Some practical tips for using OLAP functions
The online analytical Processing,olap function is very flexible and powerful. By using these functions, you can find a simple solution for some problems that are either to iterate over one or more cursors, or to be recursive. In some other cases, it is much easier to use OLAP functions or auxiliary tables than to not
PIVOT rotates table-valued expressions by converting unique values in one column of an expression to multiple columns in the output, and performs aggregations if necessary for any remaining column values that are required in the final output. UNPIVOT performs the reverse operation with PIVOT, converting columns of table-valued expressions to column values.In fact, Pivot
July is the taglib of Mondrian's performance layer, which maintains a good development progress.I have never used it for a long time. I forgot about it and wrote down my little experiences.
1. Localization1.1 search for all resources. properties files and convert them to resources_zh.properties files.1.2 native2ascii resources_zh.properties1.3 search for all XML files under the WEB-INF/jpivot and convert them to xxx_zh.xml
2. ArchitectureJuly's architecture seems an alternative, but it is actual
In 1960s, E. F. codd, the father of relational databases, proposed a relational model to promote the development of online transaction processing (OLTP) (data is stored in the form of tables rather than files ). 1993, E. f. codd proposed the OLAP concept, and believed that OLTP could not meet the needs of end users for database query and analysis, and SQL for simple query of large databases could not meet the requirements of end users for analysis. A
Why is OLAP generated?With the development of database technology, the amount of data stored in database is transition from M-byte and g (Gigabit) bytes to T-byte and P-byte, meanwhile, the user's query needs are more and more complex, and the design is not only to query or manipulate one or several records in a relational table, Moreover, the data analysis and information synthesis of the thousands records in many times, the relational database can n
Tags: instance error log display encryption fill span system log src parameter configurationFirst, the problem found Failed to start data Analysis Service for SQL Server View system log errors as follows: A detailed error is displayed after double-clicking the error: There is an error in the metadata manager. Instantiate from file "\\?\c:\program Files\Microsoft SQL Server\msas11. An error occurred while mssqlserver\olap\data\tfs_analysis.0.db\vdimt
data sources; Time-Varying: data storage provides information from a historical perspective (such as the past 5 to 10 years); Non-Easy: Data Warehouses are physically separated to store data (It only requires two data access operations: data initialization and data access)
Data Warehouses support on-line analytical processing, which is different from operating databases.Supported online transaction processing (on-line transaction processing ).
Note: distinguish OLTP from
Converts OLTP data to provide acceptable performance in the OLAP system, which requires a series of operations.
Merge data
First, we must be able to process all relevant information of a specific project (products, customers, employees) from multiple OLTP (on-line transaction processing, online transactions) the system is merged into an OLAP (Online Analytical Processing, Online Analytical Processing
How BI projects are developed:Learn how OLAP is analyzed:Multidimensional modeling analysis of data, that is, the design of their own data, then the program automatically generate the data of the square bodyData side body:1. Automatic table structure, only the columns you need2. Generate an SQL statement (with query criteria)3. Cache sql, through your pre-defined multidimensional analysis, establish the relationship between the fact table and the dime
Online Transaction Processing OLTP (on-line transaction processing)
OLTP is the main application of traditional relational databases, mainly for basic and daily transaction processing, such as bank transactions.
OLAP (on-line analytical processing)
OLAP is the main application of the data warehouse system. It supports complex analysis operations, focuses on decision support, and provides intuitive and easy
Mondrian is an open-source project. An OLAP (Online Analytical Processing) engine written in Java. It implements queries using the MDX language and reads data from relational databases (RDBMS. The results are displayed in multiple dimensions through Java APIs.
We all know that Online Analytical Processing (OLAP) needs to analyze a large amount of data in real time. The term "online" means that the system mu
Today's data processing can be broadly divided into two broad categories: online transaction processing OLTP (on-line transaction processing), online analytical processing OLAP (On-line Analytical Processing). OLTP is the main application of the traditional relational database, mainly basic and daily transaction processing, such as bank transaction. OLAP is the main application of Data Warehouse system, sup
Profile
On-Line Analytical processing (Online analytical processing, hereinafter referred to as OLAP) is a fast software technology that shares multidimensional information and online data access and analysis for specific problems. OLAP is designed to support complex analysis operations, focusing on decision support for decision-makers and senior management, and can quickly and flexibly perform complex que
"transforms" according to the storage model requirements of the DW The data format, and then "load" the process to the DW, it should be emphasized that the DB model is the ER model, followed byNormalization ofdesign principles, and DW's data model isSnowflake Typestructure or star structure, with the topic-oriented, problem-oriented design ideas, so the DB and DW model structure is different, need to be converted.(4)olap--Online Analysis System, simp
Parallel Database for OLTP and OLAPJust ASurvey article on materials in parallel database products andTechnologies for OLTP/OLAP applications. It mainly covers majorCommercial/academic efforts on developing parallel DBMS to solve theEver growing large amount of relational data processing problem.Part I–parallel DBMSs1.1 Parallel Database for OLAP (SHARED-NOTHING/MPP)TeraData–teradata Home–teradata dbc/1012
In today's article I would like to discuss a special T-SQL language structure in SQL Server-the pivot operator introduced from SQL Server 2005. I often cite this and the language structure is the most dangerous one in SQL Server--and soon you'll know why. Before we go into specific problems and pitfalls, first I want to give you a basic overview of what you can accomplish with pivot in SQL Server.OverviewTh
OLAP (on-line analysis processing)It is a kind of software technology that enables analysts, administrators, or executors to quickly, consistently, and interactively access information from multiple perspectives to gain a deeper understanding of data.
OLAP is designed to meet decision-making support or specific query and report requirements in multi-dimensional environments. Its core technology is the conce
Teach you how to use Pandas pivot tables to process data (with learning materials) and pandas learning materials
Source: bole online-PyPer
Total2203 words,Read5Minutes.This article mainly explains pandas's pivot_table function and teaches you how to use it for data analysis.
Introduction
Most people may have experience using pivot tables in Excel. In fact, Pandas also provides a similar function called
Cloveretl
Cloveretl is a data ETL framework that extracts business data and converts it to the type required by OLAP. It is still stored in relational databases. Typically, the order and orderitem tables in the parent-child relationship need to be converted into a fact table. In orderitem, a large amount of redundant order data, such as date, customer, and branch, is required for statistics convenience. It seems that this is only a few lines in the c
SQL Server skills: how to monitor and optimize OLAP Databases
It is very important to optimize the performance of online analysis and processing. Fortunately, some tools can help monitor and improve the operation of OLAP databases.
The Microsoft SQL Server Analysis Service (SSAS) provides a powerful engine used to create and manage data mining applications and online analysis and processing systems. To ac
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