在排序向量上进行多次匹配时定义起始位置会更快吗?

Will defining a start position when doing multiple matches on a sorted vector be faster?

我有一个包含 100 万个整数的向量,按升序排列,还有一个向量包含 1000 个这些整数的子集,也已排序。

什么会更快?如果samplevec变大,第二个版本会不会变快?

samplevec=sort(sample(1:10000000, 1000000))
matchvec=sort(sample(samplevec, 10000))

for (i in matchvec) {
index=match(i, samplevec)
print(index)
}

samplevec=sort(sample(1:10000000, 1000000))
matchvec=sort(sample(samplevec, 10000))

previous=1
for (i in matchvec) {
index=match(i, samplevec[previous:length(samplevec)])
previous=index
print(index)
}

基准测试很容易。这里只是两个时间点。随意拉皮条并自动增加时间点的数量。

library(microbenchmark)

set.seed(357)

samplevec = sort(sample(1:1000, 1000))
matchvec = sort(sample(samplevec, 1000))

microbenchmark(
  version1 = {
    previous=1
    for (i in matchvec) {
      index=match(i, samplevec[previous:length(samplevec)])
      previous=index
    }},
  version2 = {
    for (i in matchvec) {
      index = match(i, samplevec)
    }}
)

Unit: milliseconds
     expr       min        lq      mean    median       uq
 version1 10.619105 10.711438 12.057713 10.811051 12.71902
 version2  2.419441  2.487062  2.853868  2.506603  2.56024

这是第二点。这个运行时间有点长。

set.seed(357)

samplevec = sort(sample(1:100000, 100000))
matchvec = sort(sample(samplevec, 100000))

microbenchmark(
  version1 = {
    previous=1
    for (i in matchvec) {
      index=match(i, samplevec[previous:length(samplevec)])
      previous=index
    }},
  version2 = {
    for (i in matchvec) {
      index=match(i, samplevec)
    }}
)

Unit: seconds
     expr       min        lq      mean    median        uq
 version1 108.96069 109.61137 110.87308 110.70554 111.61337
 version2  15.63668  15.71792  16.20434  15.84646  16.07487