liprais

select * from orders a join users b on a.p_user = b.PK;
select * from paymenttransactions a join orders b on a.p_order = b.pk;
select * from paymentmodes a join orders b on a.PK = b.p_paymentmode;
select * from orderentries a join orders b on a.p_order = b.pk;
select * from products a join orderentries b on a.PK = b.p_product;
select * from subentries a join guestinfos b on a.p_guestinfo = b.PK;
select * from subentries a join orderentries b on a.p_entry = b.PK;
select * from rules a join promotion p on a.p_code = p.p_code;

liprais

0.
基于tf2.0
1.
把已有的模型导出成pb格式
保存的时候的INFO:tensorflow:Unsupported signature for serialization貌似不用管
python code:

import os
os.environ['TF_KERAS'] = '1'
import numpy as np

liprais

1.
把已有的模型导出成pb格式
保存的时候的INFO:tensorflow:Unsupported signature for serialization貌似不用管
python code:

import os
os.environ['TF_KERAS'] = '1'
import numpy as np
from bert4keras.backend import K as K
from bert4keras.models import build_transformer_model

liprais

require 'mysql2'

client = Mysql2::Client.new(:host => "localhost", :username => "root",:database => "test")

100.times do |i|
	str = "insert into money_test ( money) values (#{rand(100)})"
	p str
	client.query(str)
end

liprais

from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
data_type_map = {'StringType':'varchar(32672)',
				 'LongType':'bigint',
				 'IntegerType':'int',
				 'BooleanType':'boolean',
				 'DateType':'date',
				 'DoubleType':'double',
				 'TimestampType':'timestamp'
				}

liprais

#!/usr/bin/ruby


def birth
  dice = rand(100)
  return dice > 50 ? 1 : 0
end


### 生了男孩就不生了，生了女孩就一直生

liprais

create table test_history
(
  id int,
  prop VARCHAR(16)
);

INSERT into test_history values ( 1,'a');
INSERT into test_history values ( 2,'b');

create TABLE updated_test ( id int ,prop VARCHAR(16));