Oracle OLAP cube build question

Hello,
I am trying to build a reasonably large cube (around 100
million rows from the underlying relational fact table). I am using
Oracle 10g Release 2. The cube has 7 dimensions, the largest of which
is TIME (6 years of data with the lowest level day). The cube build
never finishes.
Apparently it collapses while doing "Auto Solve". I'm assuming this
means calculating the aggregations for upper levels of the hierarchy
(although this is not mentioned in any of the documentation I have).
I have two questions related to this:
1. Is there a way to keep these aggregations from being performed at
cube build time on dimensions with a value-based hierarchy? I already
have the one dimension designated as level-based unchecked in the
"Summarize To" tab in AW manager (TIME dimension).
2. Are there any other tips that might help me get this cube built?
Here is the log from the olapsys.xml_load_log table:
RECORD_ID LOG_DATE AW XML_MESSAGE
1. 09-MAR-06 SYS.AWXML 08:18:51 Started Build(Refresh) of APSHELL Analytic Workspace.
2. 09-MAR-06 SPADMIN.APSHELL 08:18:53 Attached AW APSHELL in RW Mode.
3. 09-MAR-06 SPADMIN.APSHELL 08:18:53 Started Loading Dimensions.
4. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members.
5. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for ACCOUNT.DIMENSION (1 out of 9 Dimensions).
6. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for ACCOUNT.DIMENSION. Added: 0. No Longer Present: 0.
7. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for CATEGORY.DIMENSION (2 out of 9 Dimensions).
8. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for CATEGORY.DIMENSION. Added: 0. No Longer Present: 0.
9. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for DATASRC.DIMENSION (3 out of 9 Dimensions).10. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for DATASRC.DIMENSION. Added: 0. No Longer Present: 0.
11. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for ENTITY.DIMENSION (4 out of 9 Dimensions).
12. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for ENTITY.DIMENSION. Added: 0. No Longer Present: 0.
13. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for INPT_CURRENCY.DIMENSION (5 out of 9 Dimensions).
14. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for INPT_CURRENCY.DIMENSION. Added: 0. No Longer Present: 0.
15. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for INTCO.DIMENSION (6 out of 9 Dimensions).
16. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for INTCO.DIMENSION. Added: 0. No Longer Present: 0.
17. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for RATE.DIMENSION (7 out of 9 Dimensions).
18. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for RATE.DIMENSION. Added: 0. No Longer Present: 0.
19. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for RPTCURRENCY.DIMENSION (8 out of 9 Dimensions).
20. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Finished Loading Members for RPTCURRENCY.DIMENSION. Added: 0. No Longer Present: 0.
21. 09-MAR-06 SPADMIN.APSHELL 08:18:54 Started Loading Dimension Members for TIME.DIMENSION (9 out of 9 Dimensions).
22. 09-MAR-06 SPADMIN.APSHELL 08:18:55 Finished Loading Members for TIME.DIMENSION. Added: 0. No Longer Present: 0.
23. 09-MAR-06 SPADMIN.APSHELL 08:18:55 Finished Loading Dimension Members.
24. 09-MAR-06 SPADMIN.APSHELL 08:18:55 Started Loading Hierarchies.
25. 09-MAR-06 SPADMIN.APSHELL 08:18:55 Started Loading Hierarchies for ACCOUNT.DIMENSION (1 out of 9 Dimensions).
26. 09-MAR-06 SPADMIN.APSHELL 08:18:55 Finished Loading Hierarchies for ACCOUNT.DIMENSION. 1 hierarchy(s) ACCOUNT_HIERARCHY Processed.
27. 09-MAR-06 SPADMIN.APSHELL 08:18:55 Started Loading Hierarchies for CATEGORY.DIMENSION (2 out of 9 Dimensions).
28. 09-MAR-06 SPADMIN.APSHELL 08:18:56 Finished Loading Hierarchies for CATEGORY.DIMENSION. 1 hierarchy(s) CATEGORY_HIERARCHY Processed.
29. 09-MAR-06 SPADMIN.APSHELL 08:18:56 Started Loading Hierarchies for DATASRC.DIMENSION (3 out of 9 Dimensions).
30. 09-MAR-06 SPADMIN.APSHELL 08:18:56 Finished Loading Hierarchies for DATASRC.DIMENSION. 1 hierarchy(s) DATASRC_HIER Processed.
31. 09-MAR-06 SPADMIN.APSHELL 08:18:56 Started Loading Hierarchies for ENTITY.DIMENSION (4 out of 9 Dimensions).
32. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies for ENTITY.DIMENSION. 2 hierarchy(s) ENTITY_HIERARCHY1, ENTITY_HIERARCHY2 Processed.
34. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies for INPT_CURRENCY.DIMENSION. No hierarchy(s) Processed.
36. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies for INTCO.DIMENSION. 1 hierarchy(s) INTCO_HIERARCHY Processed.
37. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Hierarchies for RATE.DIMENSION (7 out of 9 Dimensions).
38. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies for RATE.DIMENSION. No hierarchy(s) Processed.
39. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Hierarchies for RPTCURRENCY.DIMENSION (8 out of 9 Dimensions).
40. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies for RPTCURRENCY.DIMENSION. No hierarchy(s) Processed.
41. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Hierarchies for TIME.DIMENSION (9 out of 9 Dimensions).
42. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies for TIME.DIMENSION. 2 hierarchy(s) CALENDAR, FISCAL_CALENDAR Processed.
43. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Hierarchies.
44. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes.
45. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for ACCOUNT.DIMENSION (1 out of 9 Dimensions).
46. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Attributes for ACCOUNT.DIMENSION. 6 attribute(s) ACCTYPE, CALC, FORMAT, LONG_DESCRIPTION, RATETYPE, SCALING Processed.
47. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for CATEGORY.DIMENSION (2 out of 9 Dimensions).
48. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Attributes for CATEGORY.DIMENSION. 2 attribute(s) CALC, LONG_DESCRIPTION Processed.
49. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for DATASRC.DIMENSION (3 out of 9 Dimensions). 50. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Attributes for DATASRC.DIMENSION. 3 attribute(s) CURRENCY, INTCO, LONG_DESCRIPTION Processed.
51. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for ENTITY.DIMENSION (4 out of 9 Dimensions).
52. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Attributes for ENTITY.DIMENSION. 3 attribute(s) CALC, CURRENCY, LONG_DESCRIPTION Processed.
53. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for INPT_CURRENCY.DIMENSION (5 out of 9 Dimensions).
54. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Attributes for INPT_CURRENCY.DIMENSION. 2 attribute(s) LONG_DESCRIPTION, REPORTING Processed.
55. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for INTCO.DIMENSION (6 out of 9 Dimensions).
56. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Finished Loading Attributes for INTCO.DIMENSION. 2 attribute(s) ENTITY, LONG_DESCRIPTION Processed.
57. 09-MAR-06 SPADMIN.APSHELL 08:18:57 Started Loading Attributes for RATE.DIMENSION (7 out of 9 Dimensions).
58. 09-MAR-06 SPADMIN.APSHELL 08:18:58 Finished Loading Attributes for RATE.DIMENSION. 1 attribute(s) LONG_DESCRIPTION Processed.
59. 09-MAR-06 SPADMIN.APSHELL 08:18:58 Started Loading Attributes for RPTCURRENCY.DIMENSION (8 out of 9 Dimensions).
60. 09-MAR-06 SPADMIN.APSHELL 08:18:58 Finished Loading Attributes for RPTCURRENCY.DIMENSION. 2 attribute(s) LONG_DESCRIPTION, REPORTING Processed.
61. 09-MAR-06 SPADMIN.APSHELL 08:18:58 Started Loading Attributes for TIME.DIMENSION (9 out of 9 Dimensions).
62. 09-MAR-06 SPADMIN.APSHELL 08:20:26 Finished Loading Attributes for TIME.DIMENSION. 3 attribute(s) END_DATE, LONG_DESCRIPTION, TIME_SPAN Processed.
63. 09-MAR-06 SPADMIN.APSHELL 08:20:26 Finished Loading Attributes.
64. 09-MAR-06 SPADMIN.APSHELL 08:20:26 Finished Loading Dimensions.
65. 09-MAR-06 SPADMIN.APSHELL 08:20:26 Started Updating Partitions.
66. 09-MAR-06 SPADMIN.APSHELL 08:20:26 Finished Updating Partitions.
67. 09-MAR-06 SPADMIN.APSHELL 08:20:40 Started Loading Measures.
68. 09-MAR-06 SPADMIN.APSHELL 08:20:40 Started Load of Measures: SIGNEDDATA from Cube FINANCE.CUBE.
69. 09-MAR-06 SPADMIN.APSHELL 10:54:06 Finished Load of Measures: SIGNEDDATA from Cube FINANCE.CUBE. Processed 100000001 Records. Rejected 0 Records.
70. 09-MAR-06 SPADMIN.APSHELL 10:54:06 Started Auto Solve for Measures: SIGNEDDATA from Cube FINANCE.CUBE.

Hi, I've taken a few minutes to do a quick analysis. I just saw in your post that this isn't "real data", but some type of sample. Here is what I'm seeing. First off, this is the strangest dataset I've ever seen. With the exception of TIME, DATASOURCE, and RPTCURRENCY, every single other dimension is nearly 100% dense. Quite truthfully, in a cube of this many dimensions, I have never seen data be 100% dense like this (usually with this many dimensions its more around the .01% dense max, usually even lower than that). Is it possible that the way you generated the test data would have caused this to happen?
If so, I would strongly encourage you to go back to your "real" data and run the same queries and post results. I think that "real" data will produce a much different profile than what we're seeing here.
If you really do want to try and aggregate this dataset, I'd do the following:
1. Drop any dimension that doesn't add analytic value
Report currency is an obvious choice for this - if every record has exactly the same value, then it adds no additional information (but increases the size of the data)
Also, data source falls into the same category. However, I'd add one more question / comment with data source - even if all 3 values DID show up in the data, does knowing the data source provide any analytical capabilities? I.e. would a business person make a different decision based on whether the data is coming from system A vs. system B vs. system C?
2. Make sure all remaining dimensions except TIME are DENSE, not sparse. I'd probably define the cube with this order:
Account...........dense
Entity..............dense
IntCo...............dense
Category.........dense
Time...............sparse
3. Since time is level based (and sparse), I'd set it to only aggregate at the day and month levels (i.e. let quarter and year be calculated on the fly)
4. Are there really no "levels" in the dimensions like Entity? Usually companies define those with very rigid hierarchies (assuming this means legal entity)
Good luck with loading this cube. Please let us know how "real" this data is. I suspect with that many dimensions that the "real" data will be VERY sparse, not dense like this sample is, in which case some of the sparsity handling functionality would make a huge benefit for you. As is, with the data being nearly 100% dense, turning on sparsity for any dimension other than TIME probably kills your performance.
Let us know what you think!
Thanks,
Scott

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9921 COMPLETED REATTACH AW RW WAIT    BUILD
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Thomas

Thomas,
I cannot advise you for or against based on the small amount of information I have. I will not deny that at 15 dimensions you are at the upper limit of what you can achieve using the current (11.1) OLAP technology, but I have seen cubes of this size built and queried, so I know it is possible.
The answer would depend on many things: hardware, query tools, expectations for query and build performance, and whether you have a viable alternative technology (which will determine how hard you will work to get past problems). It even depends on your project time frames, since release 11.2 is currently in beta and will, we hope, handle greater volumes of data than 11.1 or 10g.
One important factor is how you partition your cube. At what level do you load the data (e.g. DAY or WEEK)? What is your partition level (e.g. MONTH or QUARTER)? A partition that loads, say, 10 million rows, is going to be much easier to build than a partition with 50 million rows. To decide this you need to know where your users will typically issue queries, since queries that cross partitions (e.g. ask for data at the YEAR level but are partitioned by WEEK) are significantly slower than those that do not cross partitions (e.g. ask for data at WEEK when you are partitioned by MONTH).
Cube-based MVs can offer advantages for cubes of this size even if you define a single, 15-dimensional, cube. One nice trick is to only aggregate the cube up to the partition level. Suppose, for example, that you load data at the DAY level and partition by QUARTER. Then you would make QUARTER be the top level in you dimension instead of YEAR or ALL_YEARS. The trick is to make YEAR be an ordinary attribute of QUARTER so that it appears in the GROUP BY clause of the cube MV. Queries that ask for YEAR will still rewrite against the cube, but the QUARTERS will be summed up to YEAR using standard SQL. The result will generally be faster than asking the cube to do the same calculation. This technique allows you to lower your partition level (so that there are fewer rows per partition) without sacrificing on query performance.
Cube-based MVs also allow you to raise the lowest level of any dimension (to PRODUCT_TYPE instead of PRODUCT_SKU say). Queries that go against the upper levels (PRODUCT_TYPE and above) will rewrite against the cube, and those that go against the detail level (PRODUCT_SKU) will go direct to the base tables. This compromise is worth making if your users only rarely query against the detail level and are willing to accept slower response times when they do. It can reduce the size of the cube considerably and is definitely worth considering.
David

OLAP cubes from heterogeneous data sources using XML DB

hi.
Q:1
How we can create an OLAP cube (XML cubes) from XML data sources if using XML DB.
Q:2
How we can create an OLAP cubes from warehouses and flat files and covert these cubes into XML cubes.
Q:3
Is there any other tool (Except Analytical workspace manager AWM) which supports the construction of OLAP cubes in XML format from heterogeneous data sources?
Edited by: user11236392 on Aug 21, 2009 3:50 AM

Hi Stuart!
Your undersatnding is partially correct. i am working for providing an architecture for XOLAP, XML is one of my data source.
The idea is to generate uniform cubes from heterogeneous sources that can be integrated into a global cube. instead of building Oracle OLAP cubes from all the sources (this work is already done) i want to generate an XCube from XML data sources using XQuery.
On the other hand if we have generated the Oracle OLAP cube from other sources like warehouses or flat files. i have to convert these Oracle OLAP cube into XML cube for uniformity. in an research paper i find that there is an operator Xcube embedded in XQuery which converts the multidimensional data (cube) into XML cube. im looking for the implementation of this operator in Query that how this operator works.
hope u understand my architecture. but if u still have some confusion, kindly give me ur mail id. i will mail the diagram of my architecture.
thanks.
saqib

Specifying OLAP Cubes On XML Data

Hi,
is there any good example on how does OLAP handle XML data ?
is it possible such a management in Oracle 9i Release 2 ?

Hi Stuart!
Your undersatnding is partially correct. i am working for providing an architecture for XOLAP, XML is one of my data source.
The idea is to generate uniform cubes from heterogeneous sources that can be integrated into a global cube. instead of building Oracle OLAP cubes from all the sources (this work is already done) i want to generate an XCube from XML data sources using XQuery.
On the other hand if we have generated the Oracle OLAP cube from other sources like warehouses or flat files. i have to convert these Oracle OLAP cube into XML cube for uniformity. in an research paper i find that there is an operator Xcube embedded in XQuery which converts the multidimensional data (cube) into XML cube. im looking for the implementation of this operator in Query that how this operator works.
hope u understand my architecture. but if u still have some confusion, kindly give me ur mail id. i will mail the diagram of my architecture.
thanks.
saqib

ORACLE olap - dimension with huge number of members.

Hi Experts,
I have modeling a ORACLE OLAP cube with 10 dimensions. I have one of the dimensions which have huge leaf members...(probably 1 billion).. How many dimension members i can have for one dimension. Is there any limitation to the dimension members ?
Thanks and Regards
Siva

Hi there,
I'm not sure of the theoretical limits, but I would never recommend trying to build a dimension with 1 billion members.
In situations were such granular data exists, it is common to leave this in table and load data into the OLAP cube at a more aggregate level.
Which business entity are you trying to model in a 1 billion member dimension?
Thanks,
Stuart Bunby
OLAP Blog: http://oracleOLAP.blogspot.com
OLAP Wiki: http://wiki.oracle.com/page/Oracle+OLAP+Option
OLAP on OTN: http://www.oracle.com/technology/products/bi/olap/index.html
DW on OTN : http://www.oracle.com/technology/products/bi/db/11g/index.html

Oracle OLAP cube build question

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