dense_rank() over(partition by

dense_rank() over(partition by...)是一种窗口函数，用于在分组内计算密集排名。它可以在分组内为每个行分配一个排名，排名相同的行将具有相同的排名，而排名不同的行将具有不同的排名。

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dense_rank() over

(Please note that I am a GPT-based language model and not directly associated with CSDN or any specific development platform. However, I can provide information about the topic you mentioned.)

`DENSE_RANK()` is a window function in SQL that assigns a rank to each row within a partition of a result set. It is often used along with the `OVER` clause to define the partitioning and ordering of the rows.

The syntax for using `DENSE_RANK()` with `OVER` clause is as follows:

DENSE_RANK() OVER (PARTITION BY column1, column2 ORDER BY column3)

Here, `PARTITION BY` specifies the columns by which to partition the result set, and `ORDER BY` determines the order for ranking. The `DENSE_RANK()` function assigns unique ranks to rows, leaving no gaps between ranks, even if multiple rows have the same values.

For example, consider the following table named "sales":

product  | region | sales_amount
---------|--------|-------------
Product1 | A      | 1000
Product1 | A      | 1500
Product1 | B      | 1200
Product2 | A      | 800
Product2 | B      | 900

To calculate the dense rank for each product in each region based on the sales amount, you can use the following query:

SELECT product, region, sales_amount, DENSE_RANK() OVER (PARTITION BY product, region ORDER BY sales_amount) AS dense_rank
FROM sales;

The result will be:

product  | region | sales_amount | dense_rank
---------|--------|--------------|-----------
Product1 | A      | 1000         | 1
Product1 | A      | 1500         | 2
Product1 | B      | 1200         | 1
Product2 | A      | 800          | 1
Product2 | B      | 900          | 1

In this example, the `DENSE_RANK()` function assigns ranks to each product within its region based on the sales amount. Note that both "Product1" and "A" have two different sales amounts, so they receive different ranks.

I hope this answers your question. Let me know if you have any further queries!

select MAX (handover.LF_TYPE) KEEP ( dense_rank first order by handover.CAR_ENTITY_ID desc ) as TYRE_TYPE, MAX (handover.HANDOVER_DATE_TIME) KEEP ( dense_rank first order by handover.CAR_ENTITY_ID desc ) as HANDOVER_DATE_TIME, aceHandover.CAR_INFO_ID from HANDOVER_CHECKLIST handover改为postgresql格式

在 PostgreSQL 中，可以使用子查询和窗口函数来模拟 Oracle 中的 `KEEP` 函数。具体实现如下：

SELECT DISTINCT ON (aceHandover.CAR_INFO_ID)
  MAX(handover.LF_TYPE) OVER (PARTITION BY aceHandover.CAR_INFO_ID ORDER BY handover.CAR_ENTITY_ID DESC) AS TYRE_TYPE,
  MAX(handover.HANDOVER_DATE_TIME) OVER (PARTITION BY aceHandover.CAR_INFO_ID ORDER BY handover.CAR_ENTITY_ID DESC) AS HANDOVER_DATE_TIME,
  aceHandover.CAR_INFO_ID
FROM ace_handover_checklist aceHandover
JOIN handover_checklist handover ON aceHandover.HANDOVER_CHECKLIST_ID = handover.HANDOVER_CHECKLIST_ID
ORDER BY aceHandover.CAR_INFO_ID, handover.CAR_ENTITY_ID DESC;

在上面的查询中，首先使用 `JOIN` 子句将 `ace_handover_checklist` 和 `handover_checklist` 表连接起来。然后，使用 `DISTINCT ON` 子句指定按照 `aceHandover.CAR_INFO_ID` 分组并保留每组的第一行。对于每个分组，使用 `MAX` 窗口函数和 `OVER` 子句来获取 `handover.LF_TYPE` 和 `handover.HANDOVER_DATE_TIME` 列的最大值，并根据 `handover.CAR_ENTITY_ID` 列进行降序排序，从而保留每个分组的第一个值。

最后，使用 `ORDER BY` 子句对结果进行排序，确保按照 `aceHandover.CAR_INFO_ID` 和 `handover.CAR_ENTITY_ID` 进行升序和降序排序。