etl example

requirements. For example, the caller ID is 861082585313-8148. The domain code and telephone number can be decomposed. To verify data correctness, you can use the lookup and splitting functions to verify data correctness. For example, if the caller ID is 861082585313-8148, after the domain code and phone number are decomposed, you can use lookup to return to the caller's region recorded by the gateway or

volume is usually huge. It is worth splitting the data flow process into E, T, and L. There are many mature tools that provide ETL functions, such as datastage and powermart. From the application perspective, the ETL process is not very complex. These tools bring great convenience to the Data Warehouse project, especially the convenience of development and maintenance. On the other hand, developers are eas

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 data from the source to the target. ETL is commonly used in data warehouses, but its objects are not l

concepts:Fundamentally solved the dilemma of "Difficult Process Monitoring expression" in ETL scheduling products in the current market!It is a database-free product. from the perspective of deployment practice, it is very convenient. this reduces the difficulty of deploying the runtime environment (in some ETL scheduling products, it is also annoying to deploy the runtime environment)The process "programm

of directly performing ETL without data being implemented. For example, in the data extraction stage, we need to connect to the source system. To minimize the impact on the source system, we need to save the extracted data as a text file or put it into a table in the data preparation area, in this way, when the ETL process fails due to an error, we can start

the amount of data, which is generally huge, and it is worthwhile to split the process of data flow into E, T, and L. Now there are many mature tools to provide ETL functions, such as DataStage, Powermart, etc., and do not say they are good or bad. From the application point of view, the ETL process is not very complex, these tools to the Data Warehouse engineering and great convenience, especially the dev

The main indexes of this series of articles are as follows: I. ETL Tool kettle Application Analysis Series I [Kettle Introduction] Ii. ETL Tool kettle Practical Application Analysis Series 2 [application scenarios and demo downloads] Iii. ETL Tool kettle Practical Application Analysis Series III [ETL background process

ETL scheduling development (5) -- connect to the database to execute database command subroutines and etl Scheduling In ETL scheduling, you need to connect to the database to read and write data. The following subprograms use the input database connection string and database commands (or SQL) to perform the required operations: #!/usr/bin/bash#created by lubinsu

ETL (extract-transform-load abbreviation, that is, data extraction, transformation, loading process), for enterprise or industry applications, we often encounter a variety of data processing, conversion, migration, so understand and master the use of an ETL tool, essential, Here I introduce a I used in the work of 3 years of ETL tools kettle, the spirit of good t

is more efficient than the where statement after the index is established 4, replacement/partial replacement of text strings, operating system level than the database more efficient 5, aggregation. In the ETL data stream before the data is loaded into the database, or if the aggregated data is only available through database filtering, it is done in the database. If aggregations are completed outside the database, specialized sorting packages are oft

different periods of the Business System; inconsistency of the old system module in operations, personnel, finance, office systems, and other related information;Inconsistency resulting from incomplete integration of new systems, services, and management systems. To implement ETL, you must first implement the ETL conversion process. It can be embodied in the following aspects: Null Value processing can cap

Etl tool, kettle implementation loop, etl Tool kettle implementation Kettle is an open-source ETL Tool written in java. It can be run on Windows, Linux, and Unix. It does not need to be installed green, and data extraction is efficient and stable. Business Model: there is a large data storage table in the relational database, which is designed as a parity datab

process of data flow, from different data sources to different target data. But in the Data Warehouse, ETL has several characteristics, One is the data synchronization, it is not a one-time rewind data to pull to, it is a regular activity, in accordance with the fixed cycle of operation, and even now some people put forward the concept of the Realtime ETL. Two is the amount of data, which is generally hug

extraction requirements, on the source table to be extracted to insert, modify, delete 3 triggers, whenever the data in the source table changes, the corresponding trigger will change the data to a Delta log table, ETL incremental extraction is from the Delta Log table instead of directly in the source table to extract data, At the same time, the extracted data in the Delta Log table is marked or deleted in time.For simplicity, the incremental log ta

maintenance. Flexible SQL code. If the developer's coding level is excellent, the data processing efficiency is high. In my personal opinion, let's just summarize some things from previous work.Etl and SQL are completely different,Etl is just like its name. Of course, you can also say that elt is calling and cleaning the loading process. Of course, you can also say that I can directly create it using SQL,

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 connections with other data, so that it can be converted to the desired state. Finally, we us

a large quantity. You should consider separating the insert, update, and delete processes. 7. Detects database I/O to load data. If there are no problems with the previous sections, the final need to detect is the performance issue of the target database. You can find a file to replace the database, if the performance increased a lot, you need to carefully detect the target database in the load process operations. For example, whether all the constra

. Data Conversion Data conversion tasks mainly perform inconsistent data conversion, data granularity conversion, and calculation of some business rules.A. inconsistent data conversion. This process is an integrated process that unifies the data of the same type in different business systems. For example, the Code of the settlement system of the same supplier is xx0001, in CRM, the encoding is yy0001, which is converted into an encoding after extract

, the ETL process needs to be repeated and maintained and improved continuously. 1.3 purpose of standardized formulation: ETL specifications are some rules and methods defined to ensure the correct design, implementation and maintenance of ETL, including ETL design specifications, development specifications, and mainte

For the Data warehouse and ETL knowledge, I am basically a layman. Everything has to start from scratch, take a note, to facilitate the understanding of learning progress.First, let's take a look at the basic definition:Well, some people also called the ETL simple data extraction. At least before the study, the leader told me that you need to do a data extraction tool.In fact, extraction is the key part of