个人主页：Guiat
归属专栏：Oracle
文章目录
- 1. 分区表基础概述
- 1.1 分区表的概念与优势
- 1.2 分区类型概览
- 1.3 分区表的工作原理
- 2. 范围分区 (RANGE Partitioning)
- 2.1 基础范围分区
- 2.1.1 按日期范围分区
- 2.1.2 按数值范围分区
- 2.2 间隔分区 (INTERVAL Partitioning)
- 2.2.1 自动创建月度分区
- 2.2.2 间隔分区的管理操作
- 3. 列表分区 (LIST Partitioning)
- 3.1 基础列表分区
- 3.1.1 按地区分区
- 3.1.2 按状态分区
- 3.2 列表分区的动态管理
- 3.2.1 分区值管理
- 4. 哈希分区 (HASH Partitioning)
- 4.1 基础哈希分区
- 4.1.1 均匀数据分布
- 4.1.2 多列哈希分区
- 4.2 哈希分区的性能优化
- 4.2.1 并行查询优化
- 5. 复合分区 (Composite Partitioning)
- 5.1 范围-哈希复合分区
- 5.1.1 按日期范围和哈希的复合分区
- 5.1.2 复合分区的查询优化
正文
1. 分区表基础概述
分区表是Oracle数据库中将大表物理分割成多个较小、更易管理的片段的技术。每个分区可以独立管理，同时对应用程序保持透明。
1.1 分区表的概念与优势
1.2 分区类型概览
1.3 分区表的工作原理
2. 范围分区 (RANGE Partitioning)
2.1 基础范围分区
2.1.1 按日期范围分区
-- 创建按日期范围分区的销售表
CREATE TABLE sales_range_date (
sale_id NUMBER,
customer_id NUMBER,
product_id NUMBER,
sale_date DATE,
amount NUMBER(10,2),
quantity NUMBER,
sales_rep_id NUMBER
)
PARTITION BY RANGE (sale_date) (
PARTITION sales_2020 VALUES LESS THAN (DATE '2021-01-01'),
PARTITION sales_2021 VALUES LESS THAN (DATE '2022-01-01'),
PARTITION sales_2022 VALUES LESS THAN (DATE '2023-01-01'),
PARTITION sales_2023 VALUES LESS THAN (DATE '2024-01-01'),
PARTITION sales_future VALUES LESS THAN (MAXVALUE)
);
-- 创建分区表的索引
CREATE INDEX idx_sales_range_customer ON sales_range_date (customer_id) LOCAL;
CREATE INDEX idx_sales_range_product ON sales_range_date (product_id) LOCAL;
-- 插入测试数据
INSERT INTO sales_range_date VALUES (1, 1001, 2001, DATE '2020-03-15', 1500.00, 3, 501);
INSERT INTO sales_range_date VALUES (2, 1002, 2002, DATE '2021-06-20', 2300.50, 5, 502);
INSERT INTO sales_range_date VALUES (3, 1003, 2003, DATE '2022-09-10', 890.75, 2, 503);
INSERT INTO sales_range_date VALUES (4, 1004, 2004, DATE '2023-12-05', 3200.00, 8, 504);
INSERT INTO sales_range_date VALUES (5, 1005, 2005, DATE '2024-02-14', 1750.25, 4, 505);
COMMIT;
-- 查看分区信息
SELECT table_name, partition_name, high_value, num_rows, blocks
FROM user_tab_partitions
WHERE table_name = 'SALES_RANGE_DATE'
ORDER BY partition_position;
-- 演示分区消除
EXPLAIN PLAN FOR
SELECT * FROM sales_range_date
WHERE sale_date BETWEEN DATE '2022-01-01' AND DATE '2022-12-31';
SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY);
2.1.2 按数值范围分区
-- 创建按员工ID范围分区的员工表
CREATE TABLE employees_range_id (
employee_id NUMBER,
first_name VARCHAR2(50),
last_name VARCHAR2(50),
email VARCHAR2(100),
hire_date DATE,
salary NUMBER(8,2),
department_id NUMBER
)
PARTITION BY RANGE (employee_id) (
PARTITION emp_1_1000 VALUES LESS THAN (1001),
PARTITION emp_1001_2000 VALUES LESS THAN (2001),
PARTITION emp_2001_3000 VALUES LESS THAN (3001),
PARTITION emp_3001_4000 VALUES LESS THAN (4001),
PARTITION emp_others VALUES LESS THAN (MAXVALUE)
);
-- 插入测试数据
INSERT INTO employees_range_id VALUES (500, 'John', 'Doe', 'john.doe@company.com', SYSDATE, 5000, 10);
INSERT INTO employees_range_id VALUES (1500, 'Jane', 'Smith', 'jane.smith@company.com', SYSDATE, 6000, 20);
INSERT INTO employees_range_id VALUES (2500, 'Bob', 'Johnson', 'bob.johnson@company.com', SYSDATE, 5500, 30);
INSERT INTO employees_range_id VALUES (3500, 'Alice', 'Brown', 'alice.brown@company.com', SYSDATE, 7000, 40);
INSERT INTO employees_range_id VALUES (5000, 'Mike', 'Wilson', 'mike.wilson@company.com', SYSDATE, 8000, 50);
COMMIT;
-- 查看数据分布
SELECT 'emp_1_1000' as partition_name, COUNT(*) as row_count FROM employees_range_id PARTITION(emp_1_1000)
UNION ALL
SELECT 'emp_1001_2000', COUNT(*) FROM employees_range_id PARTITION(emp_1001_2000)
UNION ALL
SELECT 'emp_2001_3000', COUNT(*) FROM employees_range_id PARTITION(emp_2001_3000)
UNION ALL
SELECT 'emp_3001_4000', COUNT(*) FROM employees_range_id PARTITION(emp_3001_4000)
UNION ALL
SELECT 'emp_others', COUNT(*) FROM employees_range_id PARTITION(emp_others);
2.2 间隔分区 (INTERVAL Partitioning)
2.2.1 自动创建月度分区
-- 创建间隔分区表（按月自动分区）
CREATE TABLE sales_interval_monthly (
sale_id NUMBER,
customer_id NUMBER,
product_id NUMBER,
sale_date DATE,
amount NUMBER(10,2),
quantity NUMBER
)
PARTITION BY RANGE (sale_date)
INTERVAL (NUMTOYMINTERVAL(1, 'MONTH'))
(
PARTITION sales_initial VALUES LESS THAN (DATE '2023-01-01')
);
-- 创建本地索引
CREATE INDEX idx_sales_interval_customer ON sales_interval_monthly (customer_id) LOCAL;
-- 插入跨多个月的数据，观察自动分区创建
INSERT INTO sales_interval_monthly VALUES (1, 1001, 2001, DATE '2022-12-15', 1500.00, 3);
INSERT INTO sales_interval_monthly VALUES (2, 1002, 2002, DATE '2023-01-20', 2300.50, 5);
INSERT INTO sales_interval_monthly VALUES (3, 1003, 2003, DATE '2023-02-10', 890.75, 2);
INSERT INTO sales_interval_monthly VALUES (4, 1004, 2004, DATE '2023-03-05', 3200.00, 8);
INSERT INTO sales_interval_monthly VALUES (5, 1005, 2005, DATE '2023-04-14', 1750.25, 4);
INSERT INTO sales_interval_monthly VALUES (6, 1006, 2006, DATE '2023-05-22', 2100.00, 6);
COMMIT;
-- 查看自动创建的分区
SELECT table_name, partition_name, high_value, interval
FROM user_tab_partitions
WHERE table_name = 'SALES_INTERVAL_MONTHLY'
ORDER BY partition_position;
-- 创建间隔分区表（按天自动分区）
CREATE TABLE transaction_log_daily (
transaction_id NUMBER,
user_id NUMBER,
transaction_type VARCHAR2(20),
transaction_date DATE,
amount NUMBER(12,2),
description VARCHAR2(200)
)
PARTITION BY RANGE (transaction_date)
INTERVAL (NUMTODSINTERVAL(1, 'DAY'))
(
PARTITION trans_initial VALUES LESS THAN (DATE '2024-01-01')
);
-- 插入跨多天的数据
INSERT INTO transaction_log_daily VALUES (1, 1001, 'PURCHASE', DATE '2023-12-30', 150.00, 'Online purchase');
INSERT INTO transaction_log_daily VALUES (2, 1002, 'REFUND', DATE '2024-01-01', -50.00, 'Product return');
INSERT INTO transaction_log_daily VALUES (3, 1003, 'PURCHASE', DATE '2024-01-02', 300.00, 'Store purchase');
INSERT INTO transaction_log_daily VALUES (4, 1004, 'TRANSFER', DATE '2024-01-03', 1000.00, 'Account transfer');
COMMIT;
-- 查看每日分区
SELECT partition_name, high_value, num_rows
FROM user_tab_partitions
WHERE table_name = 'TRANSACTION_LOG_DAILY'
ORDER BY partition_position;
2.2.2 间隔分区的管理操作
-- 创建间隔分区管理存储过程
CREATE OR REPLACE PROCEDURE manage_interval_partitions(
p_table_name IN VARCHAR2,
p_keep_months IN NUMBER DEFAULT 12
)
AS
v_sql VARCHAR2(4000);
v_partition_count NUMBER := 0;
v_dropped_count NUMBER := 0;
v_cutoff_date DATE;
BEGIN
DBMS_OUTPUT.PUT_LINE('=== 间隔分区管理 ===');
DBMS_OUTPUT.PUT_LINE('表名: ' || p_table_name);
DBMS_OUTPUT.PUT_LINE('保留月数: ' || p_keep_months);
-- 计算截止日期
v_cutoff_date := ADD_MONTHS(TRUNC(SYSDATE, 'MM'), -p_keep_months);
DBMS_OUTPUT.PUT_LINE('删除截止日期: ' || TO_CHAR(v_cutoff_date, 'YYYY-MM-DD'));
DBMS_OUTPUT.PUT_LINE('');
-- 查询需要删除的分区
FOR rec IN (
SELECT partition_name, high_value
FROM user_tab_partitions
WHERE table_name = UPPER(p_table_name)
AND interval = 'YES'
ORDER BY partition_position
) LOOP
v_partition_count := v_partition_count + 1;
-- 解析high_value中的日期
DECLARE
v_high_date DATE;
v_high_value_str VARCHAR2(4000);
BEGIN
-- 获取分区的上界值
SELECT high_value INTO v_high_value_str
FROM user_tab_partitions
WHERE table_name = UPPER(p_table_name)
AND partition_name = rec.partition_name;
-- 执行动态SQL获取日期值
EXECUTE IMMEDIATE 'SELECT ' || v_high_value_str || ' FROM dual' INTO v_high_date;
DBMS_OUTPUT.PUT_LINE('分区: ' || rec.partition_name ||
', 上界: ' || TO_CHAR(v_high_date, 'YYYY-MM-DD'));
-- 如果分区太旧，删除它
IF v_high_date <= v_cutoff_date THEN
v_sql := 'ALTER TABLE ' || p_table_name || ' DROP PARTITION ' || rec.partition_name;
EXECUTE IMMEDIATE v_sql;
v_dropped_count := v_dropped_count + 1;
DBMS_OUTPUT.PUT_LINE(' -> 已删除');
ELSE
DBMS_OUTPUT.PUT_LINE(' -> 保留');
END IF;
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE(' -> 处理错误: ' || SQLERRM);
END;
END LOOP;
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('=== 管理完成 ===');
DBMS_OUTPUT.PUT_LINE('检查分区数: ' || v_partition_count);
DBMS_OUTPUT.PUT_LINE('删除分区数: ' || v_dropped_count);
DBMS_OUTPUT.PUT_LINE('保留分区数: ' || (v_partition_count - v_dropped_count));
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE('管理过程出错: ' || SQLERRM);
END;
/
-- 测试分区管理
EXEC manage_interval_partitions('SALES_INTERVAL_MONTHLY', 6);
3. 列表分区 (LIST Partitioning)
3.1 基础列表分区
3.1.1 按地区分区
-- 创建按地区列表分区的客户表
CREATE TABLE customers_list_region (
customer_id NUMBER,
customer_name VARCHAR2(100),
email VARCHAR2(100),
phone VARCHAR2(20),
region VARCHAR2(20),
country VARCHAR2(50),
registration_date DATE,
status VARCHAR2(20)
)
PARTITION BY LIST (region) (
PARTITION customers_north VALUES ('NORTH', 'NORTHEAST', 'NORTHWEST'),
PARTITION customers_south VALUES ('SOUTH', 'SOUTHEAST', 'SOUTHWEST'),
PARTITION customers_east VALUES ('EAST', 'CENTRAL_EAST'),
PARTITION customers_west VALUES ('WEST', 'CENTRAL_WEST'),
PARTITION customers_international VALUES ('INTERNATIONAL', 'OVERSEAS'),
PARTITION customers_default VALUES (DEFAULT)
);
-- 插入测试数据
INSERT INTO customers_list_region VALUES (1, 'ABC Corp', 'contact@abc.com', '555-0001', 'NORTH', 'USA', SYSDATE, 'ACTIVE');
INSERT INTO customers_list_region VALUES (2, 'XYZ Ltd', 'info@xyz.com', '555-0002', 'SOUTH', 'USA', SYSDATE, 'ACTIVE');
INSERT INTO customers_list_region VALUES (3, 'Global Inc', 'sales@global.com', '555-0003', 'INTERNATIONAL', 'UK', SYSDATE, 'ACTIVE');
INSERT INTO customers_list_region VALUES (4, 'Local Store', 'hello@local.com', '555-0004', 'EAST', 'USA', SYSDATE, 'INACTIVE');
INSERT INTO customers_list_region VALUES (5, 'Unknown Co', 'contact@unknown.com', '555-0005', 'OTHER', 'CANADA', SYSDATE, 'PENDING');
COMMIT;
-- 查看数据分布
SELECT
p.partition_name,
p.high_value,
NVL(s.num_rows, 0) as row_count
FROM user_tab_partitions p
LEFT JOIN user_tab_statistics s ON p.table_name = s.table_name AND p.partition_name = s.partition_name
WHERE p.table_name = 'CUSTOMERS_LIST_REGION'
ORDER BY p.partition_position;
-- 查询特定分区的数据
SELECT * FROM customers_list_region PARTITION(customers_north);
SELECT * FROM customers_list_region PARTITION(customers_default);
3.1.2 按状态分区
-- 创建按订单状态分区的订单表
CREATE TABLE orders_list_status (
order_id NUMBER,
customer_id NUMBER,
order_date DATE,
total_amount NUMBER(10,2),
order_status VARCHAR2(20),
payment_method VARCHAR2(20),
shipping_address VARCHAR2(200)
)
PARTITION BY LIST (order_status) (
PARTITION orders_pending VALUES ('PENDING', 'SUBMITTED', 'PROCESSING'),
PARTITION orders_confirmed VALUES ('CONFIRMED', 'PAID', 'PREPARING'),
PARTITION orders_shipped VALUES ('SHIPPED', 'IN_TRANSIT', 'OUT_FOR_DELIVERY'),
PARTITION orders_completed VALUES ('DELIVERED', 'COMPLETED'),
PARTITION orders_cancelled VALUES ('CANCELLED', 'REFUNDED', 'RETURNED'),
PARTITION orders_other VALUES (DEFAULT)
);
-- 插入测试数据
INSERT INTO orders_list_status VALUES (1001, 1, SYSDATE-5, 150.00, 'PENDING', 'CREDIT_CARD', '123 Main St');
INSERT INTO orders_list_status VALUES (1002, 2, SYSDATE-4, 250.50, 'CONFIRMED', 'PAYPAL', '456 Oak Ave');
INSERT INTO orders_list_status VALUES (1003, 3, SYSDATE-3, 89.99, 'SHIPPED', 'DEBIT_CARD', '789 Pine Rd');
INSERT INTO orders_list_status VALUES (1004, 4, SYSDATE-2, 320.00, 'DELIVERED', 'CASH', '321 Elm St');
INSERT INTO orders_list_status VALUES (1005, 5, SYSDATE-1, 175.25, 'CANCELLED', 'CREDIT_CARD', '654 Maple Dr');
INSERT INTO orders_list_status VALUES (1006, 1, SYSDATE, 99.99, 'UNKNOWN', 'BITCOIN', '987 Cedar Ln');
COMMIT;
-- 创建订单状态统计视图
CREATE OR REPLACE VIEW order_status_summary AS
SELECT
CASE
WHEN partition_name = 'ORDERS_PENDING' THEN 'Pending Orders'
WHEN partition_name = 'ORDERS_CONFIRMED' THEN 'Confirmed Orders'
WHEN partition_name = 'ORDERS_SHIPPED' THEN 'Shipped Orders'
WHEN partition_name = 'ORDERS_COMPLETED' THEN 'Completed Orders'
WHEN partition_name = 'ORDERS_CANCELLED' THEN 'Cancelled Orders'
ELSE 'Other Status'
END as status_category,
COUNT(*) as order_count,
SUM(total_amount) as total_value
FROM (
SELECT 'ORDERS_PENDING' as partition_name, total_amount FROM orders_list_status PARTITION(orders_pending)
UNION ALL
SELECT 'ORDERS_CONFIRMED', total_amount FROM orders_list_status PARTITION(orders_confirmed)
UNION ALL
SELECT 'ORDERS_SHIPPED', total_amount FROM orders_list_status PARTITION(orders_shipped)
UNION ALL
SELECT 'ORDERS_COMPLETED', total_amount FROM orders_list_status PARTITION(orders_completed)
UNION ALL
SELECT 'ORDERS_CANCELLED', total_amount FROM orders_list_status PARTITION(orders_cancelled)
UNION ALL
SELECT 'ORDERS_OTHER', total_amount FROM orders_list_status PARTITION(orders_other)
)
GROUP BY partition_name
ORDER BY order_count DESC;
-- 查看订单状态汇总
SELECT * FROM order_status_summary;
3.2 列表分区的动态管理
3.2.1 分区值管理
-- 创建列表分区管理存储过程
CREATE OR REPLACE PROCEDURE manage_list_partition_values(
p_table_name IN VARCHAR2,
p_partition_name IN VARCHAR2,
p_action IN VARCHAR2, -- 'ADD' or 'DROP'
p_values IN VARCHAR2 -- 逗号分隔的值列表
)
AS
v_sql VARCHAR2(4000);
v_current_values CLOB;
TYPE value_array IS TABLE OF VARCHAR2(100);
v_values_to_process value_array;
v_value VARCHAR2(100);
v_pos NUMBER;
v_remaining VARCHAR2(4000);
BEGIN
DBMS_OUTPUT.PUT_LINE('=== 列表分区值管理 ===');
DBMS_OUTPUT.PUT_LINE('表名: ' || p_table_name);
DBMS_OUTPUT.PUT_LINE('分区名: ' || p_partition_name);
DBMS_OUTPUT.PUT_LINE('操作: ' || p_action);
DBMS_OUTPUT.PUT_LINE('值: ' || p_values);
-- 获取当前分区值
SELECT high_value INTO v_current_values
FROM user_tab_partitions
WHERE table_name = UPPER(p_table_name)
AND partition_name = UPPER(p_partition_name);
DBMS_OUTPUT.PUT_LINE('当前分区值: ' || v_current_values);
-- 解析输入的值列表
v_remaining := p_values;
v_values_to_process := value_array();
WHILE LENGTH(v_remaining) > 0 LOOP
v_pos := INSTR(v_remaining, ',');
IF v_pos > 0 THEN
v_value := TRIM(SUBSTR(v_remaining, 1, v_pos - 1));
v_remaining := SUBSTR(v_remaining, v_pos + 1);
ELSE
v_value := TRIM(v_remaining);
v_remaining := '';
END IF;
v_values_to_process.EXTEND;
v_values_to_process(v_values_to_process.COUNT) := v_value;
END LOOP;
-- 执行操作
IF UPPER(p_action) = 'ADD' THEN
FOR i IN 1..v_values_to_process.COUNT LOOP
v_sql := 'ALTER TABLE ' || p_table_name ||
' MODIFY PARTITION ' || p_partition_name ||
' ADD VALUES (''' || v_values_to_process(i) || ''')';
BEGIN
EXECUTE IMMEDIATE v_sql;
DBMS_OUTPUT.PUT_LINE('已添加值: ' || v_values_to_process(i));
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE('添加值失败 ' || v_values_to_process(i) || ': ' || SQLERRM);
END;
END LOOP;
ELSIF UPPER(p_action) = 'DROP' THEN
FOR i IN 1..v_values_to_process.COUNT LOOP
v_sql := 'ALTER TABLE ' || p_table_name ||
' MODIFY PARTITION ' || p_partition_name ||
' DROP VALUES (''' || v_values_to_process(i) || ''')';
BEGIN
EXECUTE IMMEDIATE v_sql;
DBMS_OUTPUT.PUT_LINE('已删除值: ' || v_values_to_process(i));
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE('删除值失败 ' || v_values_to_process(i) || ': ' || SQLERRM);
END;
END LOOP;
ELSE
RAISE_APPLICATION_ERROR(-20001, '无效的操作类型: ' || p_action);
END IF;
-- 显示更新后的分区值
SELECT high_value INTO v_current_values
FROM user_tab_partitions
WHERE table_name = UPPER(p_table_name)
AND partition_name = UPPER(p_partition_name);
DBMS_OUTPUT.PUT_LINE('更新后分区值: ' || v_current_values);
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE('操作失败: ' || SQLERRM);
END;
/
-- 测试分区值管理
-- 为customers_north分区添加新的地区值
EXEC manage_list_partition_values('CUSTOMERS_LIST_REGION', 'CUSTOMERS_NORTH', 'ADD', 'NORTH_CENTRAL,UPPER_NORTH');
-- 查看更新后的分区信息
SELECT partition_name, high_value
FROM user_tab_partitions
WHERE table_name = 'CUSTOMERS_LIST_REGION'
AND partition_name = 'CUSTOMERS_NORTH';
4. 哈希分区 (HASH Partitioning)
4.1 基础哈希分区
4.1.1 均匀数据分布
-- 创建哈希分区表用于均匀分布数据
CREATE TABLE products_hash (
product_id NUMBER,
product_name VARCHAR2(100),
category_id NUMBER,
price NUMBER(10,2),
supplier_id NUMBER,
created_date DATE,
status VARCHAR2(20)
)
PARTITION BY HASH (product_id)
PARTITIONS 8;
-- 创建本地索引
CREATE INDEX idx_products_hash_category ON products_hash (category_id) LOCAL;
CREATE INDEX idx_products_hash_supplier ON products_hash (supplier_id) LOCAL;
-- 批量插入测试数据
DECLARE
v_categories NUMBER := 10;
v_suppliers NUMBER := 20;
v_statuses SYS.ODCIVARCHAR2LIST := SYS.ODCIVARCHAR2LIST('ACTIVE', 'INACTIVE', 'DISCONTINUED', 'PENDING');
BEGIN
FOR i IN 1..10000 LOOP
INSERT INTO products_hash VALUES (
i,
'Product ' || i,
MOD(i, v_categories) + 1,
ROUND(DBMS_RANDOM.VALUE(10, 1000), 2),
MOD(i, v_suppliers) + 1,
SYSDATE - DBMS_RANDOM.VALUE(0, 365),
v_statuses(MOD(i, 4) + 1)
);
-- 每1000条提交一次
IF MOD(i, 1000) = 0 THEN
COMMIT;
END IF;
END LOOP;
COMMIT;
END;
/
-- 查看哈希分区的数据分布
SELECT
partition_name,
num_rows,
blocks,
avg_row_len
FROM user_tab_partitions
WHERE table_name = 'PRODUCTS_HASH'
ORDER BY partition_name;
-- 收集统计信息
EXEC DBMS_STATS.GATHER_TABLE_STATS(USER, 'PRODUCTS_HASH');
-- 再次查看分布（收集统计信息后）
SELECT
partition_name,
num_rows,
ROUND(num_rows * 100.0 / SUM(num_rows) OVER(), 2) as percentage,
blocks
FROM user_tab_partitions
WHERE table_name = 'PRODUCTS_HASH'
ORDER BY partition_name;
4.1.2 多列哈希分区
-- 创建基于多列的哈希分区表
CREATE TABLE user_activities_hash (
user_id NUMBER,
activity_date DATE,
activity_type VARCHAR2(50),
session_id VARCHAR2(100),
duration_minutes NUMBER,
page_views NUMBER,
device_type VARCHAR2(20)
)
PARTITION BY HASH (user_id, activity_date)
PARTITIONS 16;
-- 插入测试数据
DECLARE
v_activity_types SYS.ODCIVARCHAR2LIST := SYS.ODCIVARCHAR2LIST(
'LOGIN', 'BROWSE', 'SEARCH', 'PURCHASE', 'LOGOUT', 'DOWNLOAD', 'UPLOAD'
);
v_device_types SYS.ODCIVARCHAR2LIST := SYS.ODCIVARCHAR2LIST(
'DESKTOP', 'MOBILE', 'TABLET'
);
BEGIN
FOR i IN 1..50000 LOOP
INSERT INTO user_activities_hash VALUES (
TRUNC(DBMS_RANDOM.VALUE(1, 5000)),
SYSDATE - DBMS_RANDOM.VALUE(0, 30),
v_activity_types(TRUNC(DBMS_RANDOM.VALUE(1, 8))),
'SESSION_' || LPAD(i, 8, '0'),
TRUNC(DBMS_RANDOM.VALUE(1, 120)),
TRUNC(DBMS_RANDOM.VALUE(1, 50)),
v_device_types(TRUNC(DBMS_RANDOM.VALUE(1, 4)))
);
IF MOD(i, 5000) = 0 THEN
COMMIT;
DBMS_OUTPUT.PUT_LINE('已插入 ' || i || ' 条记录');
END IF;
END LOOP;
COMMIT;
END;
/
-- 收集统计信息
EXEC DBMS_STATS.GATHER_TABLE_STATS(USER, 'USER_ACTIVITIES_HASH');
-- 分析哈希分区的均匀性
SELECT
partition_name,
num_rows,
ROUND(num_rows * 100.0 / SUM(num_rows) OVER(), 2) as percentage,
blocks,
avg_row_len
FROM user_tab_partitions
WHERE table_name = 'USER_ACTIVITIES_HASH'
ORDER BY num_rows DESC;
-- 计算分布的标准差（衡量均匀性）
WITH partition_stats AS (
SELECT num_rows
FROM user_tab_partitions
WHERE table_name = 'USER_ACTIVITIES_HASH'
)
SELECT
ROUND(AVG(num_rows), 2) as avg_rows_per_partition,
ROUND(STDDEV(num_rows), 2) as stddev_rows,
ROUND(STDDEV(num_rows) / AVG(num_rows) * 100, 2) as coefficient_of_variation
FROM partition_stats;
4.2 哈希分区的性能优化
4.2.1 并行查询优化
-- 创建并行查询测试存储过程
CREATE OR REPLACE PROCEDURE test_hash_partition_performance(
p_parallel_degree IN NUMBER DEFAULT 4
)
AS
v_start_time TIMESTAMP;
v_end_time TIMESTAMP;
v_elapsed_seconds NUMBER;
v_result_count NUMBER;
v_total_amount NUMBER;
BEGIN
DBMS_OUTPUT.PUT_LINE('=== 哈希分区性能测试 ===');
DBMS_OUTPUT.PUT_LINE('并行度: ' || p_parallel_degree);
-- 设置并行度
EXECUTE IMMEDIATE 'ALTER TABLE products_hash PARALLEL ' || p_parallel_degree;
-- 测试1: 全表扫描聚合查询
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('测试1: 全表聚合查询');
v_start_time := SYSTIMESTAMP;
SELECT COUNT(*), SUM(price)
INTO v_result_count, v_total_amount
FROM products_hash
WHERE status = 'ACTIVE';
v_end_time := SYSTIMESTAMP;
v_elapsed_seconds := EXTRACT(SECOND FROM (v_end_time - v_start_time));
DBMS_OUTPUT.PUT_LINE('结果: ' || v_result_count || ' 行, 总金额: ' || ROUND(v_total_amount, 2));
DBMS_OUTPUT.PUT_LINE('执行时间: ' || v_elapsed_seconds || ' 秒');
-- 测试2: 分区连接查询
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('测试2: 分区连接查询');
v_start_time := SYSTIMESTAMP;
SELECT COUNT(*)
INTO v_result_count
FROM products_hash p
JOIN user_activities_hash u ON MOD(p.product_id, 1000) = MOD(u.user_id, 1000)
WHERE p.status = 'ACTIVE'
AND u.activity_type = 'PURCHASE';
v_end_time := SYSTIMESTAMP;
v_elapsed_seconds := EXTRACT(SECOND FROM (v_end_time - v_start_time));
DBMS_OUTPUT.PUT_LINE('连接结果: ' || v_result_count || ' 行');
DBMS_OUTPUT.PUT_LINE('执行时间: ' || v_elapsed_seconds || ' 秒');
-- 测试3: 分区级别的统计
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('测试3: 分区级别统计');
v_start_time := SYSTIMESTAMP;
FOR rec IN (
SELECT
'SYS_P' || ROWNUM as partition_name,
COUNT(*) as row_count,
AVG(price) as avg_price,
MAX(price) as max_price
FROM (
SELECT price FROM products_hash PARTITION(SYS_P81)
UNION ALL SELECT price FROM products_hash PARTITION(SYS_P82)
UNION ALL SELECT price FROM products_hash PARTITION(SYS_P83)
UNION ALL SELECT price FROM products_hash PARTITION(SYS_P84)
)
GROUP BY 'SYS_P' || ROWNUM
) LOOP
NULL; -- 只是为了测试执行时间
END LOOP;
v_end_time := SYSTIMESTAMP;
v_elapsed_seconds := EXTRACT(SECOND FROM (v_end_time - v_start_time));
DBMS_OUTPUT.PUT_LINE('分区统计执行时间: ' || v_elapsed_seconds || ' 秒');
-- 重置并行度
EXECUTE IMMEDIATE 'ALTER TABLE products_hash NOPARALLEL';
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE('测试过程出错: ' || SQLERRM);
EXECUTE IMMEDIATE 'ALTER TABLE products_hash NOPARALLEL';
END;
/
-- 执行性能测试
EXEC test_hash_partition_performance(2);
EXEC test_hash_partition_performance(4);
5. 复合分区 (Composite Partitioning)
5.1 范围-哈希复合分区
5.1.1 按日期范围和哈希的复合分区
-- 创建范围-哈希复合分区表
CREATE TABLE sales_composite_range_hash (
sale_id NUMBER,
customer_id NUMBER,
product_id NUMBER,
sale_date DATE,
amount NUMBER(10,2),
quantity NUMBER,
sales_rep_id NUMBER,
region VARCHAR2(20)
)
PARTITION BY RANGE (sale_date)
SUBPARTITION BY HASH (customer_id)
SUBPARTITIONS 4
(
PARTITION sales_2022 VALUES LESS THAN (DATE '2023-01-01'),
PARTITION sales_2023 VALUES LESS THAN (DATE '2024-01-01'),
PARTITION sales_2024 VALUES LESS THAN (DATE '2025-01-01'),
PARTITION sales_future VALUES LESS THAN (MAXVALUE)
);
-- 查看复合分区结构
SELECT
partition_name,
subpartition_name,
high_value,
subpartition_position
FROM user_tab_subpartitions
WHERE table_name = 'SALES_COMPOSITE_RANGE_HASH'
ORDER BY partition_name, subpartition_position;
-- 插入测试数据
DECLARE
v_regions SYS.ODCIVARCHAR2LIST := SYS.ODCIVARCHAR2LIST('NORTH', 'SOUTH', 'EAST', 'WEST');
BEGIN
FOR i IN 1..20000 LOOP
INSERT INTO sales_composite_range_hash VALUES (
i,
TRUNC(DBMS_RANDOM.VALUE(1, 1000)),
TRUNC(DBMS_RANDOM.VALUE(1, 500)),
DATE '2022-01-01' + DBMS_RANDOM.VALUE(0, 1095), -- 3年范围
ROUND(DBMS_RANDOM.VALUE(10, 5000), 2),
TRUNC(DBMS_RANDOM.VALUE(1, 20)),
TRUNC(DBMS_RANDOM.VALUE(1, 50)),
v_regions(TRUNC(DBMS_RANDOM.VALUE(1, 5)))
);
IF MOD(i, 2000) = 0 THEN
COMMIT;
DBMS_OUTPUT.PUT_LINE('已插入 ' || i || ' 条记录');
END IF;
END LOOP;
COMMIT;
END;
/
-- 收集统计信息
EXEC DBMS_STATS.GATHER_TABLE_STATS(USER, 'SALES_COMPOSITE_RANGE_HASH');
-- 分析数据分布
SELECT
partition_name,
subpartition_name,
num_rows,
blocks
FROM user_tab_subpartitions
WHERE table_name = 'SALES_COMPOSITE_RANGE_HASH'
AND num_rows > 0
ORDER BY partition_name, subpartition_name;
5.1.2 复合分区的查询优化
-- 创建复合分区查询分析存储过程
CREATE OR REPLACE PROCEDURE analyze_composite_partition_queries
AS
v_count NUMBER;
v_amount NUMBER;
BEGIN
DBMS_OUTPUT.PUT_LINE('=== 复合分区查询分析 ===');
-- 查询1: 分区消除 - 只访问特定日期范围
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('查询1: 日期范围查询（分区消除）');
EXPLAIN PLAN FOR
SELECT COUNT(*), SUM(amount)
FROM sales_composite_range_hash
WHERE sale_date BETWEEN DATE '2023-01-01' AND DATE '2023-12-31';
SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY(FORMAT => 'BASIC +PARTITION'));
-- 查询2: 子分区消除 - 特定客户和日期
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('查询2: 客户和日期查询（子分区消除）');
EXPLAIN PLAN FOR
SELECT *
FROM sales_composite_range_hash
WHERE customer_id = 123
AND sale_date BETWEEN DATE '2023-06-01' AND DATE '2023-06-30';
SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY(FORMAT => 'BASIC +PARTITION'));
-- 查询3: 跨分区聚合
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('查询3: 跨分区聚合查询');
SELECT
EXTRACT(YEAR FROM sale_date) as sale_year,
region,
COUNT(*) as transaction_count,
SUM(amount) as total_amount,
AVG(amount) as avg_amount
FROM sales_composite_range_hash
WHERE sale_date >= DATE '2022-01-01'
GROUP BY EXTRACT(YEAR FROM sale_date), region
ORDER BY sale_year, region;
-- 查询4: 分区级别的并行处理
DBMS_OUTPUT.PUT_LINE('');
DBMS_OUTPUT.PUT_LINE('查询4: 分区级别统计');
FOR rec IN (
SELECT
partition_name,
subpartition_name,
COUNT(*) as row_count,
SUM(amount) as total_amount
FROM (
SELECT 'SALES_2023' as partition_name, 'SYS_SUBP101' as subpartition_name, amount
FROM sales_composite_range_hash SUBPARTITION(SYS_SUBP101)
UNION ALL
SELECT 'SALES_2023', 'SYS_SUBP102', amount
FROM sales_composite_range_hash SUBPARTITION(SYS_SUBP102)
UNION ALL
SELECT 'SALES_2023', 'SYS_SUBP103', amount
FROM sales_composite_range_hash SUBPARTITION(SYS_SUBP103)
UNION ALL
SELECT 'SALES_2023', 'SYS_SUBP104', amount
FROM sales_composite_range_hash SUBPARTITION(SYS_SUBP104)
)
GROUP BY partition_name, subpartition_name
ORDER BY partition_name, subpartition_name
) LOOP
DBMS_OUTPUT.PUT_LINE(rec.partition_name || '.' || rec.subpartition_name ||
': ' || rec.row_count || ' 行, 总额: $' || ROUND(rec.total_amount, 2));
END LOOP;
END;
/
-- 执行复合分区分析
EXEC analyze_composite_partition_queries;
结语
感谢您的阅读！期待您的一键三连！欢迎指正！
