mongodb的set，inc，push比较
老实说，我并不是很清楚为什么这3个要放在一起比较，inc和set有相似的地方，push和这2个感觉完全不一样啊。实验中用的是ruby的mongo_ruby_driver来写程序的，为了获得比较精确的数值，我使用了benchmark这个module，反复执行set，inc，push各3000次。代码如下
#!/usr/bin/env ruby
# 20140301, mongo_test.rb
###
# test inc, set, push
###
require "rubygems"
require "mongo"
require "benchmark"
class MongoConnection
def initialize(host, port)
@mongoconn = Mongo::MongoClient.new(host, port)
@db = @mongoconn.db("test")
end
def test()
@coll = @db.collection("test")
# set test
@coll.insert({"num"=>0})
tm_start = Time.now.to_f
# (1..3000).each { |i| @coll.update({ }, { "$set" => {"num"=>i} } ) }
Benchmark.bm do |t|
t.report{ (1..3000).each { |i| @coll.update({ }, { "$set" => {"num"=>i} } ) } }
end
# p @coll.find.to_a
tm_used = Time.now.to_f - tm_start
puts "set Time used(s): #{tm_used}"
@coll.drop
# inc test
@coll.insert({"num"=>0})
tm_start = Time.now.to_f
# (1..3000).each { |i| @coll.update({ }, { "$inc" => {"num"=>1} } ) }
Benchmark.bm do |t|
t.report{ (1..3000).each { |i| @coll.update({ }, { "$inc" => {"num"=>1} } ) } }
end
# p @coll.find.to_a
tm_used = Time.now.to_f - tm_start
puts "inc Time used(s): #{tm_used}"
@coll.drop
# push test
@coll.insert({"num"=>})
tm_start = Time.now.to_f
# (1..3000).each { |i| @coll.update({ }, { "$push" => {"num"=>i} } ) }
Benchmark.bm do |t|
t.report{ (1..3000).each { |i| @coll.update({ }, { "$push" => {"num"=>i} } ) } }
end
# p @coll.find.to_a
tm_used = Time.now.to_f - tm_start
puts "push Time used(s): #{tm_used}"
@coll.drop
end
end
mongo_conn = MongoConnection.new("localhost", 27017)
mongo_conn.test()
测试结果如下
user system total real
1.570000 0.130000 1.700000 (2.180069)
set Time used(s): 2.1805129051208496
user system total real
1.480000 0.140000 1.620000 (2.059199)
inc Time used(s): 2.0596039295196533
user system total real
1.850000 0.200000 2.050000 (6.312153)
push Time used(s): 6.312557935714722
实际上，从反复执行的结果来看，set和inc基本是在同一个时间量级上，也不一定set就比inc快，也有相反的时候；而push的时间始终比较慢。这个跟rdbms的结果差异很大，rdbms的set和inc用的是update来实现，push用insert来实现，单个update语句产生的redo log要比insert多，所以一般update比insert要慢。但是，mongodb的结果与此相差很大，怀疑跟其存储引擎有关。
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