신은섭(Shin Eun Seop) / Detecting_fraud_clicks

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KimchiSoup(junu)
23ff7ca6 1 parent 6acc769d

Java-Cesco/Detecting_fraud_clicks#13 ui-create table

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Showing 5 changed files with 199 additions and 10 deletions
...@@ -31,6 +31,12 @@ ...@@ -31,6 +31,12 @@
31 <artifactId>spark-csv_2.11</artifactId> 31 <artifactId>spark-csv_2.11</artifactId>
32 <version>1.5.0</version> 32 <version>1.5.0</version>
33 </dependency> 33 </dependency>
34 + <dependency>
35 + <groupId>com.googlecode.json-simple</groupId>
36 + <artifactId>json-simple</artifactId>
37 + <version>1.1</version>
38 + </dependency>
39 +
34 </dependencies> 40 </dependencies>
35 41
36 <build> 42 <build>
......
1 +import org.json.simple.JSONObject;
2 +import org.json.simple.parser.JSONParser;
3 +import org.json.simple.JSONArray;
4 +
1 import org.apache.spark.sql.Dataset; 5 import org.apache.spark.sql.Dataset;
2 import org.apache.spark.sql.Row; 6 import org.apache.spark.sql.Row;
3 import org.apache.spark.sql.SparkSession; 7 import org.apache.spark.sql.SparkSession;
4 import org.apache.spark.sql.expressions.Window; 8 import org.apache.spark.sql.expressions.Window;
5 import org.apache.spark.sql.expressions.WindowSpec; 9 import org.apache.spark.sql.expressions.WindowSpec;
6 10
11 +
12 +import javax.swing.*;
13 +import javax.swing.table.DefaultTableModel;
14 +import java.util.List;
15 +import java.io.*;
16 +import javax.swing.table.*;
17 +
18 +
7 import static org.apache.spark.sql.functions.*; 19 import static org.apache.spark.sql.functions.*;
8 -import static org.apache.spark.sql.functions.lit;
9 -import static org.apache.spark.sql.functions.when;
10 20
11 public class Aggregation { 21 public class Aggregation {
12 22
13 public static void main(String[] args) throws Exception { 23 public static void main(String[] args) throws Exception {
14 24
15 - new GUI(); 25 +
16 26
17 //Create Session 27 //Create Session
18 SparkSession spark = SparkSession 28 SparkSession spark = SparkSession
...@@ -30,8 +40,12 @@ public class Aggregation { ...@@ -30,8 +40,12 @@ public class Aggregation {
30 dataset = agg.clickTimeDelta(dataset); 40 dataset = agg.clickTimeDelta(dataset);
31 dataset = agg.countClickInTenMinutes(dataset); 41 dataset = agg.countClickInTenMinutes(dataset);
32 42
33 - //test 43 + List<String> stringDataset = dataset.toJSON().collectAsList();
34 - dataset.where("ip == '5348' and app == '19'").show(10); 44 + GUI gui = new GUI(stringDataset);
45 +
46 +
47 +
48 +
35 } 49 }
36 50
37 51
......
1 +import org.apache.spark.sql.Dataset;
2 +import org.apache.spark.sql.Row;
3 +
1 import javax.swing.*; 4 import javax.swing.*;
2 import java.awt.*; 5 import java.awt.*;
6 +import java.io.BufferedReader;
7 +import java.io.StringReader;
8 +import java.sql.ResultSet;
9 +import java.sql.ResultSetMetaData;
10 +import java.sql.Statement;
11 +import java.util.List;
12 +import java.util.Vector;
13 +import java.awt.BorderLayout;
14 +import java.awt.GridLayout;
15 +import java.awt.event.ActionEvent;
16 +import java.awt.event.ActionListener;
17 +import java.sql.Connection;
18 +import java.sql.DriverManager;
19 +import java.sql.ResultSet;
20 +import java.sql.ResultSetMetaData;
21 +import java.sql.Statement;
22 +import java.util.Vector;
23 +
24 +import javax.swing.JButton;
25 +import javax.swing.JFrame;
26 +import javax.swing.JLabel;
27 +import javax.swing.JPanel;
28 +import javax.swing.JScrollPane;
29 +import javax.swing.JTable;
30 +import javax.swing.JTextField;
31 +import javax.swing.table.AbstractTableModel;
32 +import javax.swing.table.DefaultTableModel;
3 33
4 public class GUI extends JFrame { 34 public class GUI extends JFrame {
5 JTabbedPane tab = new JTabbedPane(); 35 JTabbedPane tab = new JTabbedPane();
6 - public GUI() { 36 +
37 + public GUI(List<String> q) {
7 super("CESCO"); 38 super("CESCO");
8 39
9 tab.addTab("png", new PngPane()); 40 tab.addTab("png", new PngPane());
10 - tab.addTab("gif",new GifPane()); 41 + tab.addTab("gif", new GifPane());
11 - tab.addTab("jpg",new JpgPane()); 42 + tab.addTab("jpg", new JpgPane());
43 + tab.addTab("table", new createTable(q));
12 44
13 add(tab); 45 add(tab);
14 46
...@@ -38,7 +70,7 @@ class GifPane extends JPanel { ...@@ -38,7 +70,7 @@ class GifPane extends JPanel {
38 ImageIcon image = new ImageIcon("data/model.gif"); 70 ImageIcon image = new ImageIcon("data/model.gif");
39 JLabel label = new JLabel("", image, JLabel.CENTER); 71 JLabel label = new JLabel("", image, JLabel.CENTER);
40 setLayout(new BorderLayout()); 72 setLayout(new BorderLayout());
41 - add( label, BorderLayout.CENTER ); 73 + add(label, BorderLayout.CENTER);
42 } 74 }
43 } 75 }
44 76
...@@ -48,6 +80,60 @@ class JpgPane extends JPanel { ...@@ -48,6 +80,60 @@ class JpgPane extends JPanel {
48 ImageIcon image = new ImageIcon("data/model.jpg"); 80 ImageIcon image = new ImageIcon("data/model.jpg");
49 JLabel label = new JLabel("", image, JLabel.CENTER); 81 JLabel label = new JLabel("", image, JLabel.CENTER);
50 setLayout(new BorderLayout()); 82 setLayout(new BorderLayout());
51 - add( label, BorderLayout.CENTER ); 83 + add(label, BorderLayout.CENTER);
84 + }
85 +}
86 +
87 +class createTable extends JPanel {
88 +
89 + public createTable(List<String> data) { //constructor : display table
90 + getTableModel(data);
91 + }
92 +
93 + private DefaultTableModel getTableModel(List<String> data) {
94 + String column_n[]={"ip","app","device","os","channel","is_attributed","click_time",
95 + "avg_valid_click_count","click_time_delta","count_click_in_tenmin"};
96 + Object tabledata[][]={};
97 + DefaultTableModel model = new DefaultTableModel(tabledata,column_n);
98 + JTable jtable = new JTable(model);
99 + JScrollPane jScollPane = new JScrollPane(jtable);
100 + add(jScollPane);
101 + try {
102 + for(int i =0; i<data.size();i++){
103 + BufferedReader reader = getFileReader(data.get(i));
104 + String line = reader.readLine();
105 +
106 +
107 + line = line.replace("\"", "");
108 + line = line.replace("_", "");
109 + //line = line.replace("\\{","");
110 + line = line.replaceAll("\\{|\\}","");
111 + line = line.replaceAll("\\w+:", "");
112 +
113 + //System.out.println(line);
114 + Object [] temp= line.split(",");
115 +
116 + model.addRow(temp);
117 +
118 + reader.close();
119 + }
120 +
121 + } catch (Exception e) {
122 + System.out.println(e);
123 + }
124 +
125 +
126 + return model;
127 + }
128 +
129 + private BufferedReader getFileReader(String data) {
130 +
131 + BufferedReader reader = new BufferedReader(new StringReader(data));
132 +
133 + // In your real application the data would come from a file
134 +
135 + //Reader reader = new BufferedReader( new FileReader(...) );
136 +
137 + return reader;
52 } 138 }
53 } 139 }
...\ No newline at end of file ...\ No newline at end of file
......
File mode changed
1 +ionTreeRegressionModel (uid=dtr_4046612293fa) of depth 5 with 55 nodes
2 + If (feature 2 <= 0.5)
3 + If (feature 0 <= 195796.5)
4 + If (feature 5 <= 3.5)
5 + If (feature 3 <= 29.5)
6 + If (feature 0 <= 65878.0)
7 + Predict: 0.12087912087912088
8 + Else (feature 0 > 65878.0)
9 + Predict: 0.0547945205479452
10 + Else (feature 3 > 29.5)
11 + If (feature 0 <= 175794.5)
12 + Predict: 0.0
13 + Else (feature 0 > 175794.5)
14 + Predict: 0.3333333333333333
15 + Else (feature 5 > 3.5)
16 + If (feature 1 <= 19.5)
17 + Predict: 1.0
18 + Else (feature 1 > 19.5)
19 + Predict: 0.0
20 + Else (feature 0 > 195796.5)
21 + If (feature 1 <= 19.5)
22 + If (feature 0 <= 212250.0)
23 + If (feature 3 <= 3.5)
24 + Predict: 0.6666666666666666
25 + Else (feature 3 > 3.5)
26 + Predict: 0.0
27 + Else (feature 0 > 212250.0)
28 + If (feature 3 <= 3.5)
29 + Predict: 0.15384615384615385
30 + Else (feature 3 > 3.5)
31 + Predict: 0.3181818181818182
32 + Else (feature 1 > 19.5)
33 + If (feature 3 <= 47.5)
34 + Predict: 0.0
35 + Else (feature 3 > 47.5)
36 + If (feature 5 <= 0.5)
37 + Predict: 0.5
38 + Else (feature 5 > 0.5)
39 + Predict: 0.0
40 + Else (feature 2 > 0.5)
41 + If (feature 1 <= 28.5)
42 + If (feature 2 <= 3.5)
43 + If (feature 0 <= 212250.0)
44 + If (feature 0 <= 118331.5)
45 + Predict: 2.176407740097345E-4
46 + Else (feature 0 > 118331.5)
47 + Predict: 8.741258741258741E-4
48 + Else (feature 0 > 212250.0)
49 + If (feature 4 <= 115.5)
50 + Predict: 0.04215456674473068
51 + Else (feature 4 > 115.5)
52 + Predict: 0.0016492578339747114
53 + Else (feature 2 > 3.5)
54 + If (feature 1 <= 18.5)
55 + Predict: 0.0
56 + Else (feature 1 > 18.5)
57 + If (feature 0 <= 123267.0)
58 + Predict: 0.14285714285714285
59 + Else (feature 0 > 123267.0)
60 + Predict: 0.3611111111111111
61 + Else (feature 1 > 28.5)
62 + If (feature 4 <= 279.0)
63 + If (feature 0 <= 175794.5)
64 + If (feature 4 <= 265.5)
65 + Predict: 0.06231454005934718
66 + Else (feature 4 > 265.5)
67 + Predict: 0.6666666666666666
68 + Else (feature 0 > 175794.5)
69 + If (feature 4 <= 228.0)
70 + Predict: 0.36923076923076925
71 + Else (feature 4 > 228.0)
72 + Predict: 1.0
73 + Else (feature 4 > 279.0)
74 + If (feature 4 <= 333.5)
75 + If (feature 1 <= 30.5)
76 + Predict: 0.5
77 + Else (feature 1 > 30.5)
78 + Predict: 0.0
79 + Else (feature 4 > 333.5)
80 + If (feature 3 <= 8.5)
81 + Predict: 0.0234375
82 + Else (feature 3 > 8.5)
83 + Predict: 0.002178649237472767