create a database called "java" with a table called "points" that has two integer columns x and y (in addition to the ID primary key)
时间: 2024-01-06 13:04:24 浏览: 29
Sure! Here's the SQL code to create the database and table you described:
```
CREATE DATABASE java;
USE java;
CREATE TABLE points (
id INT PRIMARY KEY AUTO_INCREMENT,
x INT,
y INT
);
```
This will create a new database called "java" and switch to using it. Then it will create a table called "points" with three columns: "id" (which is the primary key and will auto-increment), "x", and "y", both of which are integers.
相关问题
根据以下要求:Instead of using a binary file to save the arraylist of points, change the savaData method and the constructor of the Model class to use a database to write / read the coordinates of all the points. Use XAMPP and phpMyAdmin to create a database called "java" with a table called "points" that has two integer columns x and y (in addition to the ID primary key). Hint: make sure you delete all the old point coordinates from the database before inserting new ones. Hint: use phpMyAdmin to check what is stored in the database. Use the Test class to run all the tests for the software and check that all the tests still work. Use the Start class to run the software and check that closing the software correctly saves the point coordinates in the database (use phpMyAdmin to check the content of the database). Run the software again and check that all the points from the previous run are correctly displayed,修改下述代码:public class Model implements Serializable { private ArrayList<Point> points; private ArrayList<ModelListener> listeners; private static final String FILE_NAME = "points.bin"; public Model() { points = new ArrayList<Point>(); listeners = new ArrayList<ModelListener>(); // Read points from file if it exists File file = new File(FILE_NAME); if (file.exists()) { try { ObjectInputStream in = new ObjectInputStream(new FileInputStream(file)); points = (ArrayList<Point>) in.readObject(); in.close(); } catch (IOException e) { e.printStackTrace(); } catch (ClassNotFoundException e) { e.printStackTrace(); } } } public void addListener(ModelListener l) { listeners.add(l); } public ArrayList<Point> getPoints() { return points; } public void addPoint(Point p) { points.add(p); notifyListeners(); // points changed so notify the listeners. saveData(); // save point to file } public void clearAllPoints() { points.clear(); notifyListeners(); // points changed so notify the listeners. saveData(); // save empty list to file } public void deleteLastPoint() { if (points.size() > 0) { points.remove(points.size() - 1); notifyListeners(); // points changed so notify the listeners. saveData(); // save updated list to file } } private void notifyListeners() { for (ModelListener l : listeners) { l.update(); // Tell the listener that something changed. } } public int numberOfPoints() { return points.size(); } public void saveData() { try { ObjectOutputStream out = new ObjectOutputStream(new FileOutputStream(FILE_NAME)); out.writeObject(points); out.close(); } catch (IOException e) { e.printStackTrace(); } }
public class Model {
private ArrayList<Point> points;
private ArrayList<ModelListener> listeners;
private static final String DB_URL = "jdbc:mysql://localhost/java";
private static final String DB_USER = "root";
private static final String DB_PASSWORD = "";
public Model() {
points = new ArrayList<Point>();
listeners = new ArrayList<ModelListener>();
// Read points from database
try {
Connection conn = DriverManager.getConnection(DB_URL, DB_USER, DB_PASSWORD);
Statement stmt = conn.createStatement();
String sql = "SELECT * FROM points";
ResultSet rs = stmt.executeQuery(sql);
while (rs.next()) {
int x = rs.getInt("x");
int y = rs.getInt("y");
Point p = new Point(x, y);
points.add(p);
}
rs.close();
stmt.close();
conn.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
public void addListener(ModelListener l) {
listeners.add(l);
}
public ArrayList<Point> getPoints() {
return points;
}
public void addPoint(Point p) {
points.add(p);
notifyListeners(); // points changed so notify the listeners.
saveData(); // save point to database
}
public void clearAllPoints() {
points.clear();
notifyListeners(); // points changed so notify the listeners.
saveData(); // save empty list to database
}
public void deleteLastPoint() {
if (points.size() > 0) {
points.remove(points.size() - 1);
notifyListeners(); // points changed so notify the listeners.
saveData(); // save updated list to database
}
}
private void notifyListeners() {
for (ModelListener l : listeners) {
l.update(); // Tell the listener that something changed.
}
}
public int numberOfPoints() {
return points.size();
}
public void saveData() {
try {
Connection conn = DriverManager.getConnection(DB_URL, DB_USER, DB_PASSWORD);
Statement stmt = conn.createStatement();
String sql = "DELETE FROM points";
stmt.executeUpdate(sql);
for (Point p : points) {
sql = "INSERT INTO points (x, y) VALUES (" + p.x + ", " + p.y + ")";
stmt.executeUpdate(sql);
}
stmt.close();
conn.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
}
How to optimize queries in Hive? How to create a partition table with Hive?
To optimize queries in Hive, you can follow these best practices:
1. Use partitioning: Partitioning is a technique of dividing a large table into smaller, more manageable parts based on specific criteria such as date, region, or category. It can significantly improve query performance by reducing the amount of data that needs to be scanned.
2. Use bucketing: Bucketing is another technique of dividing a large table into smaller, more manageable parts based on the hash value of a column. It can improve query performance by reducing the number of files that need to be read.
3. Use appropriate file formats: Choose the appropriate file format based on the type of data and the query patterns. For example, ORC and Parquet formats are optimized for analytical queries, while Text and SequenceFile formats are suitable for batch processing.
4. Optimize data storage: Optimize the way data is stored on HDFS to improve query performance. For example, use compression to reduce the amount of data that needs to be transferred across the network.
To create a partition table with Hive, you can follow these steps:
1. Create a database (if it doesn't exist) using the CREATE DATABASE statement.
2. Create a table using the CREATE TABLE statement, specifying the partition columns using the PARTITIONED BY clause.
3. Load data into the table using the LOAD DATA statement, specifying the partition values using the PARTITION clause.
Here's an example:
```
CREATE DATABASE my_db;
USE my_db;
CREATE TABLE my_table (
id INT,
name STRING
) PARTITIONED BY (date STRING);
LOAD DATA LOCAL INPATH '/path/to/data' OVERWRITE INTO TABLE my_table PARTITION (date='2022-01-01');
```
This creates a table called `my_table` with two columns `id` and `name`, and one partition column `date`. The data is loaded into the table with the partition value `2022-01-01`.