For this blog, I wrote a process simulator to mimic me at home after work. (Code available in the appendix.) I enter my house through the hall and from there alternate randomly between my study, the lounge and the kitchen. The implemented logic is that after two visits to the kitchen I must go to the bathroom and after fife visits to the lounge I go to the bedroom which also ends the day. In the Celonis Activities Process Overview this looks as follows:
Since my process simulator publishes its events to a Kafka channel, I leverage the SAP Data Hub (Graph details in the appendix) to collect those and store them in a file (available in the appendix) for upload into Celonis Snap:
As a result, I get my process analysed by the Celonis Process Explorer:
Of course, this reveals the implemented logic that after two visits to the kitchen I must go to the bathroom and after fife visits to the lounge I go to the bedroom which also ends the process.
How cool is that?
Since my process simulator publishes its events to a Kafka channel, I leverage the SAP Data Hub (Graph details in the appendix) to collect those and store them in a file (available in the appendix) for upload into Celonis Snap:
As a result, I get my process analysed by the Celonis Process Explorer:
Of course, this reveals the implemented logic that after two visits to the kitchen I must go to the bathroom and after fife visits to the lounge I go to the bedroom which also ends the process.
How cool is that?
Appendix
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.serialization.StringSerializer;
import java.util.Properties;
import java.sql.Timestamp;
import java.util.Random;
public class Celonis {
public static void main(String[] args) {
try {
Properties props = new Properties();
props.put("bootstrap.servers", "kafka.server.com:6667");
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
int day = 101;
String step = "initial";
int loo = 0;
int sleep = 0;
int wee = 1;
int tired = 3;
int days = 103;
int rooms = 4;
while (true) {
Producer < String, String > producer = new KafkaProducer < > (props);
Random rand = new Random();
int x = rand.nextInt(rooms);
boolean send = true;
switch (x) {
case 0:
switch (step) {
case "initial":
step = "Hall";
break;
case "Bedroom":
day++;
if (day > days) {
System.exit(0);
}
step = "Hall";
loo = 0;
sleep = 0;
break;
default:
if (day > days) {
System.exit(0);
} else if (loo > wee) {
loo = 0;
step = "Bathroom";
} else if (sleep > tired) {
sleep = 0;
step = "Bedroom";
} else {
send = false;
}
}
break;
case 1:
switch (step) {
case "initial":
step = "Hall";
break;
case "Bedroom":
day++;
if (day > days) {
System.exit(0);
}
step = "Hall";
loo = 0;
sleep = 0;
break;
case "Kitchen":
send = false;
break;
default:
if (day > days) {
System.exit(0);
} else if (sleep > tired) {
sleep = 0;
step = "Bedroom";
} else {
loo++;
step = "Kitchen";
}
}
break;
case 2:
switch (step) {
case "initial":
step = "Hall";
break;
case "Bedroom":
day++;
if (day > days) {
System.exit(0);
}
step = "Hall";
loo = 0;
sleep = 0;
break;
case "Lounge":
send = false;
break;
default:
if (day > days) {
System.exit(0);
} else if (loo > wee) {
loo = 0;
step = "Bathroom";
} else if (sleep > tired) {
sleep = 0;
step = "Bedroom";
} else {
sleep++;
step = "Lounge";
}
}
break;
case 3:
switch (step) {
case "initial":
step = "Hall";
break;
case "Bedroom":
day++;
if (day > days) {
System.exit(0);
}
step = "Hall";
loo = 0;
sleep = 0;
break;
case "Study":
send = false;
break;
default:
if (day > days) {
System.exit(0);
} else if (loo > wee) {
loo = 0;
step = "Bathroom";
} else if (sleep > tired) {
sleep = 0;
step = "Bedroom";
} else {
step = "Study";
}
}
break;
default:
step = "error";
}
Timestamp timestamp = new Timestamp(System.currentTimeMillis());
if (send) {
producer.send(new ProducerRecord < String, String > ("celonis", Integer.toString(0), timestamp + "," + Integer.toString(day) + "," + step));
producer.close();
}
Thread.sleep(10000);
}
} catch (Exception e) {
e.printStackTrace();
}
}
}{
"properties": {},
"description": "",
"processes": {
"terminal1": {
"component": "com.sap.util.terminal",
"metadata": {
"label": "Terminal",
"x": 501.99999713897705,
"y": 12,
"height": 80,
"width": 120,
"ui": "dynpath",
"config": {}
}
},
"tostringconverter1": {
"component": "com.sap.util.toStringConverter",
"metadata": {
"label": "ToString Converter",
"x": 386.99999809265137,
"y": 42,
"height": 50,
"width": 50,
"config": {}
}
},
"kafkaconsumer1": {
"component": "com.sap.kafka.consumer2",
"metadata": {
"label": "Kafka Consumer",
"x": 17,
"y": 72,
"height": 80,
"width": 120,
"config": {
"kafkaVersion": "0.10.1",
"connectionType": "connection management",
"connection": {
"configurationType": "Configuration Manager",
"connectionID": "Kafka"
},
"topics": "celonis"
}
}
},
"12multiplexer1": {
"component": "com.sap.system.multiplexer.1-2",
"metadata": {
"label": "1:2 Multiplexer",
"x": 201.99999904632568,
"y": 72,
"height": 80,
"width": 120,
"extensible": true,
"config": {}
}
},
"toblobconverter1": {
"component": "com.sap.util.toBlobConverter",
"metadata": {
"label": "ToBlob Converter",
"x": 386.99999809265137,
"y": 132,
"height": 50,
"width": 50,
"config": {}
}
},
"formatconverter1": {
"component": "com.sap.util.formatConverter",
"metadata": {
"label": "Format Converter",
"x": 501.99999713897705,
"y": 132,
"height": 80,
"width": 120,
"config": {
"targetFormat": "CSV",
"fields": "millis,case,activity"
}
}
},
"writefile1": {
"component": "com.sap.storage.write",
"metadata": {
"label": "Write File",
"x": 686.9999961853027,
"y": 72,
"height": 80,
"width": 120,
"config": {
"service": "adl",
"adlConnection": {
"connectionProperties": {
"accountName": "",
"clientId": "",
"clientKey": "",
"rootPath": "",
"tenantId": ""
},
"configurationType": "Configuration Manager",
"connectionID": "architectIT"
},
"path": "celonis.csv"
}
}
}
},
"groups": [],
"connections": [
{
"metadata": {
"points": "440.99999809265137,67 468.9999976158142,67 468.9999976158142,52 496.99999713897705,52"
},
"src": {
"port": "outstring",
"process": "tostringconverter1"
},
"tgt": {
"port": "in1",
"process": "terminal1"
}
},
{
"metadata": {
"points": "141,103 168.99999952316284,103 168.99999952316284,112 196.99999904632568,112"
},
"src": {
"port": "message",
"process": "kafkaconsumer1"
},
"tgt": {
"port": "in1",
"process": "12multiplexer1"
}
},
{
"metadata": {
"points": "325.9999990463257,103 353.9999985694885,103 353.9999985694885,76 381.99999809265137,76"
},
"src": {
"port": "out1",
"process": "12multiplexer1"
},
"tgt": {
"port": "inmessage",
"process": "tostringconverter1"
}
},
{
"metadata": {
"points": "325.9999990463257,121 353.9999985694885,121 353.9999985694885,157 381.99999809265137,157"
},
"src": {
"port": "out2",
"process": "12multiplexer1"
},
"tgt": {
"port": "ininterface",
"process": "toblobconverter1"
}
},
{
"metadata": {
"points": "440.99999809265137,157 468.9999976158142,157 468.9999976158142,172 496.99999713897705,172"
},
"src": {
"port": "outbytearray",
"process": "toblobconverter1"
},
"tgt": {
"port": "input",
"process": "formatconverter1"
}
},
{
"metadata": {
"points": "625.999997138977,172 653.9999966621399,172 653.9999966621399,112 681.9999961853027,112"
},
"src": {
"port": "output",
"process": "formatconverter1"
},
"tgt": {
"port": "inFile",
"process": "writefile1"
}
}
],
"inports": {},
"outports": {}
}2019-07-17 13:26:26.681,101,Hall
2019-07-17 13:26:41.426,101,Kitchen
2019-07-17 13:26:51.915,101,Study
2019-07-17 13:27:33.396,101,Lounge
2019-07-17 13:27:44.073,101,Study
2019-07-17 13:27:54.508,101,Kitchen
2019-07-17 13:28:05.133,101,Bathroom
2019-07-17 13:28:26.078,101,Lounge
2019-07-17 13:28:36.597,101,Kitchen
2019-07-17 13:29:17.647,101,Study
2019-07-17 13:29:28.142,101,Lounge
2019-07-17 13:29:48.718,101,Kitchen
2019-07-17 13:29:59.099,101,Bathroom
2019-07-17 13:30:19.857,101,Lounge
2019-07-17 13:30:40.437,101,Bedroom
2019-07-17 13:30:50.766,102,Hall
2019-07-17 13:31:01.103,102,Lounge
2019-07-17 13:31:41.928,102,Study
2019-07-17 13:32:02.468,102,Lounge
2019-07-17 13:32:13.2,102,Study
2019-07-17 13:32:23.674,102,Lounge
2019-07-17 13:32:34.045,102,Study
2019-07-17 13:32:54.425,102,Lounge
2019-07-17 13:33:04.803,102,Bedroom
2019-07-17 13:33:15.498,103,Hall
2019-07-17 13:33:26.129,103,Lounge
2019-07-17 13:33:56.836,103,Kitchen
2019-07-17 13:34:07.307,103,Study
2019-07-17 13:34:28.114,103,Lounge
2019-07-17 13:34:38.445,103,Kitchen
2019-07-17 13:34:58.875,103,Bathroom
2019-07-17 13:35:09.256,103,Kitchen
2019-07-17 13:35:19.94,103,Lounge
2019-07-17 13:35:30.497,103,Kitchen
2019-07-17 13:35:40.825,103,Bathroom
2019-07-17 13:35:51.227,103,Lounge
2019-07-17 13:36:01.546,103,Bedroom- SAP Managed Tags:
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