If input files are serialized with avro, unserialize them by org.apache.avro.mapred.AvroAsTextInputFormat in hadoop streaming.

hadoop_avro_job.sh

#!/usr/bin/env bash
# @(#) norm.sh  Time-stamp: <Julian Qian 2015-06-09 15:35:35>
# Copyright 2015 Julian Qian
# Author: Julian Qian <junist@gmail.com>
# Version: $Id: norm.sh,v 0.1 2015-06-08 18:03:30 jqian Exp $
#

day=$(date +%Y%m%d -d yesterday)
input=/user/hive/warehouse/query_log/ds=$day/hr=00

output=/user/work/query_log/ds=$day

hadoop fs -test -d $input

if [[ $? -eq 0 ]]; then

    jars=/usr/lib/avro/avro.jar,/usr/lib/avro/avro-mapred.jar
    hadoop jar /usr/lib/hadoop-mapreduce/hadoop-streaming.jar \
        -files $jars \
        -libjars $jars \
        -D mapred.reduce.tasks=5 \
        -D mapred.output.compress=true \
        -D mapred.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec \
        -input $input \
        -output $output \
        -mapper mapper.py \
        -reducer reducer.py \
        -file ./mapper.py \
        -file ./reducer.py \
        -inputformat org.apache.avro.mapred.AvroAsTextInputFormat \
        -partitioner org.apache.hadoop.mapred.lib.KeyFieldBasedPartitioner \
        -jobconf mapred.job.name="jqian:$output" \
        -jobconf map.output.key.field.separator=':' \
        -jobconf num.key.fields.for.partition=1
fi