data granularity in data warehouse

Warehouse. From here you can see that it has several features:1. The redundancy of the dimension tables is large, mainly because the dimensions are generally small (relative to the fact table), and the redundancy of the dimension tables can save a lot of space in the fact table. 2. Fact sheets are generally very large, and if queried in an ordinary way, the time to get the results generally is not acceptable to us. So it usually has to do some specia

is classified as a fact, the attribute tree meets the following requirements: Each node corresponds to a data source mode attribute (simple or composite attribute ). Root corresponds to the identifier of the F object. For each node v, all subsequent attributes corresponding to V are determined by the function. 1.1.3 trim and port the attribute tree 1.1.4 define dimension 1.1.5 define measurement 1.1.6 generate fact Mo

The methods for modeling SQL Server four data warehouses are mainly grouped into the following four categories. The first class is the three-paradigm modeling of relational databases, and we usually use the three-normal modeling method to build various operational database systems. The second type is the three-paradigm Data warehouse model advocated by Inmon, w

Backup | Data 1: Data Warehouse schema Backup Including the database architecture and OLAP architecture; The database includes a dimension table, fact table, and other temporary or control class tables whose structure is generated by generating SQL scripts. Note: Its primary key, index and so on are to be generated; The OLAP schema is saved by default in the "C:\

Scenario 4 Data Warehouse Management DWParallel 4 100%-> must obtain a specified 4 degree of parallelism, if the number of processes obtained is less than the number of degrees of parallelism set, the operation failsParallel_min_percent: If set to 100, as aboveILM: Information Lifecycle ManagementHigh compression of dormant data on low-cost channels (e.g. tape dr

transactions by game, department, and item. Cross analysis. In our system, our data granularity is day. Okay, since it's a simplified version, We don't need to worry so much about what needs analysis and design are all saved. Go to the database design page. Our database consists of four dimension tables (department, game, and item, Time Dimension), a fact table (game transaction

Using the Javadate class Data Warehouse dimension tableDate Category:, returns the number of milliseconds for a relative date. Accurate to milliseconds. However, the internationalization and sub-timezone display of dates is not supported.The date class began to evolve from the Java Development Package (JDK) 1.0, when it included only a few ways to get or set the various parts of a date

1. Environmental preparednessOs:centos 6.4Turn off SELinux and iptablesDeployment Puppet: 1.0 Puppet 3.7 Department Install puppet Source: http://yum.puppetlabs.com/puppetlabs-release-el-6.noarch.rpmComplete Puppetmaster/agent deployment, certificate signing ...PUPPETDB is a data warehouse that can query nodes, facter, report, catalog, resources and other information through restful HTTP.2. Installing PUPPE

Apache Tajo is a hadoop-based relational and distributed database warehouse system. At the beginning of its design, Tajo was designed to achieve low latency, scalability, and instant query through advanced database technologies, the database warehouse system that can be aggregated to make up for the shortcomings in real-time and relational transactions such as hadoop. Tajo also supports SQL standards, so yo

cannot be blank "), Array ("NotEmpty", "email", "email address cannot be left blank "), Array ("isEmail", "email", "Incorrect email address format "), Array ("hasOne", "email", "email address occupied ") ); /** * Overwrite the method for adding data to the database of the parent class. * Perform md5 encryption on the user password first, and then call the parent class method to write the data to the databa

Before entering php data into the database, clear the phpintval and mysql int values. For more information, see. Php saves data to mysql We plan to clean up data before warehouse receiving at the dao layer, such as varchar trim and int for intval. One day, I suddenly remembered that the value range of php intval is the

Hadoop series hive (data warehouse) installation and configuration1. Install in namenodeCD/root/softTar zxvf apache-hive-0.13.1-bin.tar.gzMv apache-hive-0.13.1-bin/usr/local/hadoop/hive2. Configure environment variables (each node needs to be added)Open/etc/profile# Add the following content:Export hive_home =/usr/local/hadoop/hiveExport Path = $ hive_home/bin: $ path# Environment variables take effectSourc

On the theoretical concept of slowly changing Dimension slowly changing dimension see Data Warehouse Series-Slow slowly changing dimension (slowly changing Dimension) common three types and prototype design This article summarizes several ways to realize the slow gradual change dimension, and analyzes the logical process of changing attribute and historical attribute output. Example one: Using the slowly

business dimension information for integrated integration, this situation is more appropriate for generating surrogate keys to master keys. Summary The construction of the dimension table seems relatively simple, in most cases the business library will be directly, but in addition to the different levels of the dimension of Redundancy (Star model), but also need to grasp the details of the following dimensions of the construction of attention, after all, the dimension of errors will

Objective: To learn about Data Warehouses(The following is only a personal attempt to learn data warehouses.Is superficialI hope you will be able to provide guidance after reading this article.I will learn more on this basis in the future) Steps:1. Create a database data table to fill in the data2. Create a data

Microsoft's Azure Data Warehouse is a distributed system based on the MPP architecture:Control node is responsible for managing the system and accepting requests from users, Compute node is responsible for computing.Currently, Azure Data Warehouse has landed in the country. You can use the new portal page to manage it,

After the Oracle database has been upgraded to 11 GB recently, some problems have occurred. I began to find some things that need to be summarized. Every time I thought: next time, when I build my own data warehouse, be sure to pay attention to these details and do the work well at the initial stage of warehouse creation. 1. redo log Design1) if it can be put sep

Reprint please the head source link and the tail two-dimensional code together reprint, this article from countercurrent fish yuiop:http://blog.csdn.net/hejjunlin/article/details/52768613Preface: The data of the database is increasing every day, the overall risk of automatic deletion mechanism is too big, want to keep more historical data for query, so it is imperative to change from small hbase to large hb

Big Data Current major trends (self-understanding)file system, deployment, various streams and open source tools-------ETL Development (BI project)----Data statistical analysis------data Mining, machine learning Image from the analysisfirst, about KAKFA Kafka relatedKafka, a distributed messaging system developed by LinkedIn, is written in Scala and is widely use

Tags: loading HBA datasets Organization development int checked Storage sub Data Warehouse is a subject-oriented (Subject oriented), integrated (integrate), relatively stable (non-volatile), data collection that reflects historical changes (time Variant). Used to support management decisions. (1) Topic-oriented: Index data