比較oracle表中的行並更新匹配的行

Question

我有如下表格：

**ID      tDate        Product    Price    Quantity    BuySell    Status**
  1     10-May-17       pppp       $12        20         Buy       Null
  2     12-May-17       tttt       $10        20         Sell      Null
  3     12-May-17       tttt       $10        20         Buy       Null
  4     18-May-17       pppp       $14        20         Sell      Null
  5     18-May-17       pppp       $14        20         Buy       Null
  6     18-May-17       pppp       $14        20         Sell      Null

我需要更新名為STATUS的字段，並將其設置為“ Matched”，無論在哪里找到一對具有相等tDate，產品，價格和數量且不等於BuySell的貨幣。

以下是所需的結果：

**ID      tDate        Product    Price    Quantity    BuySell    Status**
  1     10-May-17       pppp       $12        20         Buy       Null
  2     12-May-17       tttt       $10        20         Sell      Matched
  3     12-May-17       tttt       $10        20         Buy       Matched
  4     18-May-17       pppp       $14        20         Sell      Matched
  5     18-May-17       pppp       $14        20         Buy       Matched
  6     18-May-17       pppp       $14        20         Sell      Null

注意＃6如何不匹配，因為它只能與另一個null匹配。

我希望我可以用一個SQL語句執行此操作。

我現在正在做的事情可能是最糟糕的方法：我在python中加載到pandas數據幀中，然后循環比較每一行。

s = "SELECT ID, Account, product, Price, tDate, BuySell, Qty" + \
    "FROM Table " + \
    "WHERE Status IS NULL " + \
    "ORDER BY Account, product, tDate, Price, Qty"

df = pd.read_sql(s, conn)

for i in range(len(df.index)-1):

    if df.iloc[i, 1] == df.iloc[i+1, 1]  \
        and df.iloc[i, 2] == df.iloc[i+1, 2] \
        and df.iloc[i, 3] == df.iloc[i+1, 3] \
        and df.iloc[i, 4] == df.iloc[i+1, 4] \
        and df.iloc[i, 5] != df.iloc[i+1, 5] \
        and df.iloc[i, 6] == df.iloc[i+1, 6]:

        s = "UPDATE Temp_Fees " + \
            "SET Strategy = 'UNALLOCATED \ CANCELLED' " + \
            "WHERE ID = " + str(df.iloc[i,0]) + \
            " OR ID = " + str(df.iloc[i + 1, 0])

        #custom function that will execute and commit statement
        bb.EXECUTE(s)

        #avoid reading a matched row 
        i = i + 1

謝謝

Answer 1

未經測試，但僅使用SQL的情況如下：

MERGE INTO your_table dst
USING (
  SELECT ROW_NUMBER() OVER (
             PARTITION BY tDate, Product, Price, Quantity, BuySell
             ORDER BY ID
           ) AS idx,
         COUNT( CASE BuySell WHEN 'Buy' THEN 1 END ) OVER (
             PARTITION BY tDate, Product, Price, Quantity
           ) AS num_buy,
         COUNT( CASE BuySell WHEN 'Sell' THEN 1 END ) OVER (
             PARTITION BY tDate, Product, Price, Quantity
           ) AS num_sell
  FROM   your_table
) src
ON ( src.ROWID = dst.ROWID AND src.idx <= LEAST( src.num_buy, src.num_sell ) )
WHEN MATCHED THEN
  UPDATE SET Status = 'Matched';

Answer 2

您可以獲取每個tdate的買賣對數並更新此類行。

MERGE INTO tablename dst
USING (select t.*,count(*) over(partition by tDate,Product,Price,Quantity,rn) as cnt 
       from (select t.*,row_number() over(partition by tDate,Product,Price,Quantity,buysell order by id) as rn
             from tablename t) t
       ) src
ON (src.id = dst.id AND src.cnt=2)
WHEN MATCHED THEN
UPDATE SET Status = 'Matched';

運行此查詢以查看行號如何分配給買賣。

select t.*,count(*) over(partition by tDate,Product,Price,Quantity,rn) as cnt 
from (select t.*,row_number() over(partition by tDate,Product,Price,Quantity,buysell order by id) as rn
      from tablename t) t

Answer 3

這是添加到其他視圖的另一種觀點。 這僅解決匹配部分，而不解決更新或合並部分。 最近，我遇到了類似的問題，我需要查找與交易日期和位置匹配的記錄，但它們來自兩個不同的來源。 在這種情況下，必須對記錄進行排序，以便將類似的記錄放在一起。 內部查詢將記錄與之前的記錄和之后的記錄進行比較，如果它們匹配，則將其抓取。 然后，外部查詢確定它們是否滿足“差異”條件。 希望這可以幫助。

select sbs.trnsid, sbs.amount, sbs.transaction_date, sbs.posted_date, sbs.srcid, 
        sbs.credited_flag, sbs.accid, sbs.compid, sbs.badgeid, sbs.locid, sbs.date_credited, 
        sbs.searchable, sbs.priortime, sbs.nexttime, sbs.priorsource, sbs.nextsource 
    from 
    (select trnsid, amount, transaction_date, posted_date, srcid, credited_flag,
      accid, compid, badgeid, locid, date_credited, transaction_date||locid as searchable,
      lag(transaction_date||locid, 1) over (order by accid) as priortime,
      lead(transaction_date||locid, 1) over (order by accid) as nexttime, 
    lag(srcid, 1) over (order by accid) as priorsource, 
    lead(srcid, 1) over (order by accid) as nextsource
    from transactions_table
    where accid = v_acct
      and transaction_date >= to_date('10/01/2016 00:00:00', 'mm/dd/yyyy hh24:mi:ss') 
      and transaction_date <= to_date('04/23/2017 23:59:59', 'mm/dd/yyyy hh24:mi:ss')
      and srcid in ('B', 'S') order by accid, transaction_date, locid) sbs
    where (sbs.searchable = sbs.nexttime and sbs.srcid = 'S' and sbs.nextsource = 'B')
   or (sbs.searchable = sbs.priortime and sbs.srcid = 'B' and sbs.priorsource = 'S');

Answer 4

merge into mytable t3
using (select t1.*, count(*) over (partition by tdate,product,price,quantity,field) as field2 from
(
select mytable.*, row_number() over (partition by mytable.tdate,mytable.product,mytable.price,mytable.quantity,mytable.buysell 
order by id) field from 
mytable) t1)  t2
on (t2.id=t3.id and t2.field2='2')
when matched then 
update set status='Matched';