I have 2 tables, tableStock and tableParts:
tableStock
+----+----------+-------------+
| ID | Num_Part | Description |
+----+----------+-------------+
| 1 | sr37 | plate |
+----+----------+-------------+
| 2 | sr56 | punch |
+----+----------+-------------+
| 3 | sl30 | crimper |
+----+----------+-------------+
| 4 | mp11 | holder |
+----+----------+-------------+
tableParts
+----+----------+-------+
| ID | Location | Stock |
+----+----------+-------+
| 1 | A | 2 |
+----+----------+-------+
| 3 | B | 5 |
+----+----------+-------+
| 5 | C | 2 |
+----+----------+-------+
| 7 | A | 1 |
+----+----------+-------+
And I just want to do this:
+----+----------+-------------+----------+-------+
| ID | Num_Part | Description | Location | Stock |
+----+----------+-------------+----------+-------+
| 1 | sr37 | plate | A | 2 |
+----+----------+-------------+----------+-------+
| 2 | sr56 | punch | NULL | NULL |
+----+----------+-------------+----------+-------+
| 3 | sl30 | crimper | B | 5 |
+----+----------+-------------+----------+-------+
| 4 | mp11 | holder | NULL | NULL |
+----+----------+-------------+----------+-------+
List ALL the rows of the first table and if the second table has the info, in this case 'location' and 'stock', add to the column, if not, just null.
I have been using inner and left join but some rows of the first table disappear because the lack of data in the second one:
select tableStock.ID, tableStock.Num_Part, tableStock.Description, tableParts.Location, tableParts.Stock from tableStock inner join tableParts on tableStock.ID = tableParts.ID;
What can I do?
You can use left join. Here is the demo.
select
s.ID,
Num_Part,
Description,
Location,
Stock
from Stock s
left join Parts p
on s.ID = p.ID
order by
s.ID
output:
| id | num_part | description | location | stock |
| --- | -------- | ----------- | -------- | ----- |
| 1 | sr37 | plate | A | 2 |
| 2 | sr56 | punch | NULL | NULL |
| 3 | sl30 | crimper | B | 5 |
| 4 | mp11 | holder | NULL | NULL |
I have a data orders that looks like this:
| Order | Step | Step Complete Date |
|:-----:|:----:|:------------------:|
| A | 1 | 11/1/2019 |
| | 2 | 11/1/2019 |
| | 3 | 11/1/2019 |
| | 4 | 11/3/2019 |
| | 5 | 11/3/2019 |
| | 6 | 11/5/2019 |
| | 7 | 11/5/2019 |
| B | 1 | 12/1/2019 |
| | 2 | 12/2/2019 |
| | 3 | |
| C | 1 | 10/21/2019 |
| | 2 | 10/23/2019 |
| | 3 | 10/25/2019 |
| | 4 | 10/25/2019 |
| | 5 | 10/25/2019 |
| | 6 | |
| | 7 | 10/27/2019 |
| | 8 | 10/28/2019 |
| | 9 | 10/29/2019 |
| | 10 | 10/30/2019 |
| D | 1 | 10/30/2019 |
| | 2 | 11/1/2019 |
| | 3 | 11/1/2019 |
| | 4 | 11/2/2019 |
| | 5 | 11/2/2019 |
What I need to accomplish is the following:
For each order, assign the 'Order_Completion_Date' field as the most recent 'Step_Complete_Date'. If ANY 'Step_Complete_Date' is NULL, then the value for 'Order_Completion_Date' should be NULL.
I set up a SQL FIDDLE with this data and my attempt, below:
SELECT
OrderNum,
MAX(Step_Complete_Date)
FROM
OrderNums
WHERE
Step_Complete_Date IS NOT NULL
GROUP BY
OrderNum
This is yielding:
ORDERNUM MAX(STEP_COMPLETE_DATE)
D 11/2/2019
A 11/5/2019
B 12/2/2019
C 10/30/2019
How can I achieve:
| OrderNum | Order_Completed_Date |
|:--------:|:--------------------:|
| A | 11/5/2019 |
| B | NULL |
| C | NULL |
| D | 11/2/2019 |
Aggregate function with KEEP can handle this
select ordernum,
max(step_complete_date)
keep (DENSE_RANK FIRST ORDER BY step_complete_date desc nulls first) res
FROM
OrderNums
GROUP BY
OrderNum
You can use a CASE expression to first count if there are any NULL values and if not then find the maximum value:
Query 1:
SELECT OrderNum,
CASE
WHEN COUNT( CASE WHEN Step_Complete_Date IS NULL THEN 1 END ) > 0
THEN NULL
ELSE MAX(Step_Complete_Date)
END AS Order_Completion_Date
FROM OrderNums
GROUP BY OrderNum
Results:
| ORDERNUM | ORDER_COMPLETION_DATE |
|----------|-----------------------|
| D | 11/2/2019 |
| A | 11/5/2019 |
| B | (null) |
| C | (null) |
First, you are representing dates as varchars in mm/dd/yyyy format (at least in fiddle). With max function it can produce incorrect result, try for example order with dates '11/10/2019' and '11/2/2019'.
Second, the most simple solution is IMHO to use fallback date for nulls and get null back when fallback date wins:
SELECT
OrderNum,
NULLIF(MAX(NVL(Step_Complete_Date,'~')),'~')
FROM
OrderNums
GROUP BY
OrderNum
(Example is still for varchars since tilde is greater than any digit. For dates, you could use 9999-12-31, for instance.)
I am using following query to count how many Bill_date each BAN have
select replace(c.usertoken, '-', '') as BAN
, to_char(to_date(bi.name,'YYYY-MM-DD'),'dd-mm-yy') as Billdate_dmy
, (replace(c.usertoken, '-', '') ||':'|| to_char(to_date(bi.name,'YYYY-MM-DD'),'dd-mm-yy')) as BAN_Billdate_dmy
, count(c.usertoken) as Number_Of_Bills
from customer c
, service s
, document d
, bill bi
, batch ba
, billrun br
where c.ID = s.CUSTOMER_SERVICE_ID
and s.ID = d.SERVICE_DOCUMENT_ID
and bi.ID = d.BILL_DOCUMENT_ID
and d.BATCH = ba.ID
and ba.BILLRUN = br.ID
and br.STATUS = 'APPROVED'
and c.brand='rogers'
and d.VERSIONEDCONTENTFOLDER='cbu'
group by c.usertoken, bi.name
order by c.usertoken
Output of the above query
+-----------+----------+--------------------+--------------+--+-------+
| BAN | Bill_date | BAN_Billdate | Count |
+-----------+----------+--------------------+--------------+--+-------+
| 100001247 | 25-09-19 | 100001247:25-09-19 | 1 | | |
| 100001247 | 25-10-19 | 100001247:25-10-19 | 1 | | |
| 100002583 | 15-10-19 | 100002583:15-10-19 | 1 | | |
| 100004753 | 25-09-19 | 100004753:25-09-19 | 1 | | |
| 100004753 | 25-10-19 | 100004753:25-10-19 | 1 | | |
| 100005719 | 25-09-19 | 100005719:25-09-19 | 1 | | |
| 100005719 | 25-10-19 | 100005719:25-10-19 | 1 | | |
| 100006311 | 06-09-19 | 100006311:06-09-19 | 1 | | |
| 100009596 | 25-09-19 | 100009596:25-09-19 | 1 | | |
| 100009596 | 25-10-19 | 100009596:25-10-19 | 1 | | |
+-----------+----------+--------------------+--------------+--+-------+
However I was expecting the following output
+-----------+----------+--------------------+--------------+--+-------+
| BAN | Billdate | BAN_Billdate | | Count |
+-----------+----------+--------------------+--------------+--+-------+
| 100001247 | 25-09-19 | 100001247:25-09-19 | 2 | | |
| 100001247 | 25-10-19 | 100001247:25-10-19 | 2 | | |
| 100002583 | 15-10-19 | 100002583:15-10-19 | 3 | | |
| 100004753 | 25-09-19 | 100004753:25-09-19 | 3 | | |
| 100004753 | 25-10-19 | 100004753:25-10-19 | 3 | | |
| 100005719 | 25-09-19 | 100005719:25-09-19 | 2 | | |
| 100005719 | 25-10-19 | 100005719:25-10-19 | 2 | | |
| 100006311 | 06-09-19 | 100006311:06-09-19 | 1 | | |
| 100009596 | 25-09-19 | 100009596:25-09-19 | 2 | | |
| 100009596 | 25-10-19 | 100009596:25-10-19 | 2 | | |
+-----------+----------+--------------------+--------------+--+-------+
Please advise what changes should I do in the query to have the count column reflecting the expected values.
I don't want to touch your query and the archaic join syntax. Please learn proper SQL grammar with JOIN and ON clauses for joins.
That said, you seem to want a window function to sum the counts:
select sum(count(*)) over (partition by ban, to_date(bi.name, 'YYYY-MM-DD'))
I'm not sure that aggregation is really useful, if you are only getting one row per group. In that case, you might want to remove the group by and use:
select count(*) over (partition by ban, to_date(bi.name, 'YYYY-MM-DD'))
I have table for eg "employee" with just one column "id". Say you have records from 1 through 1000.
Employee
------------
ID
------------
1
2
3
..
..
999
1000
Now I would like to write a query which gives the following results i.e. sort by ascending order and concatenate first 5 to 1 record, second 5 to 2 second, and so on. Any ideas how I can do this?
Here is the output I am looking to have.
1,2,3,4,5
6,7,8,9,10
11,12,13,14,15
...........
...........
996,997,998,999,1000
Use row_number and listagg functions, in this way:
SELECT listagg( id, ',' ) within group( order by group_no, id )
FROM (
select id,
trunc((row_number() over( order by id ) -1) / 5) as group_no
from employee
)
GROUP BY group_no
Working demo: http://sqlfiddle.com/#!4/ef526/10
| LISTAGG(ID,',')WITHINGROUP(ORDERBYGROUP_NO,ID) |
|------------------------------------------------|
| 1,2,3,4,5 |
| 6,7,8,9,10 |
| 11,12,13,14,15 |
| 16,17,18,19,20 |
| 21,22,23,24,25 |
| 26,27,28,29,30 |
| 31,32,33,34,35 |
| 36,37,38,39,40 |
| 41,42,43,44,45 |
| 46,47,48,49,50 |
| 51,52,53,54,55 |
| 56,57,58,59,60 |
| 61,62,63,64,65 |
| 66,67,68,69,70 |
| 71,72,73,74,75 |
| 76,77,78,79,80 |
| 81,82,83,84,85 |
| 86,87,88,89,90 |
| 91,92,93,94,95 |
| 96,97,98,99,100 |
| 101,102,103,104,105 |
| 106,107,108,109,110 |
| 111,112,113,114,115 |
| 116,117,118,119,120 |
| 121,122,123,124,125 |
| 126,127,128,129,130 |
| 131,132,133,134,135 |
| 136,137,138,139,140 |
| 141,142,143,144,145 |
| 146,147,148,149,150 |
| 151,152,153,154,155 |
| 156,157,158,159,160 |
| 161,162,163,164,165 |
| 166,167,168,169,170 |
| 171,172,173,174,175 |
| 176,177,178,179,180 |
| 181,182,183,184,185 |
| 186,187,188,189,190 |
| 191,192,193,194,195 |
| 196,197,198,199,200 |
I have a base table where I need to calculate the difference between two dates based on the type of the entry.
tblA
+----------+------------+---------------+--------------+
| TypeCode | Log_Date | Complete_Date | Pending_Date |
+----------+------------+---------------+--------------+
| 1 | 18/04/2016 | 19/04/2016 | |
| 2 | 10/04/2016 | 18/04/2016 | 15/04/2016 |
| 3 | 12/04/2016 | 19/04/2016 | |
| 4 | 15/04/2016 | 17/04/2016 | 16/04/2016 |
| 5 | 16/04/2016 | 21/04/2016 | |
| 1 | 19/04/2016 | 20/04/2016 | |
| 2 | 20/03/2016 | 31/03/2015 | |
| 3 | 25/03/2016 | 28/03/2016 | |
| 4 | 26/03/2016 | 27/03/2016 | |
| 5 | 27/03/2016 | 30/03/2016 | |
+----------+------------+---------------+--------------+
I have another look up table which has the column names to be considered based on the TypeCode.
tblB
+----------+----------+---------------+
| TypeCode | DateCol1 | DateCol2 |
+----------+----------+---------------+
| 1 | Log_Date | Complete_Date |
| 2 | Log_Date | Pending_Date |
| 3 | Log_Date | Complete_Date |
| 4 | Log_Date | Pending_Date |
| 5 | Log_Date | Complete_Date |
+----------+----------+---------------+
I am doing a simple DATEDIFF between two dates for my calculation. However I want to lookup which columns to consider for this calculation from tblB and apply it on tblA based on the TypeCode.
Resulting table:
For example: When the TypeCode is 2 or 4 then the calculation should be DATEDIFF(d, Log_Date, Pending_Date), otherwise DATEDIFF(d, Log_Date, Complete_Date)
+----------+------------+---------------+--------------+----------+
| TypeCode | Log_Date | Complete_Date | Pending_Date | Cal_Days |
+----------+------------+---------------+--------------+----------+
| 1 | 18/04/2016 | 19/04/2016 | | 1 |
| 2 | 10/04/2016 | 18/04/2016 | 15/04/2016 | 5 |
| 3 | 12/04/2016 | 19/04/2016 | | 7 |
| 4 | 15/04/2016 | 17/04/2016 | 16/04/2016 | 1 |
| 5 | 16/04/2016 | 21/04/2016 | | 5 |
| 1 | 19/04/2016 | 20/04/2016 | | 1 |
| 2 | 20/03/2016 | 31/03/2015 | | |
| 3 | 25/03/2016 | 28/03/2016 | | 3 |
| 4 | 26/03/2016 | 27/03/2016 | | |
| 5 | 27/03/2016 | 30/03/2016 | | 3 |
+----------+------------+---------------+--------------+----------+
Any help would be appreciated. Thanks.
Use JOIN with CASE expression:
SELECT
a.*,
Cal_Days =
DATEDIFF(
DAY,
CASE
WHEN b.DateCol1 = 'Log_Date' THEN a.Log_Date
WHEN b.DateCol1 = 'Complete_Date' THEN a.Complete_Date
ELSE a.Pending_Date
END,
CASE
WHEN b.DateCol2 = 'Log_Date' THEN a.Log_Date
WHEN b.DateCol2 = 'Complete_Date' THEN a.Complete_Date
ELSE a.Pending_Date
END
)
FROM TblA a
INNER JOIN TblB b
ON b.TypeCode = a.TypeCode