I have a poster sent to me created in illustrator and I have photoshop cs2. I used the same dimensions from the original to create the poster in cs2. After creating the poster in cs2 using images and texts from the original poster, I printed it off and
So there is a lot of white space at the top and bottom of the page when I print off poster. When I see the poster on the canvas on cs2 it looks how I want it to! I am confused! Help pls. Also I am new to photoshop.
When I sent the finished poster to the person I needed to send it to, it wasn't printing out how we wanted on A4.
What system? What printer? What print settings? Most of that has nothing to do with teh Adobe apps, but your printer's capabilities and nobody can advise without that info.
Mylenium
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Why is the Star Transformation using two indexes for the same dimension?
Hi,
Recently, I have made an investigation about the Star Transformation feature. I have found a strange test case, which plays an important role in my strategy for our overall DWH architecture. Here it is:
The Strategy:
I would like to have the classical Star Transformation approach (single column Bitmap Indexes for each dimension foreign key column in the fact table), together with additional Bitmap Join Indexes for some of the dimension attributes, which would benefit from the materialization of the join (bitmap merge operation will be skipped/optimized).
The query:
select dp.brand, ds. region_name, dc.region_name
, count(*), sum(f.extended_price)
from fact_line_item f
, dim_part dp
, dim_supplier ds
, dim_customer dc
where dp.mfgr = 10 -- dimension selectivity = 1/10 --> acttual/fact selectivity = 6/10
and f.part_dk = dp.dk
and ds.region_name = 'REGION #1' -- dimension selectivity = 1/9
and f.supplier_dk = ds.dk
and dc.region_name = 'REGION #1' -- dimension selectivity = 1/11
and f.customer_dk = dc.dk
group by dp.brand, ds. region_name, dc.region_name
The actual plan:
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers | Reads |
| 0 | SELECT STATEMENT | | 1 | | 3247 (100)| 1 |00:01:42.05 | 264K| 220K|
| 1 | HASH GROUP BY | | 1 | 2 | 3247 (1)| 1 |00:01:42.05 | 264K| 220K|
|* 2 | HASH JOIN | | 1 | 33242 | 3037 (1)| 217K|00:01:29.67 | 264K| 220K|
|* 3 | TABLE ACCESS FULL | DIM_SUPPLIER | 1 | 1112 | 102 (0)| 1112 |00:00:00.01 | 316 | 4 |
|* 4 | HASH JOIN | | 1 | 33245 | 2934 (1)| 217K|00:01:29.10 | 264K| 220K|
|* 5 | TABLE ACCESS FULL | DIM_CUSTOMER | 1 | 910 | 102 (0)| 910 |00:00:00.08 | 316 | 8 |
|* 6 | HASH JOIN | | 1 | 33248 | 2831 (1)| 217K|00:01:28.57 | 264K| 220K|
|* 7 | TABLE ACCESS FULL | DIM_PART | 1 | 10 | 3 (0)| 10 |00:00:00.01 | 6 | 0 |
| 8 | PARTITION RANGE ALL | | 1 | 36211 | 2827 (1)| 217K|00:01:28.01 | 264K| 220K|
| 9 | TABLE ACCESS BY LOCAL INDEX ROWID| FACT_LINE_ITEM | 6 | 36211 | 2827 (1)| 217K|00:01:33.85 | 264K| 220K|
| 10 | BITMAP CONVERSION TO ROWIDS | | 6 | | | 217K|00:00:07.09 | 46980 | 3292 |
| 11 | BITMAP AND | | 6 | | | 69 |00:00:08.33 | 46980 | 3292 |
| 12 | BITMAP MERGE | | 6 | | | 193 |00:00:02.09 | 2408 | 1795 |
| 13 | BITMAP KEY ITERATION | | 6 | | | 4330 |00:00:04.66 | 2408 | 1795 |
| 14 | BUFFER SORT | | 6 | | | 60 |00:00:00.01 | 6 | 0 |
|* 15 | TABLE ACCESS FULL | DIM_PART | 1 | 10 | 3 (0)| 10 |00:00:00.01 | 6 | 0 |
|* 16 | BITMAP INDEX RANGE SCAN | FACT_LI__P_PART_DIM_KEY_BIX | 60 | | | 4330 |00:00:02.11 | 2402 | 1795 |
|* 17 | BITMAP INDEX SINGLE VALUE | FACT_LI__P_PART_MFGR_BJX | 6 | | | 1747 |00:00:06.65 | 890 | 888 |
| 18 | BITMAP MERGE | | 6 | | | 169 |00:00:02.78 | 16695 | 237 |
| 19 | BITMAP KEY ITERATION | | 6 | | | 5460 |00:00:01.56 | 16695 | 237 |
| 20 | BUFFER SORT | | 6 | | | 5460 |00:00:00.02 | 316 | 0 |
|* 21 | TABLE ACCESS FULL | DIM_CUSTOMER | 1 | 910 | 102 (0)| 910 |00:00:00.01 | 316 | 0 |
|* 22 | BITMAP INDEX RANGE SCAN | FACT_LI__P_CUST_DIM_KEY_BIX | 5460 | | | 5460 |00:00:02.07 | 16379 | 237 |
| 23 | BITMAP MERGE | | 6 | | | 170 |00:00:03.65 | 26987 | 372 |
| 24 | BITMAP KEY ITERATION | | 6 | | | 6672 |00:00:02.23 | 26987 | 372 |
| 25 | BUFFER SORT | | 6 | | | 6672 |00:00:00.01 | 316 | 0 |
|* 26 | TABLE ACCESS FULL | DIM_SUPPLIER | 1 | 1112 | 102 (0)| 1112 |00:00:00.01 | 316 | 0 |
|* 27 | BITMAP INDEX RANGE SCAN | FACT_LI__S_SUPP_DIM_KEY_BIX | 6672 | | | 6672 |00:00:02.74 | 26671 | 372 |
The Question:
Why is the Star Transformation using both indexes FACT_LI__P_PART_DIM_KEY_BIX and FACT_LI__P_PART_MFGR_BJX for the same dimension criteria (dp.mfgr = 10)?? The introduction of the additional Bitmap Join Index actually make Oracle to do the work twice !!!
Anybody, any idea ?!?Dom, here it is the plan with the predicates:
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers | Reads |
| 0 | SELECT STATEMENT | | 1 | | 3638 (100)| 1 |00:06:41.17 | 445K| 236K|
| 1 | HASH GROUP BY | | 1 | 2 | 3638 (1)| 1 |00:06:41.17 | 445K| 236K|
|* 2 | HASH JOIN | | 1 | 33242 | 3429 (1)| 217K|00:08:18.02 | 445K| 236K|
|* 3 | TABLE ACCESS FULL | DIM_SUPPLIER | 1 | 1112 | 102 (0)| 1112 |00:00:00.03 | 319 | 313 |
|* 4 | HASH JOIN | | 1 | 33245 | 3326 (1)| 217K|00:08:17.47 | 445K| 236K|
|* 5 | TABLE ACCESS FULL | DIM_CUSTOMER | 1 | 910 | 102 (0)| 910 |00:00:00.01 | 319 | 313 |
|* 6 | HASH JOIN | | 1 | 33248 | 3223 (1)| 217K|00:08:16.63 | 445K| 236K|
|* 7 | TABLE ACCESS FULL | DIM_PART | 1 | 10 | 3 (0)| 10 |00:00:00.01 | 6 | 0 |
| 8 | PARTITION RANGE ALL | | 1 | 36211 | 3219 (1)| 217K|00:08:16.30 | 445K| 236K|
| 9 | TABLE ACCESS BY LOCAL INDEX ROWID| FACT_LINE_ITEM | 6 | 36211 | 3219 (1)| 217K|00:08:40.89 | 445K| 236K|
| 10 | BITMAP CONVERSION TO ROWIDS | | 6 | | | 217K|00:00:32.00 | 46919 | 19331 |
| 11 | BITMAP AND | | 6 | | | 69 |00:00:34.50 | 46919 | 19331 |
| 12 | BITMAP MERGE | | 6 | | | 193 |00:00:00.58 | 2353 | 1 |
| 13 | BITMAP KEY ITERATION | | 6 | | | 4330 |00:00:00.10 | 2353 | 1 |
| 14 | BUFFER SORT | | 6 | | | 60 |00:00:00.01 | 6 | 0 |
|* 15 | TABLE ACCESS FULL | DIM_PART | 1 | 10 | 3 (0)| 10 |00:00:00.01 | 6 | 0 |
|* 16 | BITMAP INDEX RANGE SCAN | FACT_LI__P_PART_DIM_KEY_BIX | 60 | | | 4330 |00:00:00.07 | 2347 | 1 |
|* 17 | BITMAP INDEX SINGLE VALUE | FACT_LI__P_PART_MFGR_BJX | 6 | | | 1747 |00:01:23.64 | 882 | 565 |
| 18 | BITMAP MERGE | | 6 | | | 169 |00:00:09.14 | 16697 | 7628 |
| 19 | BITMAP KEY ITERATION | | 6 | | | 5460 |00:00:02.19 | 16697 | 7628 |
| 20 | BUFFER SORT | | 6 | | | 5460 |00:00:00.01 | 316 | 0 |
|* 21 | TABLE ACCESS FULL | DIM_CUSTOMER | 1 | 910 | 102 (0)| 910 |00:00:00.01 | 316 | 0 |
|* 22 | BITMAP INDEX RANGE SCAN | FACT_LI__P_CUST_DIM_KEY_BIX | 5460 | | | 5460 |00:00:08.78 | 16381 | 7628 |
| 23 | BITMAP MERGE | | 6 | | | 170 |00:00:21.46 | 26987 | 11137 |
| 24 | BITMAP KEY ITERATION | | 6 | | | 6672 |00:00:10.29 | 26987 | 11137 |
| 25 | BUFFER SORT | | 6 | | | 6672 |00:00:00.01 | 316 | 0 |
|* 26 | TABLE ACCESS FULL | DIM_SUPPLIER | 1 | 1112 | 102 (0)| 1112 |00:00:00.01 | 316 | 0 |
|* 27 | BITMAP INDEX RANGE SCAN | FACT_LI__S_SUPP_DIM_KEY_BIX | 6672 | | | 6672 |00:00:20.94 | 26671 | 11137 |
Predicate Information (identified by operation id):
2 - access("F"."SUPPLIER_DK"="DS"."DK")
3 - filter("DS"."REGION_NAME"='REGION #1')
4 - access("F"."CUSTOMER_DK"="DC"."DK")
5 - filter("DC"."REGION_NAME"='REGION #1')
6 - access("F"."PART_DK"="DP"."DK")
7 - filter("DP"."MFGR"=10)
15 - filter("DP"."MFGR"=10)
16 - access("F"."PART_DK"="DP"."DK")
17 - access("F"."SYS_NC00017$"=10)
21 - filter("DC"."REGION_NAME"='REGION #1')
22 - access("F"."CUSTOMER_DK"="DC"."DK")
26 - filter("DS"."REGION_NAME"='REGION #1')
27 - access("F"."SUPPLIER_DK"="DS"."DK")
Note
- star transformation used for this statement -
Hello everyone,
I'm kind of newbie with MDX language, I'm trying to get filtered measures from a cube with a specific layout.
Here is my exemple :
I want to get all the "order numbers" where the "invoice" cost is more than 300. Each invoice is linked with an ID, one order number can have several invoices.
So what I do is a select request with 2 dimensions : "order num" and "id_invoice"
Here is the result : I get all the cost sorted by "order num" and I can easealy identify those who are above 300
order num
Id_invoice
cost
Total
Total2
15450307
10032013094498
1671
1737
ok
15450307
10032013099835
66
1737
KO
15450596
10032013094078
8524
8524
ok
15451214
10032013094119
228
4348
KO
15451214
10032013097069
978
4348
ok
15451214
10032013097071
3142
4348
ok
15542434
10032013101736
142
142
KO
15550064
10032013097016
1261
1261
ok
15550346
10032013097586
2252
2252
ok
15550353
10032013098446
2617
2617
ok
What i need : In "cost", I need to have the sum of each cost which are above 300 in one line (without showing the invoice id)
order num
cost
Total
Total2
15450307
1671
1737
ok
15450596
8524
8524
ok
15451214
4120
4348
ok
15550064
1261
1261
ok
15550346
2252
2252
ok
15550353
2617
2617
ok
How is it possible to use a filter on a dimension without showing it or merge 2 attributes of the same dimension ?
The problem is that if I show "id" column, the filter doesn't work properly : it compares 300 with the total cost of the whole order and does not compare with each invoice (which could be under 300 ! - see "KO" in Total2 column)
Here is the request I use to generate this result :
with
member [Measures].[Total]
as (
[TP].[ID INVOICE].[All],
[TP].[ORDER NUM].currentmember,
[Measures].[COST]
member [Measures].[Total2]
as (
IIF([Measures].[COST] >
300, "ok",
"KO")
select
{[Measures].[COST],[Measures].[Total],[Measures].[Total2]}
on
columns,
Filter
[TP].[ORDER NUM].[ORDER
NUM].members *
[TP].[ID INVOICE].[ID
INVOICE].members
,[Measures].[COST]
> 0
on
rows
FROM [MYCUBE]
Thank you for your help !
Kind regards,
Olivier.Hi Olivier,
hereunder a similar query against the AW. For all order numbers, we sum all lines above 30 without diplaying the line numbers:
WITH
MEMBER [Measures].[lines above 30] AS
IIF(
[Measures].[Internet Sales Amount] > 30,
[Measures].[Internet Sales Amount],
null
MEMBER [Measures].[aggr lines above 30] AS
SUM(
exists(
[Internet Sales Order Details].[Sales Order Line].[Sales Order Line],
[Internet Sales Order Details].[Sales Order Number].currentmember
[Measures].[lines above 30]
SELECT
[Measures].[Internet Sales Amount],
[Measures].[aggr lines above 30]
} ON 0,
[Internet Sales Order Details].[Sales Order Number].[Sales Order Number] ON 1
FROM ( SELECT
[Product].[Category].[All Products] ON 0,
[Internet Sales Order Details].[Sales Order Number].&[SO51177]:
[Internet Sales Order Details].[Sales Order Number].&[SO51178]
} ON 1
FROM [Adventure Works] )
I reduced the cube with a subselect.
Philip, -
Load scd 1 and scd 2 in the same dimension
Hi
is there any order for load of customer dimension, when you have in the same dimension fields scd1 and scd2. which one it is better load first, scd type 2 and then, scd type 1 for each customer with state = 1?
thankshi Mark,
but I have one field that I want maintain the historic and then, more some fields that I want to update, always that it's possible. both case, in the same (customer) dimension.
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thanks,
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Compare two members from the same dimension in HFR
Hi,
Is it possibe to compare two members from the same dimension in HFR? The requirement is to compare Year and Week members from the same dimension. The Week date will be selected from POV. The corresponding Year date should be displayed in the report. Week dates are in the format W2008-03-07 and Year dates are in YTD2008-03-07.
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Regards,
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Time
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Details: i have the a dimension which has the following levels.
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SriHi SrikanthGS,
Assuming that with the last date available for the measure you mean the last date with non-empty figures, consider the following against the AW:
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