AmazonRedshift
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Amazon Redshift is a data warehousing tool developed by Amazon that allows for storing and analyzing large amounts of data. It uses a columnar data storage model and massively parallel processing to enable extremely fast queries. Redshift can be easily accessed through a web service API and supports standard SQL syntax. It is a cloud-based solution that provides high security and scalability for analytical workloads.
AmazonRedshift
- 1. Amazon Redshift ~ Ahasan Habib Technical Project Manager, Ixora Solution Dhaka, Bangladesh
- 2. Data warehouse concept What is Data warehouse? ● Relational database ● Query & analysis ● Transaction processing data => Historical data ● Transaction workload => Analysis work load ● Extract, Transform, Load
- 4. Big Data So large and complex traditional data processing applications are not adequate characteristics: ● Volume: The amount or quality of data. ● Velocity The rate at which data is created. ● Variety The different types of data.
- 6. Operational Data ● Transactional data. ● Event data. ● Realtime data ● Helps to run day to day system/business operation.
- 7. Analytical Data ● Historical data ● Numerical values, measure, matrix (numerical measurement) ● Business intelligence & decision making
- 8. Rows Vs Columnar Database
- 9. What is Redshift ? ● A data warehouse management tool. ● Develop and manage by Amazon. ● Cloud hosted large data management system. ● Distributed data management system. ● Columnar data storage.
- 10. Redshift Speciality 1. Extremely fast. 2. Web service API based communication. 3. Massive parallel processing. 4. Full ANSI SQL support. 5. Columnar database. 6. Learning is very easy.
- 11. Redshift Product History ● November 2012 Bita release ● Feb 14 2014 Initial release ● POSTGRESQL 8.0.2
- 13. Advantages using Redshift ● Extremly faster for analytical data processing. ● Support ANSI SQL syntax. ● Cloud based solution. ● Highly secured (context of data & system access)
- 14. Redshift data warehouse design 1. Start schema
- 16. 3. Denormalized Fact Table Customer Id Customer Name Customer Address State City Country Product Id Product Name Product Category Gross Sales Amount Net Sales Amount
- 17. Index and Constraints 1. Sort Key 2. Distribution Key 3. Primary-key/Foreign Key 4. Triggers
- 18. Data Types Data Type Alias Description SMALLINT INT2 Signed 2 byte INTEGER INT4 Signed 4 byte BIGINT INT8 Signed 8 byte DECIMAL NUMERIC Selectable precision REAL, Double Precision Float4, Float8 Single, Double Precision (32,64) CHAR CHARACTER,NCHAR Fixed Length (4096) VARCHAR NVARCHAR, TEXT Variable Length (65535) DATE, TIMESTAMP Calendar Date, Date & Time (UTC) BOOLEAN BOOL True/False
- 19. Data Loading ● S3 ● COPY command ● Data Pipeline
- 20. Query ● CRUD ● Dynamic query ● Metadata Query ● Query execution Plan
- 21. Other database objects ● Built in Function ● User defined Function ● Stored Procedures ● Transactions
- 22. Security ● User Management ● Role Management ● Schema Management
- 23. Client Development Tools ● Navicat ● SQL Server Management Studio ● Various Drivers: Linux Visual Studio Scala Python
- 24. Q & A