Time display in a date item
This is driving me nuts.
I am trying to dynamically set the initial
value of a date item in a form.
I want it to be one hour prior to the current
system time rounded down to the hour.
i.e. if the current datetime is 07/26/2001 09:12, I want to see 07/26/2001 08:00 in the forms item.
The code I use is as follows;
DECLARE
-- get system datetime
v_date_time_char_format VARCHAR2(25) := :SYSTEM.CURRENT_DATETIME;
-- variable for hour
v_hour VARCHAR2(2);
BEGIN
IF :tbl_sf_site.test_date IS NULL THEN
-- go back one hour and delete blank caused by to_char
v_hour := SUBSTR(TO_CHAR(TO_NUMBER(SUBSTR(v_date_time_char_format,13,2)) - 1,'09'),2,2);
-- set time back one hour
v_date_time_char_format :=
SUBSTR(v_date_time_char_format,1,12)| |v_hour| |':00';
-- display the results of date manipulation
f_alert.ok('v_date_time_char_format is '| |v_date_time_char_format);
-- set value of form item
:tbl_sf_site.test_date :=
TO_DATE(v_date_time_char_format,'DD-MON-YYYY HH24:MI');
END IF;
END;
The f_alert.ok that displays is 26-JUL-2001 08:00, but the value in the item is 07/26/2001 00:00.
The forms item is a text item of date format with a mask of 'mm/dd/rrrr hh24:mi.
Change the data type of forms item into datetime then try.
null
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Message was edited by:
user552628Hi,
The special thing about it is that with a given key,
there can be a LOT of associated data, thousands to
tens of thousands. To illustrate, a btree with a 8192
byte page size has 3 levels, 0 overflow pages and
35208 duplicate pages!
In other words, my keys have a large "fan-out". Note
that I wrote "can", since some keys only have a few
dozen or so associated data items.
So I configure the b-tree for DB_DUPSORT. The default
lexical ordering with set_dup_compare is OK, so I
don't touch that. I'm getting the data items sorted
as a bonus, but I don't need that in my application.
However, I'm seeing very poor "put (DB_NODUPDATA)
performance", due to a lot of disk read operations.In general, the performance would slowly decreases when there are a lot of duplicates associated with a key. For the Btree access method lookups and inserts have a O(log n) complexity (which implies that the search time is dependent on the number of keys stored in the underlying db tree). When doing put's with DB_NODUPDATA leaf pages have to be searched in order to determine whether the data is not a duplicate. Thus, giving the fact that for each given key (in most of the cases) there is a large number of data items associated (up to thousands, tens of thousands) an impressive amount of pages have to be brought into the cache to check against the duplicate criteria.
Of course, the problem of sizing the cache and databases's pages arises here. Your size setting for these measures should tend to large values, this way the cache would be fit to accommodate large pages (in which hundreds of records should be hosted).
Setting the cache and the page size to their ideal values is a process of experimenting.
http://www.oracle.com/technology/documentation/berkeley-db/db/ref/am_conf/pagesize.html
http://www.oracle.com/technology/documentation/berkeley-db/db/ref/am_conf/cachesize.html
While there may be a lot of reasons for this anomaly,
I suspect BDB spends a lot of time tracking down
duplicate data items.
I wonder if in my case it would be more efficient to
have a b-tree with as key the combined (4 byte
integer, 8 byte integer) and a zero-length or
1-length dummy data (in case zero-length is not an
option). Indeed, these should be the best alternative, but testing must be done first. Try this approach and provide us with feedback.
You can have records with a zero-length data portion.
Also, you could provide more information on whether or not you're using an environment, if so, how did you configure it etc. Have you thought of using multiple threads to load the data ?
Another possibility would be to just add all the
data integers as a single big giant data blob item
associated with a single (unique) key. But maybe this
is just doing what BDB does... and would probably
exchange "duplicate pages" for "overflow pages"This is a terrible approach since bringing an overflow page into the cache is more time consuming than bringing a regular page, and thus performance penalty results. Also, processing the entire collection of keys and data implies more work from a programming point of view.
Or, the slowdown is a BTREE thing and I could use a
hash table instead. In fact, what I don't know is how
duplicate pages influence insertion speed. But the
BDB source code indicates that in contrast to BTREE
the duplicate search in a hash table is LINEAR (!!!)
which is a no-no (from hash_dup.c):The Hash access method has, as you observed, a linear search (and thus a search time and lookup time proportional to the number of items in the buckets, O(1)). Combined with the fact that you don't want duplicate data than hash using the hash access method may not improve performance.
This is a performance/tunning problem and it involves a lot of resources from our part to investigate. If you have a support contract with Oracle, then please don't hesitate to put up your issue on Metalink or indicate that you want this issue to be taken in private, and we will create an SR for you.
Regards,
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ULINE.
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