Flink基础(132):FLINK-SQL语法 (26) DQL(18) OPERATIONS(15)Deduplication 去重

时间:2021-08-30 00:31:04   收藏:0   阅读:19

Deduplication 

Batch Streaming

Deduplication removes rows that duplicate over a set of columns, keeping only the first one or the last one. In some cases, the upstream ETL jobs are not end-to-end exactly-once; this may result in duplicate records in the sink in case of failover. However, the duplicate records will affect the correctness of downstream analytical jobs - e.g. SUM, COUNT - so deduplication is needed before further analysis.

Flink uses ROW_NUMBER() to remove duplicates, just like the way of Top-N query. In theory, deduplication is a special case of Top-N in which the N is one and order by the processing time or event time.

The following shows the syntax of the Deduplication statement:

SELECT [column_list]
FROM (
   SELECT [column_list],
     ROW_NUMBER() OVER ([PARTITION BY col1[, col2...]]
       ORDER BY time_attr [asc|desc]) AS rownum
   FROM table_name)
WHERE rownum = 1

Parameter Specification:

Note: the above pattern must be followed exactly, otherwise the optimizer won’t be able to translate the query.

The following examples show how to specify SQL queries with Deduplication on streaming tables.

CREATE TABLE Orders (
  order_time  STRING,
  user        STRING,
  product     STRING,
  num         BIGINT,
  proctime AS PROCTIME()
) WITH (...);

-- remove duplicate rows on order_id and keep the first occurrence row,
-- because there shouldn‘t be two orders with the same order_id.
SELECT order_id, user, product, num
FROM (
  SELECT *,
    ROW_NUMBER() OVER (PARTITION BY order_id ORDER BY proctime ASC) AS row_num
  FROM Orders)
WHERE row_num = 1

 

原文:https://www.cnblogs.com/qiu-hua/p/15195954.html

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