kafka producer示例代码是：

# !/usr/bin/env python

# -*- coding: utf-8 -*-

import ConfigParser as configparser
from pykafka import KafkaClient
import time
import snappy

config = configparser.ConfigParser()
config.read("conf.ini")

app_name = "test_word_counter"
kafka_hosts = config.get(app_name, 'kafka_hosts')
kafka_topic = config.get(app_name, 'kafka_topic')
print("kafka client: %s" % kafka_hosts)
print("kafka topic: %s" % kafka_topic)

kafka_client = KafkaClient(hosts=kafka_hosts)  # Create Kafka client
topic = kafka_client.topics[kafka_topic]  # This will create the topic if it does not exist

with topic.get_producer() as producer:  # Create Kafka producer on the given topic
    while True:
        msg = "just a test for snappy compress with kafka and spark"
        msg = snappy.compress(msg) # add snappy compress
        producer.produce(msg) # Send the message to Kafka
        print("send data len(%d)" % len(msg))
        print(msg)
        time.sleep(5)

代码非常简单，使用python snappy，压缩数据，然后把它放到kafka中。
Pypark代码是：

def word_counter(zk_host, topic):
    sc = SparkContext(appName="PythonStreamingKafkaWordCounter")
    sc = SparkContext(conf=spark_conf)
    ssc = StreamingContext(sc, 30) 

    kvs = KafkaUtils.createStream(ssc, zk_host, "spark-streaming-consumer", {topic: 2}) 
    lines = kvs.map(lambda x: x[1])
    counts = lines.flatMap(lambda line: line.split(" ")) \
        .map(lambda word: (word, 1)) \
        .reduceByKey(lambda a, b: a+b)

    counts.pprint()
    ssc.start()
    ssc.awaitTermination()

然后，运行spark commit：

spark-submit --jars /usr/local/services/metrics-spark-analyser/external/spark-streaming-kafka-0-8-assembly_2.11-2.0.2.jar spark_word_counter_consumer.py

我收到了以下错误消息：

UnicodeDecodeError: 'utf8' codec can't decode byte 0xcc in position 1: invalid continuation byte

更详细的错误代码如下：

16/12/18 13:58:30 ERROR Executor: Exception in task 5.0 in stage 7.0 (TID 30)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/worker.py", line 172, in main
    process()
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/worker.py", line 167, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 2371, in pipeline_func
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 2371, in pipeline_func
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 317, in func
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/rdd.py", line 1792, in combineLocally
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/shuffle.py", line 236, in mergeValues
    for k, v in iterator:
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/streaming/kafka.py", line 73, in <lambda>
  File "/usr/local/services/spark/python/lib/pyspark.zip/pyspark/streaming/kafka.py", line 36, in utf8_decoder
    return s.decode('utf-8')
  File "/usr/local/services/python/lib/python2.7/encodings/utf_8.py", line 16, in decode
    return codecs.utf_8_decode(input, errors, True)
UnicodeDecodeError: 'utf8' codec can't decode byte 0xcc in position 1: invalid continuation byte

似乎spark streaming无法从kafka中解压缩快速的数据。
我是否应该在spark中添加任何配置？
谢谢~
软件详细信息：
Kafka0.10.1.0
Hadoop2.7的每个版本spark 2.0.2
python snappy 0.5版
附言：
我写了一个简单的Kafka消费程序来读取Kafka的snappy数据，snappy解压过程是成功的。