return;
+		}
+
+		// Side effect: force loading of the classes.
+		DAO dao = new DAO();
+
+
+		// Next, start dumping content till we hit CPU limit
+		long startTime = System.currentTimeMillis();
+		Objectify ofy = ObjectifyService.begin();
+		Query<Feedback> query = ofy.query(Feedback.class);
+		String cursorStr = request.getParameter("cursor");
+		if (cursorStr != null) {
+			query.startCursor(Cursor.fromWebSafeString(cursorStr));
+		}
+
+		JSONArray listOfFeedbacks = new JSONArray();
+		String nextCursorString = null;
+
+		QueryResultIterator<Feedback> iterator = query.iterator();
+		while(iterator.hasNext()) {
+			Feedback feedback = iterator.next();
+			listOfFeedbacks.add(feedback.toJSONObject());
+			if (System.currentTimeMillis() - startTime > LIMIT_MILLIS) {
+				nextCursorString = iterator.getCursor().toWebSafeString();
+				break;
+			}
+		}
+
+		// Finally, dump the content back to the user.
+		JSONObject result = new JSONObject();
+		result.put("feedbacks", listOfFeedbacks);
+		result.put("cursor", nextCursorString);
+		response.setContentType("text/plain");
+		response.getWriter().write(result.toString());
+	}
+
+}

src/org/wescheme/user/WeSchemeUser.java

@@ -31,7 +31,6 @@ public class WeSchemeUser{
     private byte[] _digest;			// the hash of the salted password
 	@Persistent
 	private boolean _active;		// is the account active?
-	@SuppressWarnings("unused")
 	@Persistent
 	private String _email;
 

war-src/js/ajaxactions.js

@@ -173,4 +173,25 @@ goog.require('plt.wescheme.Program');
 		     xhr: function(settings) { return new XMLHttpRequest(settings); }
 		    });
     };
+
+
+    plt.wescheme.AjaxActions.prototype.sendFeedback = function(author, type, feedbackText, onSuccess) {
+	jQuery.ajax({cache : false,
+  		     data : {author : author,
+                             type : type,
+                             feedbackText : feedbackText },
+                     datatype: "text",
+                     type: "POST",
+                     url: "/addFeedback",
+                     success: function(data) {
+                         onSuccess();
+                     },
+                     error: function(xhr) {
+                         onSuccess();
+                     },
+		     xhr: function(settings) { return new XMLHttpRequest(settings); }
+                    });
+
+    };
+
 })();