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如何使用Paimon实现增量物化视图

提问者：帅平问题分类：面试刷题

如何使用Paimon实现增量物化视图

Paimon面试题 Paimon 数据湖

发布于：1周前 (05-27) IP属地：

3 个回答

心忘则亡

具体的实现如下：
1、创建基础表与物化视图

-- 创建源表（启用CDC）
CREATE TABLE source_orders (
  order_id BIGINT,
  user_id BIGINT,
  amount DECIMAL,
  status STRING,
  PRIMARY KEY (order_id) NOT ENFORCED
) WITH (
  'connector' = 'kafka',
  'topic' = 'orders',
  'scan.startup.mode' = 'earliest-offset',
  'format' = 'json'
);
-- 创建物化视图（带增量更新逻辑）
CREATE MATERIALIZED VIEW incremental_orders_mv
WITH (
  'materialized-view.refresh.interval' = '1m',  -- 刷新间隔
  'materialized-view.unique-key' = 'order_id'   -- 唯一键
) AS
SELECT 
  user_id,
  SUM(amount) AS total_amount,
  COUNT(DISTINCT order_id) AS order_count
FROM source_orders
GROUP BY user_id;

发布于：1周前 (05-27) IP属地：

宁愿短发披肩

3、增量更新物化视图

-- 创建更新流（处理CDC事件）
CREATE TABLE cdc_update_stream (
  order_id BIGINT,
  before ROW<status STRING>,
  after ROW<status STRING, amount DECIMAL>
) WITH (
  'connector' = 'paimon-cdc',
  'table-name' = 'source_orders'
);
-- 增量更新物化视图逻辑
INSERT INTO incremental_orders_mv
SELECT 
  COALESCE(after.user_id, before.user_id) AS user_id,
  CASE 
    WHEN after.amount IS NOT NULL THEN 
      SUM(after.amount) OVER (PARTITION BY user_id)
    ELSE 
      SUM(before.amount) OVER (PARTITION BY user_id)
  END AS total_amount,
  COUNT(DISTINCT COALESCE(after.order_id, before.order_id)) 
    OVER (PARTITION BY user_id) AS order_count
FROM cdc_update_stream;

发布于：1周前 (05-27) IP属地：

玖墨

2、配置CDC触发器

// Flink CDC连接器配置（Java示例）
DebeziumSourceFunction<RowData> sourceFunction = MySQLSource.<RowData>builder()
  .hostname("mysql-host")
  .port(3306)
  .databaseList("paimon_db")  // 监听数据库
  .tableList("paimon_db.source_orders")  // 监听表
  .deserializer(new JsonDebeziumDeserializationSchema())
  .build();
DataStream<RowData> cdcStream = env.addSource(sourceFunction);

发布于：1周前 (05-27) IP属地：

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