Detail the ES1en ES2en clustering algorithm implemented by Java
- 2020-12-21 18:02:19
- OfStack
demand
The ES4en-ES5en algorithm is executed on a field of a table in the MySQL database, and the processed data is written to the new table.
Source code and Drivers
kmeans_jb51.rar
The source code
import java.sql.*;
import java.util.*;
/**
* @author tianshl
* @version 2018/1/13 In the morning 11:13
*/
public class Kmeans {
// The source data
private List<Integer> origins = new ArrayList<>();
// Grouped data
private Map<Double, List<Integer>> grouped;
// Initial center of mass list
private List<Double> cores;
// The data source
private String tableName;
private String colName;
/**
* A constructor
*
* @param tableName The name of the source table
* @param colName Source data column name
* @param cores List of center of mass
*/
private Kmeans(String tableName, String colName,List<Double> cores){
this.cores = cores;
this.tableName = tableName;
this.colName = colName;
}
/**
* Recalculate the center of mass
*
* @return New center of mass list
*/
private List<Double> newCores(){
List<Double> newCores = new ArrayList<>();
for(List<Integer> v: grouped.values()){
newCores.add(v.stream().reduce(0, (sum, num) -> sum + num) / (v.size() + 0.0));
}
Collections.sort(newCores);
return newCores;
}
/**
* Judge whether it's over
*
* @return bool
*/
private Boolean isOver(){
List<Double> _cores = newCores();
for(int i=0, len=cores.size(); i<len; i++){
if(!cores.get(i).toString().equals(_cores.get(i).toString())){
// Use the new center of mass
cores = _cores;
return false;
}
}
return true;
}
/**
* The data packet
*/
private void setGrouped(){
grouped = new HashMap<>();
Double core;
for (Integer origin: origins) {
core = getCore(origin);
if (!grouped.containsKey(core)) {
grouped.put(core, new ArrayList<>());
}
grouped.get(core).add(origin);
}
}
/**
* Select the center of mass
*
* @param num Data to group
* @return The center of mass
*/
private Double getCore(Integer num){
// poor The list of
List<Double> diffs = new ArrayList<>();
// Calculate poor
for(Double core: cores){
diffs.add(Math.abs(num - core));
}
// The smallest difference -> The index -> The corresponding center of mass
return cores.get(diffs.indexOf(Collections.min(diffs)));
}
/**
* Establishing a database connection
* @return connection
*/
private Connection getConn(){
try {
// URL Points to the name of the database to access mydata
String url = "jdbc:mysql://localhost:3306/data_analysis_dev";
// MySQL The user name at the time of configuration
String user = "root";
// MySQL Password at configuration time
String password = "root";
// The load driver
Class.forName("com.mysql.jdbc.Driver");
// The statement Connection object
Connection conn = DriverManager.getConnection(url, user, password);
if(conn.isClosed()){
System.out.println(" Failed to connect to database !");
return null;
}
System.out.println(" Database connection successful !");
return conn;
} catch (Exception e) {
System.out.println(" Connection to database failed! ");
e.printStackTrace();
}
return null;
}
/**
* Close the database connection
*
* @param conn The connection
*/
private void close(Connection conn){
try {
if(conn != null && !conn.isClosed()) conn.close();
} catch (Exception e){
e.printStackTrace();
}
}
/**
* Get source data
*/
private void getOrigins(){
Connection conn = null;
try {
conn = getConn();
if(conn == null) return;
Statement statement = conn.createStatement();
ResultSet rs = statement.executeQuery(String.format("select %s from %s", colName, tableName));
while(rs.next()){
origins.add(rs.getInt(1));
}
conn.close();
} catch (Exception e){
e.printStackTrace();
} finally {
close(conn);
}
}
/**
* Write data to the new table
*/
private void write(){
Connection conn = null;
try {
conn = getConn();
if(conn == null) return;
// Create a table
Statement statement = conn.createStatement();
// Delete old tables
statement.execute("DROP TABLE IF EXISTS k_means; ");
// Create a new table
statement.execute("CREATE TABLE IF NOT EXISTS k_means(`core` DECIMAL(11, 7), `col` INTEGER(11));");
// Automatic submission is prohibited
conn.setAutoCommit(false);
PreparedStatement ps = conn.prepareStatement("INSERT INTO k_means VALUES (?, ?)");
for(Map.Entry<Double, List<Integer>> entry: grouped.entrySet()){
Double core = entry.getKey();
for(Integer value: entry.getValue()){
ps.setDouble(1, core);
ps.setInt(2, value);
ps.addBatch();
}
}
// Batch execution
ps.executeBatch();
// Commit the transaction
conn.commit();
// Close the connection
conn.close();
} catch (Exception e){
e.printStackTrace();
} finally {
close(conn);
}
}
/**
* Process the data
*/
private void run(){
System.out.println(" Get source data ");
// Get source data
getOrigins();
// Stop the grouping
Boolean isOver = false;
System.out.println(" Data grouping processing ");
while(!isOver) {
// The data packet
setGrouped();
// Determine whether to stop grouping
isOver = isOver();
}
System.out.println(" Writes the processed data to the database ");
// Writes the packet data to the new table
write();
System.out.println(" Finished writing the data ");
}
public static void main(String[] args){
List<Double> cores = new ArrayList<>();
cores.add(260.0);
cores.add(600.0);
// The name of the table , The column name , List of center of mass
new Kmeans("attributes", "attr_length", cores).run();
}
}
The source file
Kmeans.java
compile
javac Kmeans.java
run
# Specify dependency libraries
java -Djava.ext.dirs=./lib Kmeans