Oracle BI is in use for years, has gone through many iterations, and is widespread across projects around the globe. Millions of analyses have been created, deployed, and run billions of times. The actual lifecycle of an Oracle BI query from its inception through to the effective delivery of results may therefore be regarded as a given commodity not requiring a closer look. Few people have regarded an OBI query from this point of view: "How does it get constructed? How does it get translated between the different architectural components and the RPD layers? How, through what, and where does its lifecycle get influenced? Where can we as users/developers/administrators actively intervene with its makeup and structure? Why do we genuinely have to have an understanding of the subtleties of the lifecycle to create successful BI solutions?"
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Back2 basics - A Day In The Life Of An Oracle Analytics Query
1. Back2Basics
A day in the life of an Oracle BI query
www.dimensionality.ch @Nephentur #obihackers | freenode
2. • Owner of Dimensionality GmbH in Switzerland
• Hacking OBI since 2001 (nQuire + Peregrin aquisitions by Siebel)
• Oracle ACE Associate BI/DWH
• Speaker at OpenWorld, KScope, regional Oracle User Groups...
• Part-time blogger on Oracle BI (http://dimensionality.ch)
• Full-time IRC (freenode | #obihackers) and OTN addict
• Oracle BI trainer for Oracle University since 2006
• Proud geek and gamer
• Responding to any and all questions 24 / 7 – especially on IRC
Who am I?
www.dimensionality.ch @Nephentur #obihackers | freenode
4. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
www.dimensionality.ch @Nephentur #obihackers | freenode
5. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
www.dimensionality.ch @Nephentur #obihackers | freenode
6. Why this presentation?
• Oracle BI has matured and is quite wide-spread
• As a result it’s often done worse than ever…
• Problem being: core of a whole range of products
• Hence: Back to basics presentation series
• Not understanding and comprehending query mechanisms is a
cardinal sin for any developer
• And no, “cloud” doesn’t eliminate the need for “comprehension”
www.dimensionality.ch @Nephentur #obihackers | freenode
7. Why this presentation?
• Alternative title “A normal day on the OTN forums”
www.dimensionality.ch @Nephentur #obihackers | freenode
8. Why this presentation?
• Going more into details from my “Worst practices” presentation
www.dimensionality.ch @Nephentur #obihackers | freenode
9. Why this presentation?
• Alleviate your struggle
• How can I get from front-end problems to the actual root cause?
• Why is my report returning the data it does?
• Why do I get old data back? (Spoiler alert: Cache!)
• Where can I find all bits and pieces of information for my
investigation?
• Why doesn’t my request hit the source I thought it would?
• Why does it bypass our aggregate tables?
• If I change the RPD – what will be the impact?
www.dimensionality.ch @Nephentur #obihackers | freenode
10. Why this presentation?
Simply put:
Without a solid understanding of how and why
queries function inside the Oracle BI core you will have
a very hard time of analyzing any issue pertaining to
data, aggregations, modelling, performance etc. !
www.dimensionality.ch @Nephentur #obihackers | freenode
11. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
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12. What the packaging says
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13. What the packaging says
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14. What the packaging says
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15. And “under the covers”?
www.dimensionality.ch @Nephentur #obihackers | freenode
Needs
more
detail…
20. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
www.dimensionality.ch @Nephentur #obihackers | freenode
21. VA / DV / DVD / BICS / ASCS?
www.dimensionality.ch @Nephentur #obihackers | freenode
But Christian it’s all about cloud, data visualization and mashups now!
Surely I don’t need to bother with all this query stuff?
22. VA / DV / DVD / BICS?
www.dimensionality.ch @Nephentur #obihackers | freenode
23. VA / DV / DVD / BICS?
www.dimensionality.ch @Nephentur #obihackers | freenode
24. VA / DV / DVD / BICS?
www.dimensionality.ch @Nephentur #obihackers | freenode
But Christian it’s all about data visualization and mashups now! Surely I
don’t need to bother with all this?
25. So what about VA / DV / DVD / BICS?
www.dimensionality.ch @Nephentur #obihackers | freenode
Yes DV/ASCS/BICS are way(s) forward, but…
Really? Think about it:
• They all still access Subject Areas (indirectly)
• Performance problems won’t just automagically disappear
– You’ll probably run into even more thanks to mashups and file uploads
• Just because there are nice graphs doesn’t mean there isn’t still a very
clever system in the background!
• But yes, there’s a new toy and new possibilities
• Watch out for the next dissection talk!
26. So what about VA / DV / DVD / BICS?
www.dimensionality.ch @Nephentur #obihackers | freenode
Yes VA, DV and DVD are the way forward, but…
Really? Think about it:
• They all still access Subject Areas (indirectly)
• Performance problems won’t just automagically disappear
– You’ll probably run into even more thanks to mashups and file uploads
• Just because there are nice graphs doesn’t mean there isn’t still a very
clever system in the background!
• But yes, there’s a new toy and new possibilities
• Watch out for the next dissection talk!
27. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
www.dimensionality.ch @Nephentur #obihackers | freenode
29. This is where
very few
magic should
happen
This is where
THE magic
happens
We don’t
really care
about this part
This is where
the actual
workload
should happen
“The workday” aka detailed query flow
www.dimensionality.ch @Nephentur #obihackers | freenode
Browser,
SmartView,
other tools
BI Server
WLS
Managed
Server
Presentation
Server
Sources
Browser,
SmartView,
other tools
BI Server
WLS
Managed
Server
Presentation
Server
30. To this detail architectureMapping these flow details in the
BI Server
“Magic” details
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31. Your friend the log
www.dimensionality.ch @Nephentur
12c: obis1-query.log
11g: nqquery.log
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32. Your friend the log
www.dimensionality.ch @Nephentur
12c: obis1-query.log
11g: nqquery.log
-------------------- SQL Request, logical request hash:a180d345SET VARIABLE
OBIS_REFRESH_CACHE=1,QUERY_SRC_CD='Report',SAW_SRC_PATH='/users/web
logic/Preso/Main',PREFERRED_CURRENCY='USD',DISABLE_CACHE=1,LOG_LEVEL=
2;
SELECT
0 s_0,
"D - Sample Federated"."Time"."T05 Per Name Year" s_1,
"D - Sample Federated"."Measures"."1a- Revenue (Orcl Db Tables Only)" s_2
FROM "D - Sample Federated"
ORDER BY 2 ASC NULLS LAST
FETCH FIRST 5000001 ROWS ONLY
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33. Your friend the log
www.dimensionality.ch @Nephentur
12c: obis1-query.log
11g: nqquery.log
-------------------- SQL Request, logical request hash:a180d345SET VARIABLE
OBIS_REFRESH_CACHE=1,QUERY_SRC_CD='Report',SAW_SRC_PATH='/users/web
logic/Preso/Main',PREFERRED_CURRENCY='USD',DISABLE_CACHE=1,LOG_LEVEL=
2;
SELECT
0 s_0,
"D - Sample Federated"."Time"."T05 Per Name Year" s_1,
"D - Sample Federated"."Measures"."1a- Revenue (Orcl Db Tables Only)" s_2
FROM "D - Sample Federated"
ORDER BY 2 ASC NULLS LAST
FETCH FIRST 5000001 ROWS ONLY
[2016-05-27T13:40:38.29+00:00] [OBIS] [TRACE:3] [] [] [ecid: aa89eaf6-8094-
45b1-8c59-ea46b2a1e14e-00008dd6,0:1:17:5] [sik: ssi] [tid: 996f4700]
[messageid: USER-18] [requestid: e295001d] [sessionid: e2950000] [username:
weblogic] -------------------- Sending query to database named 01 - Sample App
Data (ORCL) (id: <<387385>>), connection pool named Sample Relational
Connection, logical request hash a180d345, physical request hash f5274c5e: [[
WITH
SAWITH0 AS (select sum(T418.Revenue) as c1,
T653.Per_Name_Year as c2
From
BISAMPLE.SAMP_TIME_MTH_D T653 /* D02 Time Month Grain */ ,
BISAMPLE.SAMP_REVENUE_F T418 /* F10 Billed Rev */ where (
T418.Bill_Mth_Key = T653.Mth_Key ) group by T653.Per_Name_Year)select
D1.c1 as c1, D1.c2 as c2, D1.c3 as c3 from ( select 0 as c1, D1.c2 as c2, D1.c1
as c3from SAWITH0 D1order by c2 ) D1 where rownum <= 5000001
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34. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
www.dimensionality.ch @Nephentur #obihackers | freenode
35. Intelligent Request Generation
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• Receives the queries from the front-end
• Answers, SmartView, Visual Analyzer,
Data Visualization (Desktop)
• Other tools using the Oracle BI Server
ODBC API or Web Servives
36. Logical Request Generation
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• Creates the actual logical request to be
processed
• Doesn’t “write the query”
• Doesn’t decide which business models,
LTSs or sources to use
• Preparation stage for Cache Services and
Navigator
37. Logical Request Generation
www.dimensionality.ch @Nephentur #obihackers | freenode
-------------------- SQL Request, logical request hash:
ee9cf87d
SET VARIABLE
OBIS_REFRESH_CACHE=1,QUERY_SRC_CD='Report',SAW_SRC_PATH='/users/weblogic/Preso/Main',PREFER
RED_CURRENCY='USD',DISABLE_CACHE=1,LOG_LEVEL=5;
SELECT
0 s_0,
"D - Sample Federated"."Time"."T05 Per Name Year" s_1,
"D - Sample Federated"."Measures"."1a- Revenue (Orcl Db Tables Only)" s_2,
"D - Sample Federated"."Measures"."1b- Revenue (Essbase Cube Only)" s_3
FROM "D - Sample Federated"
ORDER BY 2 ASC NULLS LAST
FETCH FIRST 5000001 ROWS ONLY
38. Cache Services
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• Optional step: Caching enabled?
• Checks if request can be fulfilled by existing
cache entries
• Cache doesn’t need to match 1:1
– Existing entries can be aggregated
– Subsets can be extracted
• Cache can be forcibly circumvented
39. Cache Services
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• Optional step: Caching enabled?
• Checks if request can be fulfilled by existing
cache entries
• Cache doesn’t need to match 1:1
– Existing entries can be aggregated
– Subsets can be extracted
• Cache can be forcibly circumvented
40. Cache Services
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• Optional step: Caching enabled?
• Checks if request can be fulfilled by existing
cache entries
• Cache doesn’t need to match 1:1
– Existing entries can be aggregated
– Subsets can be extracted
• Cache can be forcibly circumvented-------------------- SQL Request, logical request hash:
ee9cf87d
SET VARIABLE
OBIS_REFRESH_CACHE=1,QUERY_SRC_CD='Report',SAW_SRC_PATH='/users/weblogic/Preso/Main',PREFER
RED_CURRENCY='USD',DISABLE_CACHE=1,LOG_LEVEL=5;
[…]
ORDER BY 2 ASC NULLS LAST
FETCH FIRST 5000001 ROWS ONLY
41. Cache Services
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• All SELECT columns
– Existing in cache entries or
– Derived from cache entries (bins, substring or
other analysis-based formulas/functions)
• WHERE clause must match or be a subset
of cache entries
– Query for 10 US states will hit a cache entry containing all
the US states
• Join conditions must match or be a subset
46. Cache Services
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[2016-05-28T15:31:22.112+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:24:5] [sik: ssi] [tid: de7b700]
[messageid: USER-21] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- Cache Hit on query: [[
Matching Query: SET VARIABLE
OBIS_REFRESH_CACHE=1,QUERY_SRC_CD='Report',SAW_DASHBOARD='/users/weblogic/_portal',SAW_DASHBOARD_PG='page
1',SAW_SRC_PATH='/users/weblogic/Preso/Cache Hit',PREFERRED_CURRENCY='USD';SELECT
0 s_0,
"A - Sample Sales"."Time"."T05 Per Name Year" s_1
FROM "A - Sample Sales"
ORDER BY 2 ASC NULLS LAST
FETCH FIRST 5000001 ROWS ONLY
Created by: weblogic
]]
[2016-05-28T15:31:22.114+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:24:5] [sik: ssi] [tid: de7b700]
[messageid: USER-55] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- Order By Safely Removed [[
'OrderBy: D1.c2 asc NULLS LAST [ added for join ] ' above the cache hit plan is safely dropped due to the preserved order by ' OrderBy: c2 asc NULLS LAST'
from cache entry
47. Cache Services
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[2016-05-28T15:31:22.114+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:24:5] [sik: ssi] [tid: de7b700]
[messageid: USER-50] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- The logical query seed the plan cache [[
plan
RqList <<120136>> [for database 0:0,0] /* FETCH FIRST 5000001 ROWS ONLY */
0 as c1 [for database 0:0,1],
D1.c2 as c2 [for database 0:0,0]
Child Nodes (RqJoinSpec): <<120142>> [for database 0:0,0]
RqJoinNode <<120143>> []
(
RqList <<120146>> [for database 0:0,9]
T1.2 as c2 [for database 0:0,9],
T1.2 as c3 [for database 0:0,9]
Child Nodes (RqJoinSpec): <<120152>> [for database 0:0,9]
RqJoinNode <<120153>> []
CacheTable T1
) as D1
DetailFilter: not D1.c3 < '2012' [for database 0:0,0]
48. Cache Services
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[2016-05-28T15:31:22.139+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:28] [sik: ssi] [tid: de7b700] [messageid:
USER-34] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- Query Status: Successful Completion
[2016-05-28T15:31:22.139+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:28] [sik: ssi] [tid: de7b700] [messageid:
USER-29] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- Physical Query Summary Stats: Number of physical queries 1,
Cumulative time 0.000, DB-connect time 0.000 (seconds)
[2016-05-28T15:31:22.139+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:28] [sik: ssi] [tid: de7b700] [messageid:
USER-24] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- Rows returned to Client 2
[2016-05-28T15:31:22.139+00:00] [OBIS] [TRACE:3] [] [] [ecid: 86cb6a39-9f56-4305-a0e6-dd95618de970-00000820,0:1:28] [sik: ssi] [tid: de7b700] [messageid:
USER-33] [requestid: f7340014] [sessionid: f7340000] [username: weblogic] -------------------- Logical Query Summary Stats: Elapsed time 0.030, Total time in BI
Server 0.029, Execution time 0.008, Response time 0.029, Compilation time 0.007 (seconds), logical request hash 48047dfa
49. Navigator
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• The true brain of the operation
• Parses BI Server metadata
• Decides on actual logical tables, logical
table sources etc.
• Uses 3 components to decide on details
– Multi-pass / sub-request
– Fragmentation
– Aggregates
50. Multi-pass / sub-request
www.dimensionality.ch @Nephentur #obihackers | freenode
[2016-05-27T14:28:54.799+00:00] [OBIS] [TRACE:3] [] [] [ecid: aa89eaf6-8094-45b1-8c59-ea46b2a1e14e-000092ae,0:1:9:3] [sik: ssi] [tid: 996f4700] [messageid: USER-23] [requestid:
af740029] [sessionid: af740000] [username: weblogic] -------------------- General Query Info: [[
Repository: ssi, Subject Area: 06 - Federated Sources, Presentation: D - Sample Federated
]]
[2016-05-27T14:28:54.800+00:00] [OBIS] [TRACE:3] [] [] [ecid: aa89eaf6-8094-45b1-8c59-ea46b2a1e14e-000092ae,0:1:9:3] [sik: ssi] [tid: 996f4700] [messageid: USER-2] [requestid:
af740029] [sessionid: af740000] [username: weblogic] -------------------- Logical Request (before navigation): [[
RqList [1]
0 as c1 GB,
D0 Time.T05 Per Name Year as c2 GB,
1a- Revenue (Orcl Db Tables Only):[DAggr(F0 Revenue Base Measures.1a- Revenue (Orcl Db Tables Only) by [ D0 Time.T05 Per Name Year] )] as c3 GB,
1b- Revenue (Essbase Cube Only):[DAggr(F0 Revenue Base Measures.1b- Revenue (Essbase Cube Only) by [ D0 Time.T05 Per Name Year] )] as c4 GB
OrderBy: c2 asc NULLS LAST
51. Multi-pass / sub-request
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RqBreakFilter <<390156>>[2] [for database 0:0,0] /* FETCH FIRST 5000001 ROWS ONLY */
RqList <<390157>> [for database 0:0,0]
0 as c1 GB [for database 0:0,1],
D901.c5 as c2 GB [for database 0:0,0],
D901.c1 as c3 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D901.c2 as c4 GB [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390167>> [for database 0:0,0]
RqJoinNode <<390168>> []
(
RqList <<390171>> [for database 0:0,0]
D1.c1 as c1 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D2.c1 as c2 GB [for database 0:0,0],
coalesce( D1.c2 , D2.c2) as c5 GB [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390181>> [for database 0:0,0]
RqJoinNode <<390182>> []
(
RqList <<390186>> [for database 3023:28:01 - Sample App Data (ORCL),78]
sum(F10 Billed Rev.Revenue by [ D02 Time Month Grain.Per_Name_Year] ) as c1 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D02 Time Month Grain.Per_Name_Year as c2 GB [for database 3023:28:01 - Sample App Data (ORCL),78]
Child Nodes (RqJoinSpec): <<390195>> [for database 3023:28:01 - Sample App Data (ORCL),78]
RqJoinNode <<390196>> [(InNode:<<390196>>) (OutNode:<<390199>>) ]
SAMP_TIME_MTH_D AS D02 Time Month Grain
RqJoinNode <<390199>> [(InNode:<<390196>>) (OutNode:<<390199>>) ]
SAMP_REVENUE_F AS F10 Billed Rev
DetailFilter: F10 Billed Rev.Bill_Mth_Key = D02 Time Month Grain.Mth_Key [for database 3023:28:01 - Sample App Data (ORCL),78]
GroupBy: [ D02 Time Month Grain.Per_Name_Year] [for database 3023:28:01 - Sample App Data (ORCL),78]
OrderBy: c2 asc [for database 3023:28:01 - Sample App Data (ORCL),78]
) as D1 FullOuterStitchJoin <<390183>> On D1.c2 = D2.c2; actual join vectors: [ 1 ] = [ 1 ]
(
RqList <<390215>> [for database 0:0,0] distinct
D1.c1 as c1 [for database 0:0,0],
D1.c2 as c2 [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390221>> [for database 0:0,0]
RqJoinNode <<390222>> []
(
RqList <<390225>> [for database 3023:10:03 - Essbase Sample E1 Flat,84]
sum(Sample Flattened.Gross Revenue by [ Sample Flattened.Years] ) as c1 GB [for database 3023:10:03 - Essbase Sample E1 Flat,84],
Sample Flattened.Years as c2 GB [for database 3023:10:03 - Essbase Sample E1 Flat,84]
Child Nodes (RqJoinSpec): <<390234>> [for database 3023:10:03 - Essbase Sample E1 Flat,84]
RqJoinNode <<390235>> []
Sample T12016
GroupBy: [ Sample Flattened.Years] [for database 3023:10:03 - Essbase Sample E1 Flat,84]
) as D1
OrderBy: c2 asc [for database 0:0,0]
) as D2
OrderBy: c5 asc NULLS LAST [for database 0:0,0]
) as D901
52. Multi-pass / sub-request
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RqBreakFilter <<390156>>[2] [for database 0:0,0] /* FETCH FIRST 5000001 ROWS ONLY */
RqList <<390157>> [for database 0:0,0]
0 as c1 GB [for database 0:0,1],
D901.c5 as c2 GB [for database 0:0,0],
D901.c1 as c3 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D901.c2 as c4 GB [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390167>> [for database 0:0,0]
RqJoinNode <<390168>> []
(
RqList <<390171>> [for database 0:0,0]
D1.c1 as c1 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D2.c1 as c2 GB [for database 0:0,0],
coalesce( D1.c2 , D2.c2) as c5 GB [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390181>> [for database 0:0,0]
RqJoinNode <<390182>> []
(
RqList <<390186>> [for database 3023:28:01 - Sample App Data (ORCL),78]
sum(F10 Billed Rev.Revenue by [ D02 Time Month Grain.Per_Name_Year] ) as c1 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D02 Time Month Grain.Per_Name_Year as c2 GB [for database 3023:28:01 - Sample App Data (ORCL),78]
Child Nodes (RqJoinSpec): <<390195>> [for database 3023:28:01 - Sample App Data (ORCL),78]
RqJoinNode <<390196>> [(InNode:<<390196>>) (OutNode:<<390199>>) ]
SAMP_TIME_MTH_D AS D02 Time Month Grain
RqJoinNode <<390199>> [(InNode:<<390196>>) (OutNode:<<390199>>) ]
SAMP_REVENUE_F AS F10 Billed Rev
DetailFilter: F10 Billed Rev.Bill_Mth_Key = D02 Time Month Grain.Mth_Key [for database 3023:28:01 - Sample App Data (ORCL),78]
GroupBy: [ D02 Time Month Grain.Per_Name_Year] [for database 3023:28:01 - Sample App Data (ORCL),78]
OrderBy: c2 asc [for database 3023:28:01 - Sample App Data (ORCL),78]
) as D1 FullOuterStitchJoin <<390183>> On D1.c2 = D2.c2; actual join vectors: [ 1 ] = [ 1 ]
(
RqList <<390215>> [for database 0:0,0] distinct
D1.c1 as c1 [for database 0:0,0],
D1.c2 as c2 [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390221>> [for database 0:0,0]
RqJoinNode <<390222>> []
(
RqList <<390225>> [for database 3023:10:03 - Essbase Sample E1 Flat,84]
sum(Sample Flattened.Gross Revenue by [ Sample Flattened.Years] ) as c1 GB [for database 3023:10:03 - Essbase Sample E1 Flat,84],
Sample Flattened.Years as c2 GB [for database 3023:10:03 - Essbase Sample E1 Flat,84]
Child Nodes (RqJoinSpec): <<390234>> [for database 3023:10:03 - Essbase Sample E1 Flat,84]
RqJoinNode <<390235>> []
Sample T12016
GroupBy: [ Sample Flattened.Years] [for database 3023:10:03 - Essbase Sample E1 Flat,84]
) as D1
OrderBy: c2 asc [for database 0:0,0]
) as D2
OrderBy: c5 asc NULLS LAST [for database 0:0,0]
) as D901
RqBreakFilter <<390156>>[2] [for database 0:0,0] /* FETCH FIRST 5000001 ROWS ONLY */
(
(
RqList <<390186>> [for database 3023:28:01 - Sample App Data (ORCL),78]
sum(F10 Billed Rev.Revenue by [ D02 Time Month Grain.Per_Name_Year] ) as c1 GB [for database 3023:28:01 - Sample App Data (ORCL),78],
D02 Time Month Grain.Per_Name_Year as c2 GB [for database 3023:28:01 - Sample App Data (ORCL),78]
Child Nodes (RqJoinSpec): <<390195>> [for database 3023:28:01 - Sample App Data (ORCL),78]
RqJoinNode <<390196>> [(InNode:<<390196>>) (OutNode:<<390199>>) ]
SAMP_TIME_MTH_D AS D02 Time Month Grain
RqJoinNode <<390199>> [(InNode:<<390196>>) (OutNode:<<390199>>) ]
SAMP_REVENUE_F AS F10 Billed Rev
DetailFilter: F10 Billed Rev.Bill_Mth_Key = D02 Time Month Grain.Mth_Key [for database 3023:28:01 - Sample App Data (ORCL),78]
GroupBy: [ D02 Time Month Grain.Per_Name_Year] [for database 3023:28:01 - Sample App Data (ORCL),78]
OrderBy: c2 asc [for database 3023:28:01 - Sample App Data (ORCL),78]
) as D1 FullOuterStitchJoin <<390183>> On D1.c2 = D2.c2; actual join vectors: [ 1 ] = [ 1 ]
(
RqList <<390215>> [for database 0:0,0] distinct
D1.c1 as c1 [for database 0:0,0],
D1.c2 as c2 [for database 0:0,0]
Child Nodes (RqJoinSpec): <<390221>> [for database:0,0]
RqJoinNode <<390222>> []
(
RqList <<390225>> [for database 3023:10:03 - Essbase Sample E1 Flat,84]
sum(Sample Flattened.Gross Revenue by [ Sample Flattened.Years] ) as c1 GB [for database 3023:10:03 - Essbase Sample E1 Flat,84],
Sample Flattened.Years as c2 GB [for database 3023:10:03 - Essbase Sample E1 Flat,84]
Child Nodes (RqJoinSpec): <<390234>> [for database 3023:10:03 - Essbase Sample E1 Flat,84]
RqJoinNode <<390235>> []
Sample T12016
GroupBy: [ Sample Flattened.Years] [for database 3023:10:03 - Essbase Sample E1 Flat,84]
) as D1
) as D2
) as D901
64. Aggregate Navigator
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• Which LTS contains data on a level of
aggregation to fulfill the query with the
least amount of effort?
• Hierarchy logical level # of elements
• LTS priority group
• LTS order
66. Aggregate Navigator
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WITH
SAWITH0 AS (select sum(T216.Revenue) as c1,
T795.PER_NAME_YEAR as c2
from
BISAMPLE.SAMP_TIME_QTR_D T795 /* D03 Time Quarter Grain */ ,BISAMPLE.SAMP_TIME_QTR_D T795 /* D03 Time Quarter Grain */ ,BISAMPLE.SAMP_TIME_QTR_D T795 /* D03 Time Quarter Grain */ ,BISAMPLE.SAMP_TIME_QTR_D T795 /* D03 Time Quarter Grain */ ,
BISAMPLE.SAMP_REVENUE_FA2 T216 /* F21 Rev. (Aggregate 2) */
where ( T216.Bill_Qtr_Key = T795.QTR_KEY )
group by T795.PER_NAME_YEAR)
select D1.c1 as c1, D1.c2 as c2, D1.c3 as c3 from ( select 0 as c1,
D1.c2 as c2,
D1.c1 as c3
from
SAWITH0 D1
order by c2 ) D1 where rownum <= 5000001
68. Aggregate Navigator
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WITH
SAWITH0 AS (select sum(T418.Revenue) as c1,
T42.Calendar_Date as c2,
T42.Per_Name_Year as c3
from
BISAMPLE.SAMP_TIME_DAY_D T42 /* D01 Time Day Grain */ ,BISAMPLE.SAMP_TIME_DAY_D T42 /* D01 Time Day Grain */ ,BISAMPLE.SAMP_TIME_DAY_D T42 /* D01 Time Day Grain */ ,BISAMPLE.SAMP_TIME_DAY_D T42 /* D01 Time Day Grain */ ,
BISAMPLE.SAMP_REVENUE_F T418 /* F10 Billed Rev */
where ( T42.Calendar_Date = T418.Bill_Day_Dt and T42.Per_Name_Year = '2012' )
group by T42.Calendar_Date, T42.Per_Name_Year)
select D1.c1 as c1, D1.c2 as c2, D1.c3 as c3, D1.c4 as c4 from ( select 0 as c1,
D1.c2 as c2,
D1.c3 as c3,
D1.c1 as c4
from
SAWITH0 D1
order by c3, c2 ) D1 where rownum <= 5000001
69. Optimized Query Rewrites
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• Writes the effective query sent against a
source
• Source type
• Source features
• Native function shipping driven by these
configurations (and version)
72. Optimized Query Rewrites
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• Results are retrieved from sources
• Combined and post-calculated as needed
• Written into the cache
• Passed to the initially calling interface
73. Outline
• Why this presentation
• Overview / What the packaging says
• VA / DV / DVD / BICS / ASCS
• The actual day in the life of a query
• Query execution details
• Summary
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74. Summary
www.dimensionality.ch @Nephentur #obihackers | freenode
1. Know the flow
This is where
very few
magic should
happen
This is where
THE magic
happens
We don’t
really care
about this part
This is where
the actual
workload
should happen
Browser,
SmartView,
other tools
BI Server
WLS
Managed
Server
Presentation
Server
Sources
Browser,
SmartView,
other tools
BI Server
WLS
Managed
Server
Presentation
Server