When running oprofile on a terasort workload, I noticed that a large amount of CPU usage was going to MapTask$MapOutputBuffer.compare. Upon disassembling this and looking at cycle counters, most of the cycles were going to memory loads dereferencing into the array of key-value data – implying expensive cache misses. This can be avoided as follows:
- rather than simply swapping indexes into the kv array, swap the entire meta entries in the meta array. Swapping 16 bytes is only negligibly slower than swapping 4 bytes. This requires adding the value-length into the meta array, since we used to rely on the previous-in-the-array meta entry to determine this. So we replace INDEX with VALUELEN and avoid one layer of indirection.
- introduce an interface which allows key types to provide a 4-byte comparison proxy. For string keys, this can simply be the first 4 bytes of the string. The idea is that, if stringCompare(key1.proxy(), key2.proxy()) != 0, then compare(key1, key2) should have the same result. If the proxies are equal, the normal comparison method is used. We then include the 4-byte proxy as part of the metadata entry, so that for many cases the indirection into the data buffer can be avoided.
On a terasort benchmark, these optimizations plus an optimization to WritableComparator.compareBytes dropped the aggregate mapside CPU millis by 40%, and the compare() routine mostly dropped off the oprofile results.