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Introduction to ETL technology: Introduction to ETL, data warehouse, and etl Data WarehouseETL is the abbreviation of Extract-Transform-Load. It is used to describe the process of extracting, transforming, and loading
Brief introduction Data integration is a key concept in the Data warehouse. The design and implementation of the ETL (data extraction, transformation and loading) process is an extremely important part of the Data
ETL concepts The three ETL letters represent extract, transform, and load, namely, extraction, conversion, and loading. (1) Data Extraction: extract the data required by the target data source system from the source
Etl,extraction-transformation-loading abbreviations, Chinese names are data extraction, conversion, and loading. Most warehouse-based data architectures can be summarized as: Data source-->ods (operational datastore)-->DW-->DM (data
sales_order--columns" Order_number, Customer_number, Product_code, Order_date, Entry_date, Order_ Amount "--where" Entry_date >= Date_add (current_date (), Interval-1 Day) and Entry_date 3) Add a piece of data to the source libraryINSERT into Source.sales_order values (Null,7,3,date_add (Current_date (), Interval-1 Day), Date_add (Current_date (), Interval-1 day), 10000); commit;4) Perform sqoop operationsSqoop Job--exec myjob_15) query in the RDS Li
In the data warehouse project, ETL is undoubtedly the most tedious, time-consuming, and unstable. If the data source and target are both oracle and meet certain conditions, you can use In the data warehouse project,
coordination jobsHDFs dfs-put-f coordinator.xml/user/root/(4) Run the coordination jobOozie Job-oozie Http://cdh2:11000/oozie-config/root/job-coord.properties-runFrom the Oozie Web console, you can see the coordinated jobs ready to run, with the status of Prep as shown in.This coordination job starts on July 11, 2016 and executes 14 points per day. The end date is very late, which is set for December 31, 2020. Be aware of the time zone settings. Oozie The default time zone is UTC and does not w
In the data warehouse project, ETL is undoubtedly the most tedious, time-consuming, and unstable. If the data source and target are both Oracle and meet certain conditions, you can use the oracle tablespace to improve ETL efficiency.To use a tablespace, the following conditi
often start from the data mart of a department, and then use several data marketplaces to form a complete data warehouse. Note that field definitions of the same meaning must be compatible when different data marketplaces are implemented, so that subsequent implementation o
from the data mart of a department, and then use several data marketplaces to form a complete data warehouse. Note that field definitions of the same meaning must be compatible when different data marketplaces are implemented, so that subsequent implementation of
often start from the data mart of a department, and then use several data marketplaces to form a complete data warehouse. Note that field definitions of the same meaning must be compatible when different data marketplaces are implemented, so that subsequent implementation o
or subject data (Subjectarea). In the process of data Warehouse implementation, it is often possible to start with a Department data mart and then make a complete data warehouse with several
As a data warehouse system, ETL is a key link. If it is big, ETL is a data integration solution. If it is small, it is a tool for data dumping. Recall that there have been a lot of data
Basic concepts: 1. Multi-dimensional dataset: a multi-dimensional dataset is the main object in Online Analytical Processing (OLAP) and a technology that allows quick access to data in a data warehouse. A multi-dimensional dataset is a collection of data. It is usually cons
This paper gives the basic concept of SQL Server Data Warehouse, and uses the example construction process to analyze, for everyone's reference! Basic concepts: 1. Cubes: Cubes are the primary object of online analytical processing (OLAP) and are a technology that allows fast access to data in a
I recently learned about BI, Because I mainly focus on data warehouse and learn about basic concepts first :) BISpecifically, BI is not a new technology. It uses technologies such as data warehouse (DW), Online Analytical Processing (OLAP), and
ETL: Abbreviation of extraction-transformation-loading. The Chinese name is data.Extract, convert, and load data. ETL extracts data from distributed and heterogeneous data sources, such as relational data and flat
During database management, extraction, conversion, and loading (ETL, extract, transform, and load) are three independent functions that constitute a simple editing task. First, read the data in the specified source database and extract the required sub-dataset. Then, the conversion function uses rules or drop-down lists to process the acquired data or create con
This article outlines the general process of using OWB to create a data warehouse. Oracle's OWB is one of the three most current ETL products. OWB can not only complete data extraction, conversion and loading, but also help users create ROLAP (relational online analysis Process) and MOLAP (multidimensional online) in O
The data increment extraction mechanism in ETL( Incremental extraction is an important consideration in the implementation of Data Warehouse ETL (extraction,transformation,loading, data extraction
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