数据仓库与OLAP多维数据集? [英] Data Warehouse vs. OLAP Cube?
问题描述
谁能解释一下数据仓库和OLAP多维数据集之间的真正区别是什么?
Can anyone explain what is really distinction between Data Warehouse and OLAP Cubes?
对于同一件事，他们是否使用不同的方法?
Are they different approach for same thing?
其中一个与其他相比是否已被弃用?
Is one of them deprecated in comparison with other?
其中之一是否存在性能问题?
Are there any performance issues in one of them?
欢迎任何解释
推荐答案
数据仓库是一种数据库，其设计使更容易地分析数据†而且速度更快，通常来自多个来源的数据.它通常具有维度模型，即事实表和维度表.
A data warehouse is a database with a design that makes analyzing data easier† and faster, often with data from multiple sources. It usually has a dimensional model, meaning fact tables and dimension tables.
OLAP是一组可以对数据集执行的操作，例如枢转，切片，切块，钻孔.例如，可以使用Excel PivotTables执行OLAP操作.有某些用于OLAP"的SQL语句，例如PIVOT，group by CUBE()，group by ROLLUP()和group by GROUPING SETS()，以及各种窗口函数
OLAP is a set of operations that one can do on a data set, such as pivoting, slicing, dicing, drilling. For example, one can do OLAP operations with Excel PivotTables. There are certain SQL statements which are "for OLAP", such as PIVOT, group by CUBE(), group by ROLLUP(), and group by GROUPING SETS(), as well as the various window functions
OLAP服务器是一种服务器软件，可简化OLAP操作，例如通过缓存和查询重写. OLAP操作通常用 MDX 表示，并且您的OLAP服务器可能会将MDX转换为常规SQL数据库.或者它可能会针对自己的二进制文件格式工作. OLAP服务器内部的维度模型称为 OLAP多维数据集
An OLAP Server is a type of server software that facilitates OLAP operations, for example with caching and query re-writing. OLAP operations are often expressed in MDX, and your OLAP server might translate MDX into regular SQL for your database. Or it might work against its own binary file format. A dimensional model inside an OLAP server is called an OLAP cube
您可以拥有一个数据仓库，而根本不使用OLAP(只需运行报告).
You can have a data warehouse and not use OLAP at all (you just run reports).
您还可以在数据仓库以外的其他对象(例如平面文件)上执行OLAP操作.
You can also do OLAP operations on something other than a data warehouse, such as a flat file.
对于同一件事，他们是否使用不同的方法?
Are they different approach for same thing?
否，数据仓库是一种以易于分析的格式存储数据的地方，而OLAP是一种分析数据的方法.
No, a data warehouse is a place to store data in an easily analyzable format, and OLAP is a method to analyze data.
其中一个与其他相比是否已被弃用?
Are one of them deprecated in comparison with other?
不，它们相互补充，因为数据仓库使使用OLAP进行数据分析变得容易，而OLAP可以使分析数据仓库更加有用.
No, they compliment each other in that a data warehouse makes it easy to analyze data using OLAP, and OLAP can make analyzing a data warehouse more useful.
其中之一是否存在性能问题?
Is there any performance issues in one of them?
是的.数据仓库用于存储大量数据，因此查询将花费一些时间.通过使用索引或列数据库，缓存，RAID 10 SSD，分区以及预先聚合一些数据，可以提高性能.
Yes. A data warehouse is meant to store lots and lots of data, and thus it will take time to query. Performance can be improved by using indexes or a columnar db, caching, RAID 10 SSDs, partitioning, and by pre-aggregating some data.
另请参见: https://dba.stackexchange.com/问题/45655/多维数据集的度量和维度
†而不是使交易更容易/更完整
† as opposed to making transactions easier/more integral
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