PostgreSQL – AUTO INCREMENT
PostgreSQL has the data types smallserial, serial and bigserial; these are not true types, but merely a notational convenience for creating unique identifier columns. These are similar to AUTO_INCREMENT property supported by some other databases.
If you wish a serial column to have a unique constraint or be a primary key, it must now be specified, just like any other data type.
The type name serial creates an integer columns. The type name bigserial creates a bigint column. bigserial should be used if you anticipate the use of more than 231 identifiers over the lifetime of the table. The type name smallserial creates a smallint column.
The basic usage of SERIAL dataype is as follows −
CREATE TABLE tablename ( colname SERIAL );
Consider the COMPANY table to be created as follows −
testdb=# CREATE TABLE COMPANY( ID SERIAL PRIMARY KEY, NAME TEXT NOT NULL, AGE INT NOT NULL, ADDRESS CHAR(50), SALARY REAL );
Now, insert the following records into table COMPANY −
INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( 'Paul', 32, 'California', 20000.00 ); INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ('Allen', 25, 'Texas', 15000.00 ); INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ('Teddy', 23, 'Norway', 20000.00 ); INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( 'Mark', 25, 'Rich-Mond ', 65000.00 ); INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( 'David', 27, 'Texas', 85000.00 ); INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( 'Kim', 22, 'South-Hall', 45000.00 ); INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( 'James', 24, 'Houston', 10000.00 );
This will insert seven tuples into the table COMPANY and COMPANY will have the following records −
id | name | age | address | salary ----+-------+-----+------------+-------- 1 | Paul | 32 | California | 20000 2 | Allen | 25 | Texas | 15000 3 | Teddy | 23 | Norway | 20000 4 | Mark | 25 | Rich-Mond | 65000 5 | David | 27 | Texas | 85000 6 | Kim | 22 | South-Hall | 45000 7 | James | 24 | Houston | 10000
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
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