here is the source code of the program
package kafka.examples;
import kafka.consumer.ConsumerConfig;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.message.Message;
import kafka.consumer.ConsumerIterator;
import java.util.HashMap;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.util.Properties;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.ExecutionException;
import java.io.*;
import java.util.Date;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
public class KafkaConsumerMultithread
{
private final ConsumerConnector consumer;
private final String topic;
private ExecutorService executor;
public static DateFormat dateFormat = new
SimpleDateFormat("yyyyMMddhhmmss");
//get current date time with Date()
public static Date date = new Date();
public static String filename = dateFormat.format(date)+"-topicname.csv";
public static long starttime = 0;
public static long endtime = 0;
public List<ConsumerPrintMessage> cpm_list;
public static class ConsumerPrintMessage implements Runnable
{
ConsumerIterator<Message> it;
int threadNumber;
public long messageCount=0;
ConsumerPrintMessage(KafkaStream<Message> stream, int threadNumber)
{
it = stream.iterator();
this.threadNumber = threadNumber;
}
public void run()
{
try
{
while(it.hasNext())
{
System.out.println("\nThread Consuming Data : "+threadNumber+"\n");
String msg = "";
msg = ExampleUtils.getMessage(it.next().message()) ;
this.messageCount++;
if(System.currentTimeMillis() >= starttime+36000000)
{
System.out.println("\n\n Code to Send data to hdfs is commented - uncomment
\n\n");
System.out.println("\n\nNext Hour Data \n\n");
date = new Date();
filename = dateFormat.format(date)+"-topicname.csv";
starttime = System.currentTimeMillis();
}
}
}
catch(Exception ex)
{
ex.printStackTrace();
System.out.println("\n\t\t\tError : IO Exception : Unable to write data to
temp.\n");
}
}
}
public KafkaConsumerMultithread(String a_zookeeper, String a_groupId,
String a_topic)
{
consumer =
kafka.consumer.Consumer.createJavaConsumerConnector(createConsumerConfig(a_zookeeper,
a_groupId));
this.topic = a_topic;
}
/* To shutdown consumer and producer */
public void shutdown()
{
int count = 0;
// get the total message count
for(int i = 0; i<cpm_list.size();i++){
ConsumerPrintMessage cpm = cpm_list.get(i);
count+=cpm.messageCount;
}
System.out.println("MessageCount : "+count);
//System.out.println("consumer : "+consumer);
//System.out.println("executer : "+executor);
System.out.println("thread job");
System.out.println("end time :"+ ( System.currentTimeMillis() - starttime )
);
if (consumer != null)
{
consumer.shutdown();
}
if (executor != null)
{
executor.shutdown();
}
}
public void run(int a_numThreads)
{
Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
topicCountMap.put(topic, new Integer(a_numThreads));
Map<String, List<KafkaStream<Message>>> consumerMap =
consumer.createMessageStreams(topicCountMap);
List<KafkaStream<Message>> streams = consumerMap.get(topic);
// now launch all the threads
//
executor = Executors.newFixedThreadPool(a_numThreads);
// now create an object to consume the messages
//
int threadNumber = 0;
//Future< ? > fut_1 = null;
starttime = System.currentTimeMillis();
cpm_list = new ArrayList<ConsumerPrintMessage>();
for (final KafkaStream<Message> stream : streams)
{
//fut_1 =
ConsumerPrintMessage cx = new ConsumerPrintMessage(stream,
threadNumber);
cpm_list.add(cx);
executor.submit(cx);
threadNumber++;
}
}
private static ConsumerConfig createConsumerConfig(String a_zookeeper,
String a_groupId)
{
Properties props = new Properties();
//props.put("broker.list", "1:192.168.0.46:9092,2:192.168.0.47:9092");
props.put("zk.connect", a_zookeeper);
props.put("groupid", a_groupId);
props.put("zk.sessiontimeout.ms", "400");
props.put("zk.synctime.ms", "200");
props.put("autocommit.interval.ms", "1000");
return new ConsumerConfig(props);
}
public static void main(String[] args)
{
/*
Note : This part specifies your consumer properties - dynamic
Uncomment following lines for specifying values dynamically
execution : KafkaConsumerMultithread <zk: arg[0]> <gid: arg[1]> <topic:
arg[2]> <num_threads: arg[3]>
*/
/*
String zooKeeper = args[0]; // First argument is your zookeer
connection address
String groupId = args[1]; // Second argument will be your
groupid
String topic = args[2]; // Third argument topic to consume
int threads = Integer.parseInt(args[3]); // Fourth argument Number
of threads to run
*/
/*
Note : This part specifies your consumer properties - hard coded
*/
String zooKeeper = "zoo1:2181,zoo2:2181,zoo3:2181";
String groupId = "group1";
String topic = "topic1";
int threads = Integer.parseInt(args[4]);
//Process mktemp = Runtime.getRuntime().exec("mkdir temp");
KafkaConsumerMultithread example = new
KafkaConsumerMultithread(zooKeeper, groupId, topic);
example.run(threads);
try
{
System.out.println("main thread going to sleep for 10 seconds");
Thread.sleep(900);
}
catch (InterruptedException ie)
{
System.out.println("\n\nNote : Execution Interrupted..!!\n\n");
}
System.out.println("main thread woke up");
example.shutdown();
}
}
On Mon, Jul 8, 2013 at 8:43 PM, Anurup Raveendran <
[email protected]> wrote:
> 305 bytes
>
>
> On Mon, Jul 8, 2013 at 8:41 PM, Tom Brown <[email protected]> wrote:
>
>> What is the size of each message?
>>
>> --Tom
>>
>>
>> On Mon, Jul 8, 2013 at 9:04 AM, Anurup Raveendran <
>> [email protected]> wrote:
>>
>> > I have 2 kafka brokers running on two systems with the same
>> configuration
>> >
>> > CPU - Dual Core
>> > RAM - 4 GB
>> >
>> > I'm trying to benchmark my kafka setup
>> > Number of messages - 10000
>> >
>> > for 2 partitions & 2 threads configuration - consumer consumes in 1.175
>> > seconds
>> >
>> > for 1 partition & 1 thread configuration - consumer consumes in 1.253
>> > seconds
>> >
>> > Is there some specific configuration which would enable better
>> throughput?
>> >
>> >
>> >
>> >
>>
>
>
