[streaming] python script added for performance visualization

flink-addons/flink-streaming/src/main/java/eu/stratosphere/streaming/util/PerformanceTimer.java

@@ -20,16 +20,17 @@ public class PerformanceTimer extends PerformanceTracker {
 	long timer;
 	boolean millis;
 
-	public PerformanceTimer(String name, int counterLength, int countInterval) {
+	public PerformanceTimer(String name, int counterLength, int countInterval, boolean millis) {
 		super(name, counterLength, countInterval);
+		this.millis = millis;
 	}
 
-	public PerformanceTimer(String name) {
+	public PerformanceTimer(String name, boolean millis) {
 		super(name);
+		this.millis = millis;
 	}
 
-	public void startTimer(boolean millis) {
-		this.millis = millis;
+	public void startTimer() {
 		if (millis) {
 			timer = System.currentTimeMillis();
 		} else {
@@ -38,10 +39,6 @@ public class PerformanceTimer extends PerformanceTracker {
 
 	}
 
-	public void startTimer() {
-		startTimer(true);
-	}
-
 	public void stopTimer(String label) {
 
 		if (millis) {

flink-addons/flink-streaming/src/test/java/eu/stratosphere/streaming/util/PerformanceTrackerTest.java

@@ -94,9 +94,9 @@ public class PerformanceTrackerTest {
 
 	@Test
 	public void testTimer() throws InterruptedException {
-		PerformanceTimer pT = new PerformanceTimer("timer");
+		PerformanceTimer pT = new PerformanceTimer("timer",true);
 
-		pT.startTimer(true);
+		pT.startTimer();
 		Thread.sleep(100);
 		pT.stopTimer();
 

flink-addons/flink-streaming/src/test/resources/Performance/PerformanceTracker.py

+# -*- coding: utf-8 -*-
+"""
+Created on Wed Apr 30 15:40:17 2014
+
+@author: gyfora
+"""
+
+import matplotlib.pyplot as plt
+import pandas as pd
+import os
+
+def plotPerformance(csv_dir):
+    csv_dir=csv_dir
+    dataframes={}
+    
+    for fname in os.listdir(csv_dir):
+        if '.csv' in fname:
+            df=pd.read_csv(os.path.join(csv_dir,fname),index_col='Time')
+            speed=[0]
+            values=list(df.ix[:,0])
+            for i in range(1,len(values)):
+                speed.append(float(values[i]-values[i-1])/float(df.index[i]-df.index[i-1]))
+            df['speed']=speed    
+            dataframes[fname.rstrip('.csv')]=df
+            
+    plt.figure(figsize=(12, 8), dpi=80)
+    plt.title('Values')
+    
+    for name in dataframes.keys():
+        dataframes[name].ix[:,0].plot()
+    plt.legend(dataframes.keys())
+    
+    plt.figure(figsize=(12, 8), dpi=80)
+    plt.title('dV/dT')
+
+    for name in dataframes.keys():
+        dataframes[name].speed.plot()
+    plt.legend(dataframes.keys())