Using the Redis list data structure to execute SQL statements in bulk

There are now more than 3,000 such records in the database, each with a regional Chinese name and a regional English name (e.g.)

I now want to implement batch update with Redis queue Lpush and rpop, SQL statements I have already written (for example)

Code I write this way (for example), I put more than 3,000 SQL statements into the list (Lpush), ready to take out each time a execution (Rpop), one-by-step, then do not know how to write, ask everyone how to write, now has put SQL statements in the list And I see the value of the list under the CLI, Chinese seems to have garbled (for example), I started the CLI added--raw, please answer

Thank you, everyone.

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There are now more than 3,000 such records in the database, each with a regional Chinese name and a regional English name (e.g.)

I now want to implement batch update with Redis queue Lpush and rpop, SQL statements I have already written (for example)

Code I write this way (for example), I put more than 3,000 SQL statements into the list (Lpush), ready to take out each time a execution (Rpop), one-by-step, then do not know how to write, ask everyone how to write, now has put SQL statements in the list And I see the value of the list under the CLI, Chinese seems to have garbled (for example), I started the CLI added--raw, please answer

Thank you, everyone.

Xie invited
In fact, without Redis, you put all the SQL in a file, read one to execute one, not just?

function getSql(){    $fp = fopen('sql.txt', 'r');    while (!feof($fp)) {        yield fgets($fp);    }}foreach (getSql() as $sql) {    executeSql($sql);}function executeSql(){    //执行语句}

insert into base_region(region_name, en_name) values('中国','Zhongguo'), ('北京', 'Beijing'),...,('上海', 'Shanghai') on duplicate key update en_name = values(en_name);

A very small cost of SQL is done (a database connection, performance is similar to bulk INSERT into data).

There are two points to note:

1. VALUES (), (), (), () are required to be spliced with the for loop.

2. Region_name must be a unique index, you can temporarily add a unique index to this field, and then after this SQL execution is finished, drop

