spark steaming with kafka, cannot receive all data - apache-spark

Question

In my spark streaming program, I try to receive data from kafka. In kafka producer, I send 1 million messages, but in the spark streaming, I cannot receive all the messages. It'll always loss some messages.
I start kafka-server with the default config.
Here is my producer's code:
val props = new HashMap[String, Object]()
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, brokers)
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringSerializer")
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringSerializer")
val producer = new KafkaProducer[String, String](props)
for (i <- 1 to loop_times.toInt) {
var cnt = 0
while (cnt < record_count.toInt) {
val message = new ProducerRecord[String, String](topic, null, "aaa")
producer.send(message)
cnt += 1
if (cnt % 10000 == 0)
println(s"send $cnt records")
}
}
producer.close()
and here is my spark streaming code(this code is in spark's example):
object KafkaWordCount {
def main(args: Array[String]) {
if (args.length < 4) {
System.err.println("Usage: KafkaWordCount <zkQuorum> <group> <topics> <numThreads>")
System.exit(1)
}
StreamingExamples.setStreamingLogLevels()
val Array(zkQuorum, group, topics, numThreads) = args
val sparkConf = new SparkConf().setAppName("KafkaWordCount")
val ssc = new StreamingContext(sparkConf, Seconds(2))
ssc.checkpoint("checkpoint")
val topicMap = topics.split(",").map((_, numThreads.toInt)).toMap
val lines = KafkaUtils.createStream(ssc, zkQuorum, group, topicMap).map(_._2)
val words = lines.flatMap(_.split(" "))
val wordCounts = words.map(x => (x, 1L))
.reduceByKeyAndWindow(_ + _, _ - _, Minutes(10), Seconds(2), 2)
wordCounts.print()
ssc.start()
ssc.awaitTermination()
}
}
My spark's version is 1.6 and kafka's is 0.8.2.1