, we can get an approximate direction of the OLTP. Although the overall data volume of the system is large, but the proportion of the system active data in the total data is small, we can enlarge the memory capacity to cache the active data in memory as much as possible; Although IO access is very frequent, but the amount of data accessed per visit is small and discrete, our requirement for disk storage is that IOPS perform well and throughput is a secondary factor; Concurrency is very high, CPU
Tags: ODI partial user process modification supports storage elementsWith Oracle 12c introducing the in memory component, the Oracle database has dual-mode data storage that enables support for mixed-type applications: traditional, row-saving data meets OLTP applications, and data stored in columns satisfies OLAP applications that are primarily queried. The in memory component can be used with other database component functions, and does not require t
the system active data in the total data is small, we can enlarge the memory capacity to cache the active data in memory as much as possible; Although IO access is very frequent, but the amount of data accessed per visit is small and discrete, our requirement for disk storage is that IOPS perform well and throughput is a secondary factor; Concurrency is very high, CPU per second to deal with a lot of requests, so CPU processing power needs to be relatively strong; Although the amount of data pe
May 15 15:20:58 2013 Copyright (c) 1982,201 0, Oracle. all rights reserved. connected to: Oracle Database 11g Enterprise Edition Release 11.2.0.2.0-64bit Production With the Partitioning, OLAP, data Mining and Real Application Testing options SQL> create directory test_dir as '/home/orauat/zzj'; Directory created. SQL> Grant read, write on directory test_dir to cux; Grant succeeded. SQL> exit Disconnected from Oracle Database 11g Enterprise Edition R
The following content is taken from the Internet and sorted out.
Terms:
Bi (Business Intelligence): Business Intelligence,
DW (data warehouse): Data Warehouse. For details, see section Q1.
OLTP (on-line transaction processing): Online Transaction Processing
It is also known as a transaction-oriented processing system. Its basic feature is that the customer's raw data can be immediately transmitted to the Computing Center for processing and the processing results can be given in a very short t
for management personnel. Data Warehouse is mainly used in decision support systems. Its main purpose is to "extract" Information and expand it to process the application of the data warehouse-based decision support system (DSS.
2 The Data warehouse-based decision support system (DSS) is composed of three components: Data warehousing and OLAP, on-Line Analytical Pro-cessing), Data Mining technology (Data Mining ).
Introduction to Mondrian MDX and mondrianmdx
Introduction to Mondrian MDX
MDX (multidimen1_expression) is the language used to construct and query OLAP databases, just as SQL is used to build and operate relational databases.
MDX was the first developed by Microsoft and is part of the 1997 system ole db for OLAP (ODBO). Mosha Pasumansky is one of the MDX Language designers. MDX is soon implemented by oth
Roles
Before discussing how the newly created role affects the xmla code of the oalkaline database, let's briefly describe the role in SSAs. The following is a role editing interface. Although it has seven option configuration interfaces (not discussed about the mining structure Interface), all of them can be classified into three categories:
1.Read defined Permissions
A person with this permission can connect to the OLAP database, and then it wi
Sap bi product line Note: I have not used all SAP bi products, so the following descriptions may be incorrect.1.1: Let's first look at the data warehouse (DW)SAP biw is a multidimensional database with a management platform. It provides an ETL platform in BW for ETL.It is worth mentioning that BW provides a standard bapi interface that allows third-party ETL tool providers to extract data from SAP data warehouses, resulting in many ETL third-party tools. No DW exists in the acquired Bo product l
Run the following command on the source database server:
Log On As A system user to execute SQL statements.
C: \ Documents ents and Settings \ Administrator> sqlplus system/Password
SQL * Plus: Release 10.2.0.1.0-production on Thursday March 28 17:16:47 2013Copyright (c) 1982,200 5, Oracle. All rights reserved.
Connect:Oracle Database 10g Enterprise Edition Release 10.2.0.1.0-64bit production with the partitioning, OLAP and Data Mining options
amount of data accessed each time is small and discrete, our requirement for disk storage is that the IOPS performance is good, and the throughput is a secondary factor;
The concurrency is high, and the number of requests processed by the CPU per second is naturally large, so the CPU processing capability needs to be strong;
Although the amount of data for each interaction with the client is not very large, but the network interaction is very frequent, so the network device for interaction betw
2014Copyright (c) 1982,200 9, Oracle and/or its affiliates. All rights reserved.Connected to: Oracle Database 11g Enterprise Edition Release 11.2.0.1.0-ProductionWith the Partitioning, OLAP, Data Mining and Real Application Testing optionsExport done in US7ASCII character set and AL16UTF16 NCHAR character setServer uses WE8MSWIN1252 character set (possible charset conversion)About to export specified tables via Conventional Path..... Exporting table
Mondrian Introduction to MDX MDX (Multidimensional Expression) is the language that constructs the query OLAP database; just like SQL is to build an operational relational database language. MDX was pioneered by Microsoft as part of the 1997 Year system OLE DB for OLAP (ODBO) ;Mosha Pasuma Nsky is One of the MDX language designers;MDX is quickly used by other OLAP
:
Deterministic data analysis: mainly simple data statistics tasks, such as OLAP, attention to rapid response, the implementation of components such as Impala;
Exploratory data analysis: Mainly information-related discovery tasks, such as searching, focusing on unstructured full-volume information collection, implementing components such as search;
Predictive data analysis: Mainly machine learning tasks, such as
In practical work, often hear beginners say: "Large table partition can certainly improve query performance." In fact, when you do not understand the application of the situation, blind to create a partition not only can not improve query performance, but also may lead to query performance degradation. Therefore, before deciding whether to use a partition, you must understand the current application environment.
Generally speaking, the application of database is divided into two kinds: OLTP and
(Operational Data store,ods) ". In ODS mode, data is copied from the business database to
A central location, which is extracted from here to multiple data marts. ODS is from customers, products and other business
A "real-time snapshot" of the business situation that is organized in an industry perspective. It does not contain historical information, but can be very
Easily meet the needs of a historical database or a set of theme-oriented data marts.
We generally call it a "merged Data War
ETL Tools: IBM Datastage
Informatica PowerCenter
Teradata ETL Automation
OLAP (On-line Analytical Processing)
Microsoft related products: SSAS
Olap--rolap--molap
Related (to find):
OLAP (On-line analysis processing) is a kind of software technology that enables analysts, managers, or executives to access information quickly, consistently and interactively
data in the total data is small, we can enlarge the memory capacity to cache the active data in memory as much as possible;Although IO access is very frequent, but the amount of data accessed per visit is small and discrete, our requirement for disk storage is that IOPS perform well and throughput is a secondary factor;Concurrency is very high, CPU per second to deal with a lot of requests, so CPU processing power needs to be relatively strong;Although the amount of data per interaction with th
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