The Anatomy of Hadoop I/O Pipeline (Hadoop and Distributed Computing at Yahoo!)Introduction In a typical Hadoop MapReduce job, input files are read from HDFS. Data are usually compressed to reduce the file sizes. After decompression, serialized bytes are transformed into Java objects before being passed to a user-defined map() function. Conversely, output records are serialized, compressed, and eventually pushed back to HDFS. This seemingly simple, two-way process is in fact
