It was, IIRC, only 3 C++ classes and just a few hundred lines of code. It outsourced much of the distribution, task running, and disk-access tasks to other Google infrastructure, and only focused on running the computation, collecting results for each key, and distributing to the reducers.
The current (as of ~2012, so not that current anymore) version of MapReduce is much faster and more reliable, but there's a certain elegance to starting a trillion-dollar industry with a few hundred lines of code.
There was another doozy, also by Jeff Dean, in the current (again, as of 2012) MapReduce code. It was an external sorting algorithm, and like most external sorts, it worked by writing a bunch of whole-machine-RAM sized temporary files and then performing an N-way merge. But how did it sort the machine's RAM? Using the STL qsort() function, of course! But how do you sort ~64GB of data efficiently using a standard-library function? He'd written a custom comparator that compared whole records at a time, using IIRC compiler intrinsics that compiled down into SIMD instructions and did some sort of Duff's-Device like unrolling to account for varying key lengths. It was a very clever mix of stock standard library functions with highly-optimized, specialized code.