Maintenance of data Cube using DBMS_BUILD

Hello

I've got cube partitioned by date, with the 1 year retention period - every day a new created partition and the other removed.

No problem with the creation of data, but I am struggling to find a way to lose the old partition.

I'm looking for is

1) more information on DBMS_CUBE. BUILD to help me understand how to use it to reach my goal.

The official docs are examples of syntax, but I'm not finding in the syntax HERE to allow me to do this: http://docs.oracle.com/cd/E11882_01/appdev.112/e40758/d_cube.htm#ARPLS73464

(I would have the cube data cycle would be a common requirement that would be required by all and so surprised that it is not explicitly covered for example).

Is there another source of reference for the info DBMS_CUBE. BUILD that I can use to help me better understand the syntax fix myself?

(2) or a direct help with my problem

I found another post that addresses this specific point and gives the syntax to achieve this: https://community.oracle.com/thread/2154852

I tried to use the technique which recommends David, but it takes a lot of times more to manage that in order to do that requires a full version of the cube and actually does not reach the goal by the removal of the partition (no change of data in the cube and the values for the target partition remains).

The generation of complete cube takes too long, and I think that must be a quicker way of deleting a data partition, but am not able to do this.

When I run the command based on the advice of David (see below), in the CUBE_BUILD_LOG I see the CLEAR VALUES with the correct partition identified (that's the step that almost all of the time is spent on), but nothing really changes in the data when the cube is queried,

for example, I can query the cube for values in this partition and they stay.

No error is returned.

So I am very confused and do not know how to move it - any ideas?

for example, in the example below, I'm trying to delete the partition "20131230" which is a level in the hierarchy "STD" in the "TIME_1YEAR" of the "CUBE_MNE_E_RATED" cube dimension

I'm eager for this deletion, in the cube, all the data to date, but as above it takes a lot of time doing nothing.

When this command is executed the data actually, relative to this day table does not exist, and so it is not true that reconstruction including date based on data it finds in the fact table.

I'm on 11.2.0.3 Enterprise Edition.

BEGIN
    DBMS_CUBE.BUILD('"CUBE_MNE_E_RATED" USING
                       (FOR "TIME_1YEAR"
                        WHERE "TIME_1YEAR"."DIM_KEY" IS DESCENDANT OF ''20131230'' WITHIN "TIME_1YEAR"."STD"
                        BUILD(CLEAR))');
END;
/

Thank you in anticipation

Jim

Regd move 365 days entry windows:

You have a window mobile day or level the relational table entry containing the 365 lines last 365 days... It seems that this would trigger aggregations on a large scale along the time dimension hierarchies assuming the definitions of month/quarter/year regular. In this case, perhaps the cube full re-aggregation may be inevitable. The cube can attempt a full build/refresh (C) from other types of charges (? for quick or otherwise Complete, F for Fast Refresh etc) are not possible.

If today is April 4, 2014, so your input table gave April 4, 2013-April 3, 2014. The difference b/w done cube entry table b/w yesterday and today is that day = April 3, 2013 fell from the table. Month Apr 2013 with children from April 1, 2013 to 30 April 2013, this should trigger a new aggregation level months Member April 2013 and even a new Member of the month level aggregation Apr 2014 (since April 3, 2014 has now come in the picture).

Charge of OLAP via DBMS_CUBE. BUILD

Your best case scenario is for olap Manager do the following:

* reloading data for affected for months because of moving window - Apr 2013 and 2014 after only... that is to say reload the level data sheet for April 4, 2013 April 30, 2013, as well as for April 1, 2014, to April 3, 2014.

* re - aggregate affected higher level members like Apr 2013, 2nd quarter of 2013, 2013 year 2014 Apr, 2nd quarter 2014 and 2014 year alone.

Olap perspective load or dbms_cube.build load behavior, it is not an exact match due to the fact that entry window varies every day. FAST_SOLVE is closest, in my opinion.

A Complete (C) charge the fact:

* Clears all data - sheets as well as aggregates

* reloads all the data at the level sheet of the object (table/view) the input source

aggregates the cube according to the settings/aggregation design

A charge of FAST_SOLVE (S) for this:

* reloads all the data at the level sheet of the object (table/view) the input source... NOTE: this refill all the data of reln. not only for the day added to the entrance... independent source updated lopped or daily added.

* re - includes the affected/relevant part of the cube according to the settings/aggregation design

A FAST (F) refresh the fact:

* Load the data for the new dates only... that is will load data for April 3, 2014, but does not delete the data up-to-date lopped relational source: April 3, 2013

* re - includes the affected/relevant part of the cube according to the settings/aggregation design... in this case: April 2014, 2nd quarter of 2014, year 2014 alone. All 2013 aggregates remain as they did because they have not been erased.

Olap for DBMS_CUBE documentation. BUILD explains, if the cube can be built using a load of Partition (can handle more recent partitions as they appear but I guess he can't handle more delicate complexity relating to the partitions being cut at the base/start/front of the moving time window) or through refresh FAST charge (usually this needs a quick refreshment on MV to act as Cube source again without the complexity of the data will lack every day at the beginning of the input time window) then it falls on the full charge (charging data, cube of aggregates). There is a special type of load - FAST_SOLVE which is to reload all the data, but only hit reaggregate / higher levels of the cube.

Currently, the cube seems to function according to the COMPLETE (C) charge.

QUICKLY RESOLVE may be your Best Bet... recharge every day, placed affected qtrs/months/years only in the cube.

******************

DBMS_CUBE. BUILD has many options regarding the build/refresh of capacity.

Maybe you should try to reference the other parameters of the procedure to refine the process of generation.

I hope this helps.

-ERASE the partition corresponding to day being filed and also try to re-aggregation of stakeholders

BEGIN

DBMS_CUBE. BUILD)

script => ' USE of 'CUBE_MNE_E_RATED '.

(FOR 'TIME_1YEAR'

WHERE 'TIME_1YEAR '. "" "DIM_KEY" IS A DESCENDANT OF "20131230" IN THE "TIME_1YEAR" STD ".

BUILD)

CLEAR VALUES,

FIX

)

)',

method => of '-S tent FAST_SOLVE refresh method

refresh_after_errors to-online true,-refresh after errors

parallelism-online 1-parallelism

atomic_refresh => false, - atomic refresh

automatic_order-online order wrong, - automatic

Add an add_dimensions to-online true - dimensions

);

END;

-Reload all data, including the newly added date and aggregate/solve the cube incrementally

BEGIN

DBMS_CUBE. BUILD)

script => ' USE of 'CUBE_MNE_E_RATED '.

(

PLUM CHARGE OF SYNCHRONIZATION,

FIX

)',

method => of '-S tent FAST_SOLVE refresh method

refresh_after_errors to-online true,-refresh after errors

parallelism-online 1-parallelism

atomic_refresh => false, - atomic refresh

automatic_order-online order wrong, - automatic

Add an add_dimensions to-online true - dimensions

);

END;

Rgds
Shankar

Tags: Business Intelligence

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