Building A History: The Lego Group by Sarah Herman

By Sarah Herman

The historical past of LEGO from its early days making yo-yos and different wood toys (which persisted until eventually the 1960s), a list of its toys, together with the recognized construction bricks and Duplo and the way it has tailored to the altering toy marketplace e.g. bringing in authorized items equivalent to celebrity Wars and Harry Potter.

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The clauses include: (1) maintained by {system | user}, (2) refresh {immediate | deferred}, (3) data initially {immediate | deferred}, and (4) enable query optimization. A MQT can be maintained either by a system or by a user. In the first case, the maintained by system clause is used. This is a default clause. For a system-maintained MQT, one can define either automatic or non-automatic refreshing mode. In the automatic mode, a MQT is refreshed automatically as the result of changes in the content of its base tables.

B 0 represents the 20 bit, B 1 represents the 21 bit, etc. Every value of an indexed attribute is represented on the same number of n bits. As a result, the encoded values in a table form n bitmaps. The bitmaps are called bit-slices. Data retrieval and computation are supported either by the bit-sliced index arithmetic [63] or by means of a dedicated retrieval function [55]. Additionally, a mapping data structure is required for mapping the encoded values into their real values [55]. Compression Techniques The second approach that allows to reduce the size of a bitmap index defined on an attribute of high cardinality is based on compression.

Lines 10-12), creating a temporary bitmap. Next, the bitmap for ’London’ is retrieved (cf. line 8) and it is ANDed with the temporary bitmap (cf. line 7). The result bitmap is then converted to ROWIDs of records fulfilling the criteria (cf. line 6). In this query plan table Time was accessed with the support of a B-tree index defined on its primary key, rather than by means of the bitmap join index. 42 R. Wrembel ------------------------------------------------------------------------------------|Id | Operation |Name |Rows |Bytes |Cost(%CPU)|Time | ------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1| 58 | 13 (8)|00:00:01| | 1 | SORT AGGREGATE | | 1| 58 | | | | 2 | NESTED LOOPS | | 21| 1218 | 13 (8)|00:00:01| | 3 | HASH JOIN | | 22| 1012 | 12 (9)|00:00:01| | 4 | TABLE ACCESS FULL |PRODUCTS | 3| 51 | 3 (0)|00:00:01| | 5 | TABLE ACCESS BY INDEX ROWID |SALES | 1155|33495 | 8 (0)|00:00:01| | 6 | BITMAP CONVERSION TO ROWIDS | | | | | | | 7 | BITMAP AND | | | | | | | 8 | BITMAP INDEX SINGLE VALUE |BI_CU_SALES| | | | | | 9 | BITMAP OR | | | | | | |10 | BITMAP INDEX SINGLE VALUE|BI_PR_SALES| | | | | |11 | BITMAP INDEX SINGLE VALUE|BI_PR_SALES| | | | | |12 | BITMAP INDEX SINGLE VALUE|BI_PR_SALES| | | | | |13 | TABLE ACCESS BY INDEX ROWID |TIME | 1| 12 | 1 (0)|00:00:01| |14 | INDEX UNIQUE SCAN |PK_TIME | 1| | 0 (0)|00:00:01| ------------------------------------------------------------------------------------- Alternatively, it is possible to create one bitmap join index on all of the dimension attributes.

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