Using analytical function - value with highest count

Hi
i have this table below
CREATE TABLE table1
( cust_name VARCHAR2 (10)
, txn_id NUMBER
, txn_date DATE
, country VARCHAR2 (10)
, flag number
, CONSTRAINT key1 UNIQUE (cust_name, txn_id)
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9870,TO_DATE ('15-Jan-2011', 'DD-Mon-YYYY'), 'Iran', 1);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9871,TO_DATE ('16-Jan-2011', 'DD-Mon-YYYY'), 'China', 1);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9872,TO_DATE ('17-Jan-2011', 'DD-Mon-YYYY'), 'China', 1);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9873,TO_DATE ('18-Jan-2011', 'DD-Mon-YYYY'), 'Japan', 1);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9874,TO_DATE ('19-Jan-2011', 'DD-Mon-YYYY'), 'Japan', 1);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9875,TO_DATE ('20-Jan-2011', 'DD-Mon-YYYY'), 'Russia', 1);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9877,TO_DATE ('22-Jan-2011', 'DD-Mon-YYYY'), 'China', 0);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9878,TO_DATE ('26-Jan-2011', 'DD-Mon-YYYY'), 'Korea', 0);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9811,TO_DATE ('17-Jan-2011', 'DD-Mon-YYYY'), 'China', 0);
INSERT INTO table1 (cust_name, txn_id, txn_date,country,flag) VALUES ('Peter', 9854,TO_DATE ('13-Jan-2011', 'DD-Mon-YYYY'), 'Taiwan', 0);
The requirement is to create an additional column in the resultset with country name where the customer has done the maximum number of transactions
(with transaction flag 1). In case we have two or more countries tied with the same count, then we need to select the country (among the tied ones)
where the customer has done the last transaction (with transaction flag 1)
e.g. The count is 2 for both 'China' and 'Japan' for transaction flag 1 ,and the latest transaction is for 'Japan'. So the new column should contain 'Japan'
CUST_NAME TXN_ID TXN_DATE COUNTRY FLAG country_1
Peter 9811 17-JAN-11 China 0 Japan
Peter 9854 13-JAN-11 Taiwan 0 Japan
Peter 9870 15-JAN-11 Iran 1 Japan
Peter 9871 16-JAN-11 China 1 Japan
Peter 9872 17-JAN-11 China 1 Japan
Peter 9873 18-JAN-11 Japan 1 Japan
Peter 9874 19-JAN-11 Japan 1 Japan
Peter 9875 20-JAN-11 Russia 1 Japan
Peter 9877 22-JAN-11 China 0 Japan
Peter 9878 26-JAN-11 Korea 0 Japan
Please let me know how to accomplish this using analytical functions
Thanks
-Learnsequel

Does this work (not spent much time checking it)?
WITH ana AS (
SELECT cust_name, txn_id, txn_date, country, flag,
        Sum (flag)
            OVER (PARTITION BY cust_name, country)      n_trx,
        Max (CASE WHEN flag = 1 THEN txn_date END)
            OVER (PARTITION BY cust_name, country)      l_trx
  FROM cnt_trx
SELECT cust_name, txn_id, txn_date, country, flag,
        First_Value (country) OVER (PARTITION BY cust_name ORDER BY n_trx DESC, l_trx DESC) top_cnt
  FROM ana
CUST_NAME      TXN_ID TXN_DATE  COUNTRY          FLAG TOP_CNT
Fred             9875 20-JAN-11 Russia              1 Russia
Fred             9874 19-JAN-11 Japan               1 Russia
Peter            9873 18-JAN-11 Japan               1 Japan
Peter            9874 19-JAN-11 Japan               1 Japan
Peter            9872 17-JAN-11 China               1 Japan
Peter            9871 16-JAN-11 China               1 Japan
Peter            9811 17-JAN-11 China               0 Japan
Peter            9877 22-JAN-11 China               0 Japan
Peter            9875 20-JAN-11 Russia              1 Japan
Peter            9870 15-JAN-11 Iran                1 Japan
Peter            9878 26-JAN-11 Korea               0 Japan
Peter            9854 13-JAN-11 Taiwan              0 Japan
12 rows selected.

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       14877740       12140 SCREENING            19000101
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       14877940       12140 SCREENING            19000101
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       14878140       12140 SCREENING            19000101
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       14878440       12140 SCREENING            19000101
       14878540       12140 SCREENING            19000101
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       14877740       12140 SCREENING            19000101
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      5                                         count(*) over (partition by rci.visit_id, rci.dci_date order by rci.visit_id) rn
      6                                    from rci) r1
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       14876540       12140 SCREENING            20091015
       14876540       12140 SCREENING            19000101
       14876640       12140 SCREENING            19000101
       14876740       12140 SCREENING            19000101
       14876840       12140 SCREENING            19000101
       14876940       12140 SCREENING            19000101
       14877040       12140 SCREENING            19000101
       14877140       12140 SCREENING            19000101
       14877240       12140 SCREENING            19000101
       14877240       12140 SCREENING            19000101
       14877640       12140 SCREENING            19000101
       14877640       12140 SCREENING            19000101
       14877740       12140 SCREENING            19000101
       14877740       12140 SCREENING            19000101
       14877840       12140 SCREENING            19000101
       14877940       12140 SCREENING            19000101
       14878040       12140 SCREENING            19000101
       14878140       12140 SCREENING            19000101
       14878240       12140 SCREENING            19000101
       14878240       12140 SCREENING            20000101
       14878340       12140 SCREENING            19000101
       14878340       12140 SCREENING            19000101
       14878440       12140 SCREENING            19000101
       14878540       12140 SCREENING            19000101
       14878540       12140 SCREENING            19000101
       17418240       12140 SCREENING            20000101
       17418340       12140 SCREENING            20000101
       17418440       12140 SCREENING            20000101
       18790240       12140 SCREENING            19000101
       21724540       12140 SCREENING            19000101
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    SQL> just as what frank have said it will be helpful if you post a sample output based on the original posting, that is in the first posting you have.

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    insert into temp_one values (4, 'Mexico', to_date('03/14/2011', 'MM/DD/YYYY'), 'Gerry', 3);
    insert into temp_one values (5, 'Mexico', to_date('03/15/2011', 'MM/DD/YYYY'), 'Zick', 9);
    insert into temp_one values (6, 'London', to_date('03/16/2011', 'MM/DD/YYYY'), 'Mike', 8);this is output I desire
    placeid       issueperiod                               failures
    NY              02/28/2011 - 03/06/2011          10
    Mexico       02/28/2011 - 03/06/2011           3
    Mexico        03/14/2011 - 03/20/2011          12
    London        03/14/2011 - 03/20/2011          8All help is appreciated. I will post my query as soon as I am able to think of a good logic for this...

    hI,
    user13328581 wrote:
    ... Kindly note, I am still learning how to use analytic functions.That doesn't matter; analytic functions won't help in this problem. The aggregate SUM function is all you need.
    But what do you need to GROUP BY? What is each row of the result set going to represent? A placeid? Yes, each row will represent only one placedid, but it's going to be divided further. You want a separate row of output for every placeid and week, so you'll want to GROUP BY placeid and week. You don't want to GROUP BY the raw issuedate; that would put March 3 and March 4 into separate groups. And you don't want to GROUP BY failures; that would mean a row with 3 failures could never be in the same group as a row with 9 failures.
    This gets the output you posted from the sample data you posted:
    SELECT       placeid
    ,             TO_CHAR ( TRUNC (issuedate, 'IW')
                  , 'MM/DD/YYYY'
                ) || ' - '|| TO_CHAR ( TRUNC (issuedate, 'IW') + 6
                                             , 'MM/DD/YYY'
                               )     AS issueperiod
    ,       SUM (failures)                  AS sumfailures
    FROM        temp_one
    GROUP BY  placeid
    ,            TRUNC (issuedate, 'IW')
    ;You could use a sub-query to compute TRUNC (issuedate, 'IW') once. The code would be about as complicated, efficiency probably won't improve noticeably, and the the results would be the same.

  • Using Analytic Functions

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  • [b]Using Analytic functions...[/b]

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    bal_points number(3)
    insert into cust_points values ('ABC',01-MAY-2004',5, 15)
    insert into cust_points values ('ABC',05-MAY-2004',3, 12)
    insert into cust_points values ('ABC',09-MAY-2004',3, 9)
    insert into cust_points values ('XYZ',02-MAY-2004',8, 4)
    insert into cust_points values ('XYZ',03-MAY-2004',5, 1)
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    try this...
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         nvl(SUM(b.col2),0) col2,
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    WHERE a.pkcol = b.plcol(+)
    AND a.pkcol = c.pkcol
    GROUP BY a.pkcol;
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    DEPTNO COL1 COL2
    10 12786 0
    20 13237 738
    30 11217 2415
    40 0 0
    99 0 0
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    30 11217 2415
    20 13237 738
    10 12786 0
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    10 12786 0
    20 13237 738
    30 11217 2415
    40 0 0
    99 0 0
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  • Query for using "analytical functions" in DWH...

    Dear team,
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    Select 12345,         'W3',       0,         100,      50,        0 From dual Union All
    Select 12345,         'W4',       0,         100,      50,        0 From dual
    PRODUCT     WEEK     SOH     DEMAND     SUPPLY     EOH
    12345     W1     10,000     0     0     10000
    12345     W2     0     100     50     0
    12345     W3     0     100     50     0
    12345     W4     0     100     50     0
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    12345     W1     10,000               10000
    12345     W2     10,000     100     50     9950
    12345     W3     9,950     100     50     9900
    12345     W4     9,000     100     50     8950
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    Nicloei W wrote:
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    12345 W1      10000          0          0          0            10000
    12345 W2      10000      100         50          0             9950
    12345 W3      9950       100         50          0             *9900*
    12345 W4      *9000*       100         50          0             9850
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      3  As
      4  (
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      6  Select 12345,         'W2',       0,         100,      50,        0 From dal Union All
      7  Select 12345,         'W3',       0,         100,      50,        0 From dal Union All
      8  Select 12345,         'W4',       0,         100,      50,        0 From dual
      9  )
    10  Select Product
    11  ,Week
    12  , Sum(Soh) Over(Partition By Product Order By Week)- Sum(Supply) Over(Parttion By Product Order By Week)+Supply Soh
    13  ,Demand
    14  ,Supply
    15  , Sum(Soh) Over(Partition By Product Order By Week)- Sum(Supply) Over(Partition By Product Order By Week) eoh
    16  from  data;
       PRODUCT WE        SOH     DEMAND     SUPPLY        EOH
         12345 W1      10000          0          0      10000
         12345 W2      10000        100         50       9950
         12345 W3       9950        100         50       9900
         12345 W4       9900        100         50       9850 Vivek L

  • Restrict Query Resultset  which uses Analytic Function

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    C1 P1 19994 300.00
    C1 P2 19991 100.00
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    C1 P2 19993 175.00
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  • Using analytic function in a view

    Hello to all
    Sorry If I use this thread
    sql not merge using analytic functions
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    I think what you'll discover is that if you apply the function over the result set, the initial SQL might be quicker,
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          ,tp.Partition_Name
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                where   dtp.Partition_Name  like 'Y____\_Q_\_M__\_D__' escape '\'
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                and     dtp.Table_name      not like '%$%'
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          and     dtp.Table_name      not like '%$%'
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    Edited by: bluefrog on Jun 10, 2010 12:48 PM

  • Is it possible using Analytical functions?

    Hi,
       I have the following data
        Column1      Column2
        2005            500
        2006            500
        2007            500
        2008            500
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        2008               500
        2007               300
        2006                  0
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    Thanks,
    Sundar
    P.S: It doesnt have to be using analytical, if it can be achieved in a SQL, it's good.
    Message was edited by:
    Sundar M

    Hi, a sample using analytical function SUM:
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               ( Year NUMBER
               , Value NUMBER
    BEGIN
       DELETE FROM Source_Data;
       FOR v_Cycle IN 1 .. 6
       LOOP
          INSERT
            INTO Source_Data
                 Year
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          VALUES
                 2000 + v_Cycle
               , 100 * v_Cycle
       END LOOP;
       COMMIT;
    END;
    VARIABLE v_Amount NUMBER
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         , :v_Amount Original_Amount
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         , DECODE(
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                   , 1, Value              -- Positive number, more value can be subtract
                   , GREATEST(Value - (SUM(Value) OVER (ORDER BY Year DESC RANGE UNBOUNDED PRECEDING) - :v_Amount), 0)
                 )         Year_Quota
      FROM Source_Data s
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    /will give
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         2006        600            1200            600        600
         2005        500            1200           1100        500
         2004        400            1200           1500        100
         2003        300            1200           1800          0
         2002        200            1200           2000          0
         2001        100            1200           2100          0You can add different conditions (PARTITION BY ..)
    Hope this helps
    Max

  • SQL using analytical function

    Hi all,
    I want an help in creating my SQL query to extract the data described below:
    I have one table example test containing data like below:
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    2     T2          ACTIVE
    3     T3          SUCCESS
    4     T4          DEACTIVE
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    regards,
    Raluce

    Hi, Raluce,
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                                     ,             hiredate  DESC
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            20 SCOTT      ANALYST   19-APR-87
            20 FORD       ANALYST   03-DEC-81
            30 JAMES      CLERK     03-DEC-81
    This query finds all ANALYSTs in each department, regardless of how many there are.  (Deptno 20 happens to have 2 ANALYSTs.)  If there is no ANALYST in a department, then the most recently hired CLERK is included.  (Deptnos 10 and 30 don't have any ANALYSTs.)
    This "partitions", or sub-divides, the table into separate units, one for each department.  In the problem you posted, it looks like you want to operate in the entire table, without sub-dividing it in any way.  To do that, just omit the PARTITION BY clause in the analytic ROW_NUMBER function, like this:
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        SELECT  deptno, ename, job, hiredate
        ,       ROW_NUMBER () OVER ( --  PARTITION BY  deptno
                                     ORDER BY      job
                                     ,             hiredate  DESC
                                   )  AS r_num
        FROM    scott.emp
        WHERE   job  IN ('ANALYST', 'CLERK')
    SELECT     deptno, ename, job, hiredate
    FROM       got_r_num
    WHERE      job     = 'ANALYST'
    OR         r_num   = 1
    ORDER BY   deptno

  • How to use Analytic functions in Forms10g

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    Can we use Analytic function in forms10g like Lead & Lag.
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  • Build interface using analytic functions twice

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