Empire Big Data Project Notes

No. 2022.10.6

1. Create an aggregation table, the pioneer of big data!

Create aggregate tables, three:

CREATE TABLE `i9j_cn`.`phome_book_1` ( `id` INT(10) NOT NULL AUTO_INCREMENT COMMENT 'id' , `book` VARCHAR(255) NOT NULL COMMENT '本页聚合名' , `pageid` VARCHAR(255) NOT NULL COMMENT '关联的文章id' , `bookerid` INT(10) NOT NULL COMMENT '作者id' , `bookurl` VARCHAR(100) NOT NULL COMMENT '本页的链接' , `description` VARCHAR(255) NOT NULL COMMENT '本页的描述' , `bookerurl` VARCHAR(100) NOT NULL COMMENT '作者链接' , PRIMARY KEY (`id`), UNIQUE `book` (`book`)) ENGINE = InnoDB;
CREATE TABLE `i9j_cn`.`phome_book_2` ( `id` INT(10) NOT NULL AUTO_INCREMENT COMMENT 'id' , `book` VARCHAR(255) NOT NULL COMMENT '本页聚合名' , `pageid` VARCHAR(255) NOT NULL COMMENT '关联的文章id' , `bookerid` INT(10) NOT NULL COMMENT '作者id' , `bookurl` VARCHAR(100) NOT NULL COMMENT '本页的链接' , `description` VARCHAR(255) NOT NULL COMMENT '本页的描述' , `bookerurl` VARCHAR(100) NOT NULL COMMENT '作者链接' , PRIMARY KEY (`id`), UNIQUE `book` (`book`)) ENGINE = InnoDB;
CREATE TABLE `i9j_cn`.`phome_book_3` ( `id` INT(10) NOT NULL AUTO_INCREMENT COMMENT 'id' , `book` VARCHAR(255) NOT NULL COMMENT '本页聚合名' , `pageid` VARCHAR(255) NOT NULL COMMENT '关联的文章id' , `bookerid` INT(10) NOT NULL COMMENT '作者id' , `bookurl` VARCHAR(100) NOT NULL COMMENT '本页的链接' , `description` VARCHAR(255) NOT NULL COMMENT '本页的描述' , `bookerurl` VARCHAR(100) NOT NULL COMMENT '作者链接' , PRIMARY KEY (`id`), UNIQUE `book` (`book`)) ENGINE = InnoDB;

Create an author table, build it yourself, divided into four fields: id, author, author link, work id collection

2. Import the prepared author data
Previously, 1.5 million pieces of unique data have been collected into another data table.
So I exported the previous data table and put it in the database of the current project.