diff --git a/perf/README.md b/perf/README.md
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+# Apache Kafka 
+
+## Performance testing
+
+To run the Kafka performance tests you can update the server.properties to dump the metrics of the test to CSV files.
+
+Add this to your brokers' server.properties file setting the values approriate for your enviornment.
+
+    kafka.metrics.polling.interval.secs=5
+    kafka.metrics.reporters=kafka.metrics.KafkaCSVMetricsReporter
+    kafka.csv.metrics.dir=/tmp/kafka_metrics
+    kafka.csv.metrics.reporter.enabled=true
+
+Before running the tests decide on what settings make the test valid for your implementation for producers and consumers.
+
+    bin/kafka-producer-perf-test.sh --help
+    bin/kafka-consumer-perf-test.sh --help
+    
+You may want to review the wiki page on performance testing https://cwiki.apache.org/confluence/display/KAFKA/Performance+testing for more detail about this or review the help that each test provides from the command line.
+
+After you have run your tests and you have your CSV results you can now graph the metrics using the `draw-performance-graphs.r` script.
+
+You need to have R http://www.r-project.org/ installed and X11 too (for Mac users this is no longer shipped by Apple but available here http://xquartz.macosforge.org/landing/)
+
+Once these are installed then you can go to the folder where your metrics csv where created (e.g. /tmp/kafka_metrics) and then run the script (assuming you have kafka cloned e.g. /opt/apache/kafka)
+
+    cd /tmp/kafka_metrics
+    RScript /opt/apache/kafka/perf/draw-performance-graphs.r TRUE Produce-RequestsPerSec.csv
+    
+This will generate an image of all metrics in one png and also a png for each metric seperatly (metrics being total count, total mean, 1min, 5min, 15min moving averages)
+
+If you want to generate a graph for more than one CSV file then add it as another argument to the command line.
+
+    RScript /opt/apache/kafka/perf/draw-performance-graphs.r TRUE Produce-RequestsPerSec.csv test-MessagesInPerSec.csv
+    
+If you want to generate pngs for every CSV in the directory then run
+
+    RScript /opt/apache/kafka/perf/draw-performance-graphs.r FALSE
diff --git a/perf/draw-performance-graphs.r b/perf/draw-performance-graphs.r
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+#!/usr/bin/env Rscript 
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+# 
+#    http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+#needed functions
+plotAndSummarize <- function(topicName,data){
+	timeIndex <- grep("time",colnames(data))
+	time <- data[,timeIndex[1]]
+	subset <- data.frame(data[,-c(timeIndex)])##subset of data that isn't time
+	numCols <- length(colnames(subset))
+	
+	png(paste(topicName,".png",sep = ""), width = 800, height = 800*numCols)
+	par(mfrow=c(numCols,1))
+	for(i in 1:numCols){
+		## time series
+		plot(time, subset[,i], xlab = "time", ylab = colnames(subset)[i], main = paste(topicName,colnames(subset)[i], sep = " "), type = "l")
+	}
+	dev.off()
+
+	names <- colnames(subset)
+	for(i in 1:numCols){
+			## time series
+		png(paste(topicName,"_",names[i],".png",sep = ""), width = 800, height = 800)
+		plot(time, subset[,i], xlab = "time", ylab = colnames(subset)[i], main = paste(topicName,colnames(subset)[i], sep = " "), type = "l")
+		dev.off()
+	}
+}
+
+testingMetrics <- function(topicName, path){
+	data <- read.csv(path, header = TRUE, sep = ",")
+	numCols <- length(colnames(data))
+	if(sum(grep("time",colnames(data)))>0){
+		plotAndSummarize(topicName, data)
+	} else{
+		stop("Missing time arg.")
+	}
+}
+
+strippedName <- function(files){
+	names <- files
+	for (i in 1:length(names)){
+		names[i] = read.table(text = names[i], sep = ".", as.is = TRUE)$V1
+	}
+	names
+}
+
+args <- commandArgs(TRUE)
+
+if(args[1]){
+	files <- args[-1]
+	fileNames <- strippedName(args[-1])
+	for(i in 1:length(files)){
+		if(sum(grep(".csv",files[i]) == 1)) testingMetrics(fileNames[i],files[i])
+	}
+} else{
+	files <- list.files() #assume r is running in the same directory as the files
+	fileNames <- strippedName(files)
+	for(i in 1:length(files)){
+		if(sum(grep(".csv",files[i]) == 1)) testingMetrics(fileNames[i],files[i])
+	}
+}
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