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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.
COUNT - so deduplication is needed before further analysis.
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
ROW_NUMBER(): Assigns an unique, sequential number to each row, starting with one.
PARTITION BY col1[, col2...]: Specifies the partition columns, i.e. the deduplicate key.
ORDER BY time_attr [asc|desc]: Specifies the ordering column, it must be a time attribute. Currently Flink supports processing time attribute and event time attribute. Ordering by ASC means keeping the first row, ordering by DESC means keeping the last row.
WHERE rownum = 1: The
rownum = 1is required for Flink to recognize this query is deduplication.
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