Oracle sql 或 pl/sql：根据前一行值和日期列计算
Oracle sql or pl/sql: Compute based on previous row values and on date column
我在 Python 技术上找到了很多与我的问题相关的解决方案，但在 Oracle SQL 或 PL/SQL 上找不到很多解决方案。所以在 Oracle SQL 上使用 Oracle Application Express 进行尝试。
我的数据库 table 具有以下 8 天的股票样本数据。每天收市后都会插入新记录。我有查询要查找价格连续 increase/decrease 的股票。现在我想再添加一列，我可以在其中看到一个基于当前日期和之前日期值的称为看涨或看跌的模式。
+-------+------------+--------+-------+-------+--------+--------+
| Stock | Cdate | Open | High | Low | Close | Volume |
+-------+------------+--------+-------+-------+--------+--------+
| XYZ | 01-01-2021 | 40 | 40.5 | 38.5 | 38.8 | 83057 |
| XYZ | 02-01-2021 | 39.2 | 39.2 | 37.2 | 37.8 | 181814 |
| XYZ | 03-01-2021 | 38 | 38.5 | 36.5 | 37 | 117378 |
| XYZ | 04-01-2021 | 36 | 36.1 | 35.6 | 35.7 | 93737 |
| XYZ | 05-01-2021 | 35.35 | 36.8 | 35.1 | 36.6 | 169106 |
| XYZ | 06-01-2021 | 36.5 | 38.5 | 36.5 | 38 | 123179 |
| XYZ | 07-01-2021 | 37.5 | 39.5 | 37.3 | 39.4 | 282986 |
| XYZ | 08-01-2021 | 39 | 40.5 | 38.5 | 40 | 117437 |
| | | | | | | |
| DDD | 01-01-2021 | 135.35 | 136.8 | 135.1 | 136.6 | 16454 |
| DDD | 02-01-2021 | 136.5 | 138.5 | 136.5 | 138 | 281461 |
| DDD | 03-01-2021 | 137.5 | 139.5 | 137.3 | 139.4 | 77334 |
| DDD | 04-01-2021 | 139 | 140.5 | 138.5 | 140 | 321684 |
| DDD | 05-01-2021 | 139.7 | 139.8 | 139.3 | 139.4 | 873009 |
| DDD | 06-01-2021 | 139.2 | 139.2 | 137.2 | 137.8 | 62522 |
| DDD | 07-01-2021 | 138 | 138.5 | 136.5 | 137 | 114826 |
| DDD | 08-01-2021 | 136.6 | 136.8 | 135.1 | 135.35 | 27317 |
+-------+------------+--------+-------+-------+--------+--------+
这是图表查找股票 XYZ 的方式：
2021 年 1 月 5 日，趋势发生了变化，我想根据以下公式添加新的“看涨”栏：
O1 > C1 and C > O and C > H1 and O < L1
其中，
O1 = Previous day Open price
C1 = Previous day Close price
C = Today's Close price
O = Today's Open price
H1 = Previous day High price
L1 = Previous day Low price
预期输出将是一个新列，在列模式下显示“看涨”：
+-------+------------+-------+------+------+-------+--------+---------+
| Stock | Cdate | Open | High | Low | Close | Volume | Pattern |
+-------+------------+-------+------+------+-------+--------+---------+
| XYZ | 01-01-2021 | 40 | 40.5 | 38.5 | 38.8 | 83057 | |
| XYZ | 02-01-2021 | 39.2 | 39.2 | 37.2 | 37.8 | 181814 | |
| XYZ | 03-01-2021 | 38 | 38.5 | 36.5 | 37 | 117378 | |
| XYZ | 04-01-2021 | 36 | 36.1 | 35.6 | 35.7 | 93737 | |
| XYZ | 05-01-2021 | 35.35 | 36.8 | 35.1 | 36.6 | 169106 | Bullish |
| XYZ | 06-01-2021 | 36.5 | 38.5 | 36.5 | 38 | 123179 | |
| XYZ | 07-01-2021 | 37.5 | 39.5 | 37.3 | 39.4 | 282986 | |
| XYZ | 08-01-2021 | 39 | 40.5 | 38.5 | 40 | 117437 | |
+-------+------------+-------+------+------+-------+--------+---------+
我在互联网上搜索了解决方案，找到的最接近的是 this。我稍微修改了查询，但无法添加公式或任何其他新列。下面是我试过的查询：
WITH StockRow AS (SELECT stock, close, cdate,
ROW_NUMBER() OVER(PARTITION BY stock
ORDER BY cdate) rn
FROM sampletable where volume > 200000),
RunGroup AS (SELECT Base.stock, Base.cdate, base.close,
MAX(Restart.rn) OVER(PARTITION BY Base.stock
ORDER BY Base.cdate) groupingId
FROM StockRow Base
LEFT JOIN StockRow Restart
ON Restart.stock = Base.stock
AND Restart.rn = Base.rn - 1
AND Restart.CLOSE < Base.CLOSE)
SELECT stock,
COUNT(*) AS consecutiveCount,
MIN(cdate) AS startDate, MAX(cdate) AS endDate, min(close) as latestclose
FROM RunGroup
GROUP BY stock, groupingId
HAVING COUNT(*) >= 3
and MAX(cdate) = (select max(cdate) from sampletable)
ORDER BY CONSECUTIVECOUNT desc, stock, startDate
与股票类似，下面的“DDD”是图表的外观和最终数据：
2021 年 1 月 5 日，趋势发生了变化，我想根据以下公式添加新的“看跌”列：
C < O and C < C1 and O < C1 and O1 < C1 and C > O1 and O < C1
其中，
O1 = Previous day Open price
C1 = Previous day Close price
C = Today's Close price
O = Today's Open price
+-------+------------+--------+-------+-------+--------+--------+---------+
| Stock | Cdate | Open | High | Low | Close | Volume | Pattern |
+-------+------------+--------+-------+-------+--------+--------+---------+
| XYZ | 01-01-2021 | 40 | 40.5 | 38.5 | 38.8 | 83057 | |
| XYZ | 02-01-2021 | 39.2 | 39.2 | 37.2 | 37.8 | 181814 | |
| XYZ | 03-01-2021 | 38 | 38.5 | 36.5 | 37 | 117378 | |
| XYZ | 04-01-2021 | 36 | 36.1 | 35.6 | 35.7 | 93737 | |
| XYZ | 05-01-2021 | 35.35 | 36.8 | 35.1 | 36.6 | 169106 | Bullish |
| XYZ | 06-01-2021 | 36.5 | 38.5 | 36.5 | 38 | 123179 | |
| XYZ | 07-01-2021 | 37.5 | 39.5 | 37.3 | 39.4 | 282986 | |
| XYZ | 08-01-2021 | 39 | 40.5 | 38.5 | 40 | 117437 | |
| | | | | | | | |
| DDD | 01-01-2021 | 135.35 | 136.8 | 135.1 | 136.6 | 16454 | |
| DDD | 02-01-2021 | 136.5 | 138.5 | 136.5 | 138 | 281461 | |
| DDD | 03-01-2021 | 137.5 | 139.5 | 137.3 | 139.4 | 77334 | |
| DDD | 04-01-2021 | 139 | 140.5 | 138.5 | 140 | 321684 | |
| DDD | 05-01-2021 | 139.7 | 139.8 | 139.3 | 139.4 | 873009 | Bearish |
| DDD | 06-01-2021 | 139.2 | 139.2 | 137.2 | 137.8 | 62522 | |
| DDD | 07-01-2021 | 138 | 138.5 | 136.5 | 137 | 114826 | |
| DDD | 08-01-2021 | 136.6 | 136.8 | 135.1 | 135.35 | 27317 | |
+-------+------------+--------+-------+-------+--------+--------+---------+
感谢任何帮助。
更新：对不起，如果我要求太多。这就是我想要实现的目标。
简而言之，我想识别以下屏幕截图中以黄色突出显示的区域，仅当它位于 upmove/uptrend 或 downmove/downtrend.
中时
XYZ 股票，2021 年 5 月 1 日看涨
股票 DDD，2021 年 5 月 1 日看跌
谢谢，
里查
从 Oracle 12c 开始，您可以使用 MATCH_RECOGNIZE:
SELECT *
FROM table_name
MATCH_RECOGNIZE(
PARTITION BY stock
ORDER BY cdate
MEASURES
CLASSIFIER() AS pttrn
ALL ROWS PER MATCH
PATTERN (bullish|bearish|other)
DEFINE
bullish AS PREV(open) > PREV(close)
AND Close > Open
AND Close > PREV(High)
AND Open < PREV(Low),
bearish AS Close < Open
AND Close < PREV(Close)
AND Open < PREV(Close)
AND PREV(Open) < PREV(Close)
AND Close > PREV(Open)
AND Open < PREV(Close)
)
其中，对于示例数据：
CREATE TABLE table_name (Stock, Cdate, Open, High, Low, Close, Volume ) AS
SELECT 'XYZ', DATE '2021-01-01', 40.00, 40.50, 38.50, 38.80, 83057 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-02', 39.20, 39.20, 37.20, 37.80, 181814 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-03', 38.00, 38.50, 36.50, 37.00, 117378 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-04', 36.00, 36.10, 35.60, 35.70, 93737 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-05', 35.35, 36.80, 35.10, 36.60, 169106 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-06', 36.50, 38.50, 36.50, 38.00, 123179 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-07', 37.50, 39.50, 37.30, 39.40, 282986 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-08', 39.00, 40.50, 38.50, 40.00, 117437 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-01', 135.35, 136.80, 135.10, 136.60, 16454 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-02', 136.50, 138.50, 136.50, 138.00, 281461 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-03', 137.50, 139.50, 137.30, 139.40, 77334 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-04', 139.00, 140.50, 138.50, 140.00, 321684 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-05', 139.70, 139.80, 139.30, 139.40, 873009 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-06', 139.20, 139.20, 137.20, 137.80, 62522 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-07', 138.00, 138.50, 136.50, 137.00, 114826 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-08', 136.60, 136.80, 135.10, 135.35, 27317 FROM DUAL;
输出：
STOCK
CDATE
PTTRN
OPEN
HIGH
LOW
CLOSE
VOLUME
DDD
01-JAN-21
OTHER
135.35
136.8
135.1
136.6
16454
DDD
02-JAN-21
OTHER
136.5
138.5
136.5
138
281461
DDD
03-JAN-21
OTHER
137.5
139.5
137.3
139.4
77334
DDD
04-JAN-21
OTHER
139
140.5
138.5
140
321684
DDD
05-JAN-21
BEARISH
139.7
139.8
139.3
139.4
873009
DDD
06-JAN-21
OTHER
139.2
139.2
137.2
137.8
62522
DDD
07-JAN-21
OTHER
138
138.5
136.5
137
114826
DDD
08-JAN-21
OTHER
136.6
136.8
135.1
135.35
27317
XYZ
01-JAN-21
OTHER
40
40.5
38.5
38.8
83057
XYZ
02-JAN-21
OTHER
39.2
39.2
37.2
37.8
181814
XYZ
03-JAN-21
OTHER
38
38.5
36.5
37
117378
XYZ
04-JAN-21
OTHER
36
36.1
35.6
35.7
93737
XYZ
05-JAN-21
BULLISH
35.35
36.8
35.1
36.6
169106
XYZ
06-JAN-21
OTHER
36.5
38.5
36.5
38
123179
XYZ
07-JAN-21
OTHER
37.5
39.5
37.3
39.4
282986
XYZ
08-JAN-21
OTHER
39
40.5
38.5
40
117437
您还可以使用 LAG 分析函数（在 Oracle 12 之前可用）：
SELECT t.*,
CASE
WHEN LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
> LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > Open
AND Close > LAG(high) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(low) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BULLISH'
WHEN Close < Open
AND Close < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
< LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BEARISH'
ELSE 'OTHER'
END AS pttrn
FROM table_name t
（给出类似的输出。）
db<>fiddle here
更新：向上和向下跟踪：
同样，这就是 MATCH_RECOGNIZE 的用途：
SELECT *
FROM table_name
MATCH_RECOGNIZE(
PARTITION BY stock
ORDER BY cdate
MEASURES
CLASSIFIER() AS pttrn
ALL ROWS PER MATCH
PATTERN (^initial_value|bullish|bearish|up|down|other)
DEFINE
bullish AS PREV(open) > PREV(close)
AND Close > Open
AND Close > PREV(High)
AND Open < PREV(Low),
bearish AS Close < Open
AND Close < PREV(Close)
AND Open < PREV(Close)
AND PREV(Open) < PREV(Close)
AND Close > PREV(Open)
AND Open < PREV(Close),
up AS close > PREV(close)
AND open > PREV(open),
down AS close < PREV(close)
AND open < PREV(open)
)
但是你可以用 LAG 做同样的事情：
SELECT t.*,
CASE
WHEN ROW_NUMBER() OVER (PARTITION BY stock ORDER BY cdate) = 1
THEN 'INITIAL_VALUE'
WHEN LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
> LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > Open
AND Close > LAG(high) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(low) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BULLISH'
WHEN Close < Open
AND Close < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
< LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BEARISH'
WHEN Close > LAG(Close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open > LAG(Open) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'UP'
WHEN Close < LAG(Close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(Open) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'DOWN'
ELSE 'OTHER'
END AS pttrn
FROM table_name t
db<>fiddle here
我在 Python 技术上找到了很多与我的问题相关的解决方案，但在 Oracle SQL 或 PL/SQL 上找不到很多解决方案。所以在 Oracle SQL 上使用 Oracle Application Express 进行尝试。
我的数据库 table 具有以下 8 天的股票样本数据。每天收市后都会插入新记录。我有查询要查找价格连续 increase/decrease 的股票。现在我想再添加一列，我可以在其中看到一个基于当前日期和之前日期值的称为看涨或看跌的模式。
+-------+------------+--------+-------+-------+--------+--------+
| Stock | Cdate | Open | High | Low | Close | Volume |
+-------+------------+--------+-------+-------+--------+--------+
| XYZ | 01-01-2021 | 40 | 40.5 | 38.5 | 38.8 | 83057 |
| XYZ | 02-01-2021 | 39.2 | 39.2 | 37.2 | 37.8 | 181814 |
| XYZ | 03-01-2021 | 38 | 38.5 | 36.5 | 37 | 117378 |
| XYZ | 04-01-2021 | 36 | 36.1 | 35.6 | 35.7 | 93737 |
| XYZ | 05-01-2021 | 35.35 | 36.8 | 35.1 | 36.6 | 169106 |
| XYZ | 06-01-2021 | 36.5 | 38.5 | 36.5 | 38 | 123179 |
| XYZ | 07-01-2021 | 37.5 | 39.5 | 37.3 | 39.4 | 282986 |
| XYZ | 08-01-2021 | 39 | 40.5 | 38.5 | 40 | 117437 |
| | | | | | | |
| DDD | 01-01-2021 | 135.35 | 136.8 | 135.1 | 136.6 | 16454 |
| DDD | 02-01-2021 | 136.5 | 138.5 | 136.5 | 138 | 281461 |
| DDD | 03-01-2021 | 137.5 | 139.5 | 137.3 | 139.4 | 77334 |
| DDD | 04-01-2021 | 139 | 140.5 | 138.5 | 140 | 321684 |
| DDD | 05-01-2021 | 139.7 | 139.8 | 139.3 | 139.4 | 873009 |
| DDD | 06-01-2021 | 139.2 | 139.2 | 137.2 | 137.8 | 62522 |
| DDD | 07-01-2021 | 138 | 138.5 | 136.5 | 137 | 114826 |
| DDD | 08-01-2021 | 136.6 | 136.8 | 135.1 | 135.35 | 27317 |
+-------+------------+--------+-------+-------+--------+--------+
这是图表查找股票 XYZ 的方式：
2021 年 1 月 5 日，趋势发生了变化，我想根据以下公式添加新的“看涨”栏：
O1 > C1 and C > O and C > H1 and O < L1
其中，
O1 = Previous day Open price
C1 = Previous day Close price
C = Today's Close price
O = Today's Open price
H1 = Previous day High price
L1 = Previous day Low price
预期输出将是一个新列，在列模式下显示“看涨”：
+-------+------------+-------+------+------+-------+--------+---------+
| Stock | Cdate | Open | High | Low | Close | Volume | Pattern |
+-------+------------+-------+------+------+-------+--------+---------+
| XYZ | 01-01-2021 | 40 | 40.5 | 38.5 | 38.8 | 83057 | |
| XYZ | 02-01-2021 | 39.2 | 39.2 | 37.2 | 37.8 | 181814 | |
| XYZ | 03-01-2021 | 38 | 38.5 | 36.5 | 37 | 117378 | |
| XYZ | 04-01-2021 | 36 | 36.1 | 35.6 | 35.7 | 93737 | |
| XYZ | 05-01-2021 | 35.35 | 36.8 | 35.1 | 36.6 | 169106 | Bullish |
| XYZ | 06-01-2021 | 36.5 | 38.5 | 36.5 | 38 | 123179 | |
| XYZ | 07-01-2021 | 37.5 | 39.5 | 37.3 | 39.4 | 282986 | |
| XYZ | 08-01-2021 | 39 | 40.5 | 38.5 | 40 | 117437 | |
+-------+------------+-------+------+------+-------+--------+---------+
我在互联网上搜索了解决方案，找到的最接近的是 this。我稍微修改了查询，但无法添加公式或任何其他新列。下面是我试过的查询：
WITH StockRow AS (SELECT stock, close, cdate,
ROW_NUMBER() OVER(PARTITION BY stock
ORDER BY cdate) rn
FROM sampletable where volume > 200000),
RunGroup AS (SELECT Base.stock, Base.cdate, base.close,
MAX(Restart.rn) OVER(PARTITION BY Base.stock
ORDER BY Base.cdate) groupingId
FROM StockRow Base
LEFT JOIN StockRow Restart
ON Restart.stock = Base.stock
AND Restart.rn = Base.rn - 1
AND Restart.CLOSE < Base.CLOSE)
SELECT stock,
COUNT(*) AS consecutiveCount,
MIN(cdate) AS startDate, MAX(cdate) AS endDate, min(close) as latestclose
FROM RunGroup
GROUP BY stock, groupingId
HAVING COUNT(*) >= 3
and MAX(cdate) = (select max(cdate) from sampletable)
ORDER BY CONSECUTIVECOUNT desc, stock, startDate
与股票类似，下面的“DDD”是图表的外观和最终数据：
2021 年 1 月 5 日，趋势发生了变化，我想根据以下公式添加新的“看跌”列：
C < O and C < C1 and O < C1 and O1 < C1 and C > O1 and O < C1
其中，
O1 = Previous day Open price
C1 = Previous day Close price
C = Today's Close price
O = Today's Open price
+-------+------------+--------+-------+-------+--------+--------+---------+
| Stock | Cdate | Open | High | Low | Close | Volume | Pattern |
+-------+------------+--------+-------+-------+--------+--------+---------+
| XYZ | 01-01-2021 | 40 | 40.5 | 38.5 | 38.8 | 83057 | |
| XYZ | 02-01-2021 | 39.2 | 39.2 | 37.2 | 37.8 | 181814 | |
| XYZ | 03-01-2021 | 38 | 38.5 | 36.5 | 37 | 117378 | |
| XYZ | 04-01-2021 | 36 | 36.1 | 35.6 | 35.7 | 93737 | |
| XYZ | 05-01-2021 | 35.35 | 36.8 | 35.1 | 36.6 | 169106 | Bullish |
| XYZ | 06-01-2021 | 36.5 | 38.5 | 36.5 | 38 | 123179 | |
| XYZ | 07-01-2021 | 37.5 | 39.5 | 37.3 | 39.4 | 282986 | |
| XYZ | 08-01-2021 | 39 | 40.5 | 38.5 | 40 | 117437 | |
| | | | | | | | |
| DDD | 01-01-2021 | 135.35 | 136.8 | 135.1 | 136.6 | 16454 | |
| DDD | 02-01-2021 | 136.5 | 138.5 | 136.5 | 138 | 281461 | |
| DDD | 03-01-2021 | 137.5 | 139.5 | 137.3 | 139.4 | 77334 | |
| DDD | 04-01-2021 | 139 | 140.5 | 138.5 | 140 | 321684 | |
| DDD | 05-01-2021 | 139.7 | 139.8 | 139.3 | 139.4 | 873009 | Bearish |
| DDD | 06-01-2021 | 139.2 | 139.2 | 137.2 | 137.8 | 62522 | |
| DDD | 07-01-2021 | 138 | 138.5 | 136.5 | 137 | 114826 | |
| DDD | 08-01-2021 | 136.6 | 136.8 | 135.1 | 135.35 | 27317 | |
+-------+------------+--------+-------+-------+--------+--------+---------+
感谢任何帮助。
更新：对不起，如果我要求太多。这就是我想要实现的目标。 简而言之，我想识别以下屏幕截图中以黄色突出显示的区域，仅当它位于 upmove/uptrend 或 downmove/downtrend.
中时XYZ 股票，2021 年 5 月 1 日看涨
股票 DDD，2021 年 5 月 1 日看跌
谢谢，
里查
从 Oracle 12c 开始，您可以使用 MATCH_RECOGNIZE:
SELECT *
FROM table_name
MATCH_RECOGNIZE(
PARTITION BY stock
ORDER BY cdate
MEASURES
CLASSIFIER() AS pttrn
ALL ROWS PER MATCH
PATTERN (bullish|bearish|other)
DEFINE
bullish AS PREV(open) > PREV(close)
AND Close > Open
AND Close > PREV(High)
AND Open < PREV(Low),
bearish AS Close < Open
AND Close < PREV(Close)
AND Open < PREV(Close)
AND PREV(Open) < PREV(Close)
AND Close > PREV(Open)
AND Open < PREV(Close)
)
其中，对于示例数据：
CREATE TABLE table_name (Stock, Cdate, Open, High, Low, Close, Volume ) AS
SELECT 'XYZ', DATE '2021-01-01', 40.00, 40.50, 38.50, 38.80, 83057 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-02', 39.20, 39.20, 37.20, 37.80, 181814 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-03', 38.00, 38.50, 36.50, 37.00, 117378 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-04', 36.00, 36.10, 35.60, 35.70, 93737 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-05', 35.35, 36.80, 35.10, 36.60, 169106 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-06', 36.50, 38.50, 36.50, 38.00, 123179 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-07', 37.50, 39.50, 37.30, 39.40, 282986 FROM DUAL UNION ALL
SELECT 'XYZ', DATE '2021-01-08', 39.00, 40.50, 38.50, 40.00, 117437 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-01', 135.35, 136.80, 135.10, 136.60, 16454 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-02', 136.50, 138.50, 136.50, 138.00, 281461 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-03', 137.50, 139.50, 137.30, 139.40, 77334 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-04', 139.00, 140.50, 138.50, 140.00, 321684 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-05', 139.70, 139.80, 139.30, 139.40, 873009 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-06', 139.20, 139.20, 137.20, 137.80, 62522 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-07', 138.00, 138.50, 136.50, 137.00, 114826 FROM DUAL UNION ALL
SELECT 'DDD', DATE '2021-01-08', 136.60, 136.80, 135.10, 135.35, 27317 FROM DUAL;
输出：
STOCK CDATE PTTRN OPEN HIGH LOW CLOSE VOLUME DDD 01-JAN-21 OTHER 135.35 136.8 135.1 136.6 16454 DDD 02-JAN-21 OTHER 136.5 138.5 136.5 138 281461 DDD 03-JAN-21 OTHER 137.5 139.5 137.3 139.4 77334 DDD 04-JAN-21 OTHER 139 140.5 138.5 140 321684 DDD 05-JAN-21 BEARISH 139.7 139.8 139.3 139.4 873009 DDD 06-JAN-21 OTHER 139.2 139.2 137.2 137.8 62522 DDD 07-JAN-21 OTHER 138 138.5 136.5 137 114826 DDD 08-JAN-21 OTHER 136.6 136.8 135.1 135.35 27317 XYZ 01-JAN-21 OTHER 40 40.5 38.5 38.8 83057 XYZ 02-JAN-21 OTHER 39.2 39.2 37.2 37.8 181814 XYZ 03-JAN-21 OTHER 38 38.5 36.5 37 117378 XYZ 04-JAN-21 OTHER 36 36.1 35.6 35.7 93737 XYZ 05-JAN-21 BULLISH 35.35 36.8 35.1 36.6 169106 XYZ 06-JAN-21 OTHER 36.5 38.5 36.5 38 123179 XYZ 07-JAN-21 OTHER 37.5 39.5 37.3 39.4 282986 XYZ 08-JAN-21 OTHER 39 40.5 38.5 40 117437
您还可以使用 LAG 分析函数（在 Oracle 12 之前可用）：
SELECT t.*,
CASE
WHEN LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
> LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > Open
AND Close > LAG(high) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(low) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BULLISH'
WHEN Close < Open
AND Close < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
< LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BEARISH'
ELSE 'OTHER'
END AS pttrn
FROM table_name t
（给出类似的输出。）
db<>fiddle here
更新：向上和向下跟踪：
同样，这就是 MATCH_RECOGNIZE 的用途：
SELECT *
FROM table_name
MATCH_RECOGNIZE(
PARTITION BY stock
ORDER BY cdate
MEASURES
CLASSIFIER() AS pttrn
ALL ROWS PER MATCH
PATTERN (^initial_value|bullish|bearish|up|down|other)
DEFINE
bullish AS PREV(open) > PREV(close)
AND Close > Open
AND Close > PREV(High)
AND Open < PREV(Low),
bearish AS Close < Open
AND Close < PREV(Close)
AND Open < PREV(Close)
AND PREV(Open) < PREV(Close)
AND Close > PREV(Open)
AND Open < PREV(Close),
up AS close > PREV(close)
AND open > PREV(open),
down AS close < PREV(close)
AND open < PREV(open)
)
但是你可以用 LAG 做同样的事情：
SELECT t.*,
CASE
WHEN ROW_NUMBER() OVER (PARTITION BY stock ORDER BY cdate) = 1
THEN 'INITIAL_VALUE'
WHEN LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
> LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > Open
AND Close > LAG(high) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(low) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BULLISH'
WHEN Close < Open
AND Close < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
< LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
AND Close > LAG(open) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(close) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'BEARISH'
WHEN Close > LAG(Close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open > LAG(Open) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'UP'
WHEN Close < LAG(Close) OVER (PARTITION BY stock ORDER BY cdate)
AND Open < LAG(Open) OVER (PARTITION BY stock ORDER BY cdate)
THEN 'DOWN'
ELSE 'OTHER'
END AS pttrn
FROM table_name t
db<>fiddle here