lookup table in data warehouse

1. What is hashing technology?The hashing technique establishes a definite correspondencebetween the stored location of the record and the key word of the record , so that each keyword key corresponds to a storage location F (key).When looking, the mapping F (key) of the given value is found based on this determined correspondence, and must be at f (key) if the record exists in the lookup collection.Hashing technology is both a storage method and a

get data from the Data warehouse, or they do not depend on the data warehouse when they get data from the operating system.fact : The fact is that the information unit in the Data

number, work class, exit Section..., Income section) L detailed list of precise cash splitting results Tb_cashaccuratesplitresult (flow number, work class, exit Section..., Income section) L stream non-precise splitting record table Tb_inaccuratesplitrecord..., Income section) L split the journal exception record table Tb_outlistspliterrorgb (flow number, work class, exit section,..., Error Type Code) L sp

The common dwh architecture is as simple as figures 2 and 3. Generally, for an enterprise, the data lifecycle is 5-7 years, especially for detailed data. The lower the data granularity level, the shorter the lifecycle, the higher the data granularity and the longer the lifecycle. For the flow account

stochastic analysis is essentially an iterative and continuous optimization of the problem in an interactive environment. Business users want direct access to the data warehouse through a graphical user interface (GUI), and do not want programmers as intermediaries. Supports concurrent queries for data warehouses and large-volume users, which is a typical featur

changes. In the above example, it may be necessary to analyze the results of the biwork in 2012 when the overall level of purchase, but the purchase amount has been reduced since 2013, the reason may be related to the city, the stores in Beijing may be more than in Sanya stores. In a situation like this, it's not easy to update the biwork in the data warehouse directly, but a new piece of

Objective:Ready to systematize a set of distributed Data Warehouse Modeling Practice Guide, the first list of the table, is to design a goal for themselves.The first part of the basic articleChapter One concept and definition of data Warehouse1.1 Data Management System1.2

previous day with the hash of the previous day, this strategy is more complex, described here, For example, a membership table, its primary key is MemberID, and the status of the member is likely to be updated every day, After the first extraction, we generate an alternate table A, containing two fields, the first of which is MemberID, The second is that all the fields except MemberID are stitched together

to design; Data Warehouse design is intentionally introduced redundancy, the use of anti-paradigm approach.4, the provision of different functions: The database is designed to capture data, the Data Warehouse is designed for the analysis of

Warehouse new Features 1 SQL Server relational database management system for Data Warehouse Improvement 1 Star Association 2 Partitioned Table Parallel 3 aligning partitioned Indexed views 4 GROUPING SETS4 MERGE5 Change data Capture 6 Minimum log record INSERT7

necessary to change the storage mode of spatial data and load the required spatial data, avoid repeated loading and uninstallation of unnecessary data. Layered Manager 1. Hierarchical Manager architecture The layered manager is a key part for quick browsing of large-scale data. It controls the layer-by-layer refine

1 Introduction Database has become an indispensable part of large software, database is playing a more and more important role in software system, and database design is becoming an important factor affecting software performance and robustness. As the complexity of the software architecture grows higher, developers have to design more tables to store the data they need. The more tables, the more complex the database. Complex databases don't have any

makefile is required to minimize conversion before it is loaded into the HDFs file system or hive Data Warehouse, you can load the file directly. After determining the target table and the split specification, Hive has a command to load the data. Pig is a high-level language for d