新葡萄京娱乐场

脾性测试比较,time时间模块学习

四月 3rd, 2019  |  新葡萄京娱乐场

喜爱经久不衰的大旨曲,旋律奔放,给那些爱情遗闻增加了不停浪漫色彩。 oh,
my love, my darling i’ve hungered for your touch a long, lonely time.
and time goes by so slowly and time can do so much, are you still mine?
………

Python time时间模块学习

time包

time包的底蕴项目是struct_time。

time.sleep() 让程序 延时,以秒为单位。

time.time() 重返时间戳,浮点型。

time.strptime(string, format)

用法 ,将字符串转换来 struct_time,重返时间协会struct_time

time_struct = time.strptime(‘2014-10-10 22:22:12’,”%Y-%m-%d
%H:%M:%S”)

time.strftime(format,struct_time)

用法,struct_time将转换来 字符串, 重临字符串。

time.strftime(“%Y-%m-%d”,struct_time)

time.mktime(time_struct)

用法,时间组织到时刻戳,重回浮点情势的 时间戳。

time.gmtime(time_stamp)

用法,将时刻戳,转化成时间组织,再次回到时间结构。

time.gmtime(1812950932)

time.localtime()
用法,将时刻戳,转化成时间组织,重回时间结构。

time.localtime()

gmtime()和loaltime() 都以将 时间戳 转换到 时间结构 ,不一样之处是 gmtime
转化成 格林威治时间, localtime
转换出来的是本地时间,比如大家正是新加坡时间。 所以一般time.localtime()
括号里都不加参数,暗中认可正是得到当前的时刻戳,转换来当今天子。

脾性测试比较,time时间模块学习。

总结

字符串 到 time_struct 用 time.strptime()

time_struct 到 字符串 用 time.strftime()

时间戳 到 time_struct 用 time.gmtime(time_stamp) 或者
time.localtime(time_stamp) time_stamp能够简简单单

time_struct 到 时间戳 用 time.mktime(time_struct)

能够见见 字符串 和 时间戳之间 未有 直接转换的关系 ,能够由此 时间组织来作为 过渡。

简图:

新葡萄京娱乐场 1

尽管如此 time.ctime() 也是 将 时间戳 转化为 字符串,不过不可能用 格式化字符
来定制,用处简单。如

time.ctime(1212950932) 的 重回结果 是 Mon Jun 玖 02:4八:5二 二〇〇九 。

time.asctime(time_struct) 也是将 时间组织体 ,转化成
字符串,通ctime一样,生成的字符串格式,不可能定制。如

time.asctime(time_struct) 的归来结果是 Mon Jun 1四 05:28:52 20贰柒。

time时间模块学习 time包
time包的功底项目是struct_time。 time.sleep() 让程序 延时,以秒为单位。
time.time() 重临时间戳,浮点型。 time.str…

试验场景一:要对同几个list实时添澳成分,且放入缓存中。代码如下:

今天攻读了peersim的cycle形式,明天始于持续悟事件情势。

    @Test  
    public void testMemCacheAndRedis() {  
      this.testInsert(1000);  
    }  

    public void testInsert(int size) {  
      MemCached memCached = (MemCached) ctx.getBean("configMemCache");  
      memCached.flushAll();  
      long before = System.currentTimeMillis();  
      List<Integer> list = new ArrayList<Integer>();  
      for (int i = 0; i < size; i++) {  
        list.add(i);  
        memCached.put("test", list);  
      }  
      long end = System.currentTimeMillis();  

      RedisTemplate<String, Object> redisTemplate = (RedisTemplate<String, Object>) ctx.getBean("bubbleRedisTemplate");  
      redisTemplate.delete("test123");  
      long before2 = System.currentTimeMillis();  
      for (int i = 0; i < size; i++) {  
        redisTemplate.boundListOps("test123").leftPush(i);  
      }  
      long end2 = System.currentTimeMillis();  
      System.out.println("memcached use time is " + (end - before));  
      System.out.println("redis use time is " + (end2 - before2));  
    }  

总的看,小编个人觉得事件形式是周期情势的提拔版,恐怕说,周期格局只是事件形式的二个子效益。

 

事件情势是依照时间和事件的(没打错),每便试验的起来会设定甘休时间和几何要拍卖的轩然大波,当岁月甘休,或然事件全部做完,实验就得了,而在得了以前,也是足以周期性的推行壹些风波,所以说周期形式只是事件形式的二个子意义。

当n=一千时的专断1回打字与印刷结果:

memcached use time is 6282
redis use time is 1156

memcached use time is 6547
redis use time is 1172

memcached use time is 6234
redis use time is 1375

上学方法依旧一贯看代码,看不懂的地点一贯去找对应的源文件,1稀罕从子类往上看。

当n=贰仟时的四意1次打字与印刷结果:

memcached use time is 22313
redis use time is 2328

memcached use time is 22969
redis use time is 2907

memcached use time is 22938
redis use time is 2234

贴上样例代码,功效和周期方式壹样,首先是对互联网中的各种节点赋早先值(那里运用线性分布),接着各种节点和邻座节点求平均值

当n=三千时的妄动一回打字与印刷结果:

memcached use time is 48859
redis use time is 3297

新葡萄京娱乐场 ,memcached use time is 48156
redis use time is 4547

memcached use time is 47765
redis use time is 3375

**试验一结论(只对本次试验负责):当n在20条以内时,两者反差相当的小,但当n大于20时,redis在质量上的优势就会逐年呈现出来。

检测场景贰:对先后做些稍许的改变,即将memCached.put(“xwq”,
list);那壹行移到for循环外面执行,代码如下:**

 

 1      @Test  
 2     public void testMemCacheAndRedis() {  
 3       this.testBatchInsert(3000);  
 4     }  
 5       
 6     public void testBatchInsert(int size) {  
 7       MemCached memCached = (MemCached) ctx.getBean("configMemCache");  
 8       memCached.flushAll();  
 9       long before = System.currentTimeMillis();  
10       List<Integer> list = new ArrayList<Integer>();  
11       for (int i = 0; i < size; i++) {  
12         list.add(i);  
13       }  
14       memCached.put("test", list);  
15       long end = System.currentTimeMillis();  
16       
17       RedisTemplate<String, Object> redisTemplate = (RedisTemplate<String, Object>) ctx.getBean("bubbleRedisTemplate");  
18       redisTemplate.delete("test123");  
19       long before2 = System.currentTimeMillis();  
20       for (int i = 0; i < size; i++) {  
21         redisTemplate.boundListOps("test123").leftPush(i);  
22       }  
23       long end2 = System.currentTimeMillis();  
24       System.out.println("memcached use time is " + (end - before));  
25       System.out.println("redis use time is " + (end2 - before2));  
26     }  

 

大家再做下考察:

样例代码:

当n=1000时的私行一回打字与印刷结果:

memcached use time is 15
redis use time is 1188

memcached use time is 32
redis use time is 1188

memcached use time is 31
redis use time is 1234

  1 /*
  2  * Copyright (c) 2003 The BISON Project
  3  *
  4  * This program is free software; you can redistribute it and/or modify
  5  * it under the terms of the GNU Lesser General Public License version 2 as
  6  * published by the Free Software Foundation.
  7  *
  8  * This program is distributed in the hope that it will be useful,
  9  * but WITHOUT ANY WARRANTY; without even the implied warranty of
 10  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 11  * GNU Lesser General Public License for more details.
 12  *
 13  * You should have received a copy of the GNU Lesser General Public License
 14  * along with this program; if not, write to the Free Software
 15  * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 16  *
 17  */
 18 
 19 package example.edaggregation;
 20 
 21 import peersim.vector.SingleValueHolder;
 22 import peersim.config.*;
 23 import peersim.core.*;
 24 import peersim.transport.Transport;
 25 import peersim.cdsim.CDProtocol;
 26 import peersim.edsim.EDProtocol;
 27 
 28 /**
 29 * Event driven version of epidemic averaging.
 30 */
 31 public class AverageED extends SingleValueHolder
 32 implements CDProtocol, EDProtocol {                     //这里除了ED协议,还实现了CD协议,正是因为在实验中会周期性的执行一些事件,所以要实现CD协议             
 33 
 34 //--------------------------------------------------------------------------
 35 // Initialization
 36 //--------------------------------------------------------------------------
 37 
 38 /**
 39  * @param prefix string prefix for config properties
 40  */
 41 public AverageED(String prefix) { super(prefix); }
 42 
 43 
 44 //--------------------------------------------------------------------------
 45 // methods
 46 //--------------------------------------------------------------------------
 47 
 48 /**
 49  * This is the standard method the define periodic activity.
 50  * The frequency of execution of this method is defined by a
 51  * {@link peersim.edsim.CDScheduler} component in the configuration.
 52  */
 53 public void nextCycle( Node node, int pid )        //这里就是周期模式的核心代码部分,定义了周期性的行为
 54 {
 55     Linkable linkable = 
 56         (Linkable) node.getProtocol( FastConfig.getLinkable(pid) );    
 57     if (linkable.degree() > 0)
 58     {
 59         Node peern = linkable.getNeighbor(
 60                 CommonState.r.nextInt(linkable.degree()));          //这部分的功能是得到本地节点的一个邻居节点,而不是所有相邻节点
 61         
 62         // XXX quick and dirty handling of failures
 63         // (message would be lost anyway, we save time)
 64         if(!peern.isUp()) return;
 65         
 66         ((Transport)node.getProtocol(FastConfig.getTransport(pid))).     //这里涉及到了传输层,功能是像邻居节点发送信息,把本地的值发过去
 67             send(
 68                 node,
 69                 peern,
 70                 new AverageMessage(value,node),
 71                 pid);
 72     }
 73 }
 74 
 75 //--------------------------------------------------------------------------
 76 
 77 /**
 78 * This is the standard method to define to process incoming messages.
 79 */
 80 public void processEvent( Node node, int pid, Object event ) {        //这里是ED模式的核心代码部分,用来处理事件
 81         
 82     AverageMessage aem = (AverageMessage)event;                       //从邻居节点那里接受到的信息
 83     
 84     if( aem.sender!=null )                                           //如果邻居节点的发送者不为空,说明本节点并不是目的节点,所以继续帮他转发
 85         ((Transport)node.getProtocol(FastConfig.getTransport(pid))).
 86             send(
 87                 node,
 88                 aem.sender,
 89                 new AverageMessage(value,null),
 90                 pid);
 91                 
 92     value = (value + aem.value) / 2;                             //如果为空,则说明本节点就是目的节点,所以把对方的值和本地的平均值替换本地值
 93 }
 94 
 95 }
 96 
 97 //--------------------------------------------------------------------------
 98 //--------------------------------------------------------------------------
 99 
100 /**
101 * The type of a message. It contains a value of type double and the
102 * sender node of type {@link peersim.core.Node}.
103 */
104 class AverageMessage {                                   //信息类,非常简单,只有一个value和sender
105 
106     final double value;
107     /** If not null,
108     this has to be answered, otherwise this is the answer. */
109     final Node sender;
110     public AverageMessage( double value, Node sender )
111     {
112         this.value = value;
113         this.sender = sender;
114     }
115 }

当n=三千时的任意三回打印结果:

memcached use time is 47
redis use time is 2437

memcached use time is 31
redis use time is 2344

memcached use time is 47
redis use time is 2265

上述正是ed形式下的叁个粗略的样例,作用也很简短,比较上周期形式,我认为她是这么工作的:在各种定义的周期内向邻居发送节点,当节点接受到发送来的消息后,则会处理(求平均值),当中内部一些是通过3个堆来保管那么些事件(send()方法本身就是把事件添加到堆个中)

但n=两千时的任意三次打印结果:

memcached use time is 62
redis use time is 3406

memcached use time is 47
redis use time is 3391

memcached use time is 47
redis use time is 3688

检查评定2结论(只对本次试验负责):由此能够看出,memcached一回性将list放入到缓存中,比redis每趟换代质量是要高很多的。

检查实验场景叁:对相同大小的四个list,同时进行同样次数的读操作,代码如下:
 

 1  @Test
 2   public void testMemCacheAndRedis() {
 3     // this.testInsert(3000);
 4     // this.testBatchInsert(3000);
 5     this.testRead(200);
 6   }
 7 
 8   public void testRead(int size) {
 9     MemCached memCached = (MemCached) ctx.getBean("configMemCache");
10     memCached.flushAll();
11     List<Integer> list = new ArrayList<Integer>();
12     for (int i = 0; i < 1000; i++) {
13       list.add(i);
14     }
15     memCached.put("test", list);
16 
17     long before = System.currentTimeMillis();
18     for (int i = 0; i < size; i++) {
19       memCached.get("test");
20     }
21     long end = System.currentTimeMillis();
22 
23     RedisTemplate<String, Object> redisTemplate = (RedisTemplate<String, Object>) ctx.getBean("bubbleRedisTemplate");
24     redisTemplate.delete("test123");
25     for (int i = 0; i < 1000; i++) {
26       redisTemplate.boundListOps("test123").leftPush(i);
27     }
28 
29     long before2 = System.currentTimeMillis();
30     for (int i = 0; i < size; i++) {
31       redisTemplate.boundListOps("xwq123").range(0, -1);
32     }
33     long end2 = System.currentTimeMillis();
34     System.out.println("memcached use time is " + (end - before));
35     System.out.println("redis use time is " + (end2 - before2));
36   } 

 

但是难点并不是这,而是布署文件部分。。。shit :(

当n=十0时的随意三遍打字与印刷结果:

memcached use time is 6765
redis use time is 281

memcached use time is 2187
redis use time is 297

memcached use time is 9547
redis use time is 313

贴代码

当n=200时的人身自由二遍打印结果:

memcached use time is 34250
redis use time is 546

memcached use time is 12171
redis use time is 547

memcached use time is 8297
redis use time is 516

 1 # network size                             #首先是类似宏定义的一样定义了几个值,方便一会使用,果然换了ED模式连这里都高级起来了
 2 SIZE 1000
 3 
 4 # parameters of periodic execution
 5 CYCLES 100
 6 CYCLE SIZE*10000                     
 7 
 8 # parameters of message transfer
 9 # delay values here are relative to cycle length, in percentage,
10 # eg 50 means half the cycle length, 200 twice the cycle length, etc.
11 MINDELAY 0
12 MAXDELAY 0
13 # drop is a probability, 0<=DROP<=1
14 DROP 0
15 
16 random.seed 1234567890
17 network.size SIZE
18 simulation.endtime CYCLE*CYCLES
19 simulation.logtime CYCLE
20 
21 ################### protocols ===========================   #这部分比较麻烦,全是新的玩意
22 
23 protocol.link peersim.core.IdleProtocol          #网络还是选的之前的一样
24 
25 protocol.avg example.edaggregation.AverageED
26 protocol.avg.linkable link
27 protocol.avg.step CYCLE          #这里的step类似于周期的概念
28 protocol.avg.transport tr        #这里的tr在下面有定义
29 
30 protocol.urt UniformRandomTransport       #这里是具体的传输层协议,功能是以随机的延迟(随机范围在下面定义)发送消息,发送的实质是向事件的堆中添加事件
31 protocol.urt.mindelay (CYCLE*MINDELAY)/100
32 protocol.urt.maxdelay (CYCLE*MAXDELAY)/100
33 
34 protocol.tr UnreliableTransport          #一个不稳定的传输层协议,以下面的drop的值随机丢包,实际传输还是用的上面urt
35 protocol.tr.transport urt
36 protocol.tr.drop DROP
37 
38 ################### initialization ======================
39 
40 init.rndlink WireKOut                    #网络布局,节点以k出度相连
41 init.rndlink.k 20
42 init.rndlink.protocol link
43 
44 init.vals LinearDistribution            #给每个节点的赋初值,线性分布,具体分布方法是定义step= (max.doubleValue()-min.doubleValue())/(Network.size()-1);   setter.set(i,Math.round(i*step)+min.longValue()); 详细见源文件

45 init.vals.protocol avg
46 init.vals.max SIZE
47 init.vals.min 1
48 
49 init.sch CDScheduler                    #这里很关键,定义了一个周期调度管理器,会在每个周期的开始随机打乱节点的部分,每隔一个cycle值就打乱一次
50 init.sch.protocol avg
51 init.sch.randstart
52 
53 ################ control ==============================
54 
55 control.0 SingleValueObserver         #这里的step指定了周期值,使得监测者也会在每个指定的周期调用一次,否则control则会想周期模式一样调度
56 control.0.protocol avg
57 control.0.step CYCLE

当n=500时的随意三遍打字与印刷结果:

memcached use time is 69437
redis use time is 1297

memcached use time is 43781
redis use time is 1516

memcached use time is 37750
redis use time is 1281

调查三结论(只对此番考试负责):同样是从缓存中读取数据,redis的天性是要远远超越memcached。

综合结论(只对这次次试验负责):通过上述3回考试,redis在
读操作和写操作上是圆满超过memcached的。但有一点,memcached能够叁回性将聚集的多少放入自个儿的缓存中,而redis却卓越(有照旧木
有?),所以memcached并不是荒谬的,在不可胜道光景下,二者是亟需交叉使用的,要依据实际情状举办抉择。

最后贴上实验结果:

EDSimulator: resetting
Network: no node defined, using GeneralNode
EDSimulator: running initializers

  • Running initializer init.rndlink: class peersim.dynamics.WireKOut
  • Running initializer init.sch: class peersim.edsim.CDScheduler
  • Running initializer init.vals: class
    peersim.vector.LinearDistribution
    EDSimulator: loaded controls [control.0]
    Current time: 0
    control.0: 1.0 1000.0 1000 500.5 83416.66666666667 1 1
    Current time: 10000000
    control.0: 37.5 919.0 1000 500.5 25724.159091250687 1 1
    Current time: 20000000
    control.0: 206.7109375 767.890625 1000 500.5 8096.807036889389 1 1
    Current time: 30000000
    control.0: 352.373046875 695.453125 1000 500.5 2578.022573176135 1 1
    Current time: 40000000
    control.0: 412.430419921875 625.474609375 1000 500.5 801.1082179446831 1
    1
    Current time: 50000000
    control.0: 436.43787479400635 570.459858417511 1000 500.5
    243.53994072762902 1 1
    Current time: 60000000
    control.0: 470.7608990445733 527.0359845032217 1000 500.49999999999994
    74.13788674564383 1 2
    Current time: 70000000
    control.0: 483.6040476858616 518.0301055684686 1000 500.49999999999903
    23.428974301677556 1 1
    Current time: 80000000
    control.0: 490.5196089811798 512.0301471857779 1000 500.4999999999993
    7.285566419597019 1 1
    Current time: 90000000
    control.0: 494.97216907397836 506.0375954180854 1000 500.4999999999999
    2.1798299307442246 1 1
    Current time: 100000000
    control.0: 497.18190345272336 503.5837144460532 1000 500.5000000000001
    0.6073148838336206 1 1
    Current time: 110000000
    control.0: 498.54320551492475 502.3533156558903 1000 500.5
    0.1786794435445898 1 2
    Current time: 120000000
    control.0: 499.4023441821402 501.4962048486104 1000 500.49999999999966
    0.055257607540637785 1 1
    Current time: 130000000
    control.0: 500.0032071191514 501.09832936709677 1000 500.4999999999995
    0.017914865984002482 1 1
    Current time: 140000000
    control.0: 500.2115701087355 500.83018846682955 1000 500.5000000000003
    0.005681541785868155 1 1
    Current time: 150000000
    control.0: 500.34130672550015 500.6817038675913 1000 500.49999999999983
    0.0018027434356275712 1 1
    Current time: 160000000
    control.0: 500.4099993828274 500.593872603867 1000 500.50000000000006
    5.362825330674977E-4 1 1
    Current time: 170000000
    control.0: 500.45257293353984 500.54348273631905 1000 500.50000000000057
    1.540724446790086E-4 1 1
    Current time: 180000000
    control.0: 500.4730336913324 500.5308245606462 1000 500.49999999999983
    4.870521656989873E-5 2 1
    Current time: 190000000
    control.0: 500.48375224793585 500.5157654498322 1000 500.4999999999995
    1.6009524787167412E-5 1 1
    Current time: 200000000
    control.0: 500.48865909872677 500.50651976294216 1000 500.50000000000017
    5.077729859315717E-6 1 1
    Current time: 210000000
    control.0: 500.4951192430326 500.5047676794802 1000 500.5000000000002
    1.6155684864646324E-6 1 1
    Current time: 220000000
    control.0: 500.4974085478983 500.502935896735 1000 500.50000000000045
    5.105843169016166E-7 1 1
    Current time: 230000000
    control.0: 500.4987222960319 500.5016402188968 1000 500.5000000000002
    1.6512563666543207E-7 1 1
    Current time: 240000000
    control.0: 500.49903235648463 500.50092451432386 1000 500.49999999999994
    5.299286046125987E-8 1 1
    Current time: 250000000
    control.0: 500.49958979342233 500.50059026547086 1000 500.5000000000001
    1.5440470612681545E-8 1 1
    Current time: 260000000
    control.0: 500.4996881991682 500.500274943262 1000 500.5000000000001
    4.8652048911656945E-9 1 1
    Current time: 270000000
    control.0: 500.49977403242923 500.5001382754437 1000 500.4999999999995
    2.0101744759906163E-9 1 1
    Current time: 280000000
    control.0: 500.49987495360983 500.50007640960587 1000 500.5
    1.7479778052092316E-10 1 1
    Current time: 290000000
    control.0: 500.49994445650935 500.5000501190701 1000 500.5000000000004
    0.0 1 1
    Current time: 300000000
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    Current time: 440000000
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    Current time: 450000000
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    Current time: 470000000
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    Current time: 480000000
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    Current time: 490000000
    control.0: 500.49999999949034 500.500000000275 1000 500.50000000000006
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    Current time: 500000000
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    Current time: 570000000
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    Current time: 580000000
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    Current time: 590000000
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    Current time: 600000000
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    Current time: 610000000
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    Current time: 630000000
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    Current time: 650000000
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    Current time: 660000000
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    Current time: 670000000
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    Current time: 680000000
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    Current time: 690000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 700000000
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    Current time: 710000000
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    Current time: 720000000
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    Current time: 730000000
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    Current time: 750000000
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    Current time: 760000000
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    Current time: 770000000
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    Current time: 780000000
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    Current time: 790000000
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    Current time: 800000000
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    Current time: 810000000
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    Current time: 820000000
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    Current time: 830000000
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    Current time: 840000000
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    Current time: 850000000
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    Current time: 860000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 870000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 880000000
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    Current time: 890000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 900000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 910000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 920000000
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    Current time: 930000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 940000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 950000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 960000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 970000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 980000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    Current time: 990000000
    control.0: 500.5 500.5 1000 500.5 0.0 1000 1000
    EDSimulator: queue is empty, quitting at time 999980413

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