Rework checking if a year is a leap year (#60585) (#60790)

This way is faster, saving about 8% on the microbenchmark that rounds to
the nearest month. That is in the hot path for `date_histogram` which is
a very popular aggregation so it seems worth it to at least try and
speed it up a little.

Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>

benchmarks/README.md

@@ -63,3 +63,29 @@ To get realistic results, you should exercise care when running benchmarks. Here
 * Blindly believe the numbers that your microbenchmark produces but verify them by measuring e.g. with `-prof perfasm`.
 * Run more threads than your number of CPU cores (in case you run multi-threaded microbenchmarks).
 * Look only at the `Score` column and ignore `Error`. Instead take countermeasures to keep `Error` low / variance explainable.
+
+## Disassembling
+
+Disassembling is fun! Maybe not always useful, but always fun! Generally, you'll want to install `perf` and FCML's `hsdis`.
+`perf` is generally available via `apg-get install perf` or `pacman -S perf`. FCML is a little more involved. This worked
+on 2020-08-01:
+
+```
+wget https://github.com/swojtasiak/fcml-lib/releases/download/v1.2.2/fcml-1.2.2.tar.gz
+tar xf fcml*
+cd fcml*
+./configure
+make
+cd example/hsdis
+make
+cp .libs/libhsdis.so.0.0.0
+sudo cp .libs/libhsdis.so.0.0.0 /usr/lib/jvm/java-14-adoptopenjdk/lib/hsdis-amd64.so
+```
+
+If you want to disassemble a single method do something like this:
+
+```
+gradlew -p benchmarks run --args ' MemoryStatsBenchmark -jvmArgs "-XX:+UnlockDiagnosticVMOptions -XX:CompileCommand=print,*.yourMethodName -XX:PrintAssemblyOptions=intel"
+```
+
+If you want `perf` to find the hot methods for you then do add `-prof:perfasm`.

server/src/main/java/org/elasticsearch/common/time/DateUtilsRounding.java

@@ -92,8 +92,27 @@ class DateUtilsRounding {
         return (year * 365L + (leapYears - DAYS_0000_TO_1970)) * MILLIS_PER_DAY; // millis per day
     }
 
-    private static boolean isLeapYear(final int year) {
+    static boolean isLeapYear(final int year) {
-        return ((year & 3) == 0) && ((year % 100) != 0 || (year % 400) == 0);
+        // Joda had
+        // return ((year & 3) == 0) && ((year % 100) != 0 || (year % 400) == 0);
+        // But we've replaced that with this:
+        if ((year & 3) != 0) {
+            return false;
+        }
+        if (year % 100 != 0) {
+            return true;
+        }
+        return ((year / 100) & 3) == 0;
+        /*
+         * It is a little faster because it saves a division. We don't have good
+         * measurements for this method on its own, but this change speeds up
+         * rounding the nearest month by about 8%.
+         *
+         * Note: If you decompile this method to x86 assembly you won't see the
+         * division you'd expect from % 100 and / 100. Instead you'll see a funny
+         * sequence of bit twiddling operations which the jvm thinks is faster.
+         * Division is slow so it almost certainly is.
+         */
     }
 
     private static final long AVERAGE_MILLIS_PER_YEAR_DIVIDED_BY_TWO = MILLIS_PER_YEAR / 2;

server/src/test/java/org/elasticsearch/common/time/DateUtilsRoundingTests.java

@@ -46,4 +46,14 @@ public class DateUtilsRoundingTests extends ESTestCase {
             }
         }
     }
+
+    public void testIsLeapYear() {
+        assertTrue(DateUtilsRounding.isLeapYear(2004));
+        assertTrue(DateUtilsRounding.isLeapYear(2000));
+        assertTrue(DateUtilsRounding.isLeapYear(1996));
+        assertFalse(DateUtilsRounding.isLeapYear(2001));
+        assertFalse(DateUtilsRounding.isLeapYear(1900));
+        assertFalse(DateUtilsRounding.isLeapYear(-1000));
+        assertTrue(DateUtilsRounding.isLeapYear(-996));
+    }
 }