本文主要是介绍计算机毕业设计hadoop+spark+hive物流快递大数据分析平台 物流预测系统 物流信息爬虫 物流大数据 机器学习 深度学习 知识图谱 大数据，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
1.Python爬虫采集物流数据等存入mysql和.csv文件；
2.使用pandas+numpy或者MapReduce对上面的数据集进行数据清洗生成最终上传到hdfs；
3.使用hive数据仓库完成建库建表导入.csv数据集；
4.使用hive之hive_sql进行离线计算，使用spark之scala进行实时计算；
5.将计算指标使用sqoop工具导入mysql；
6.使用Flask+echarts进行可视化大屏实现、数据查询表格实现、含预测算法；
核心算法代码分享如下：
from flask import Flask, request
import json
from flask_mysqldb import MySQL# 创建应用对象
app = Flask(__name__)
app.config['MYSQL_HOST'] = 'bigdata'
app.config['MYSQL_USER'] = 'root'
app.config['MYSQL_PASSWORD'] = '123456'
app.config['MYSQL_DB'] = '2408_meituan'
mysql = MySQL(app) # this is the instantiation@app.route('/tables01')
def tables01():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table01''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['name','goods','bads'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables02')
def tables02():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table02''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['name','price'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables03')
def tables03():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table03 order by goods desc limit 5''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['type','goods'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables04')
def tables04():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table04''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['shop_name','goods'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables05')
def tables05():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table05''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['shop_name','bads'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables06')
def tables06():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table06''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['addr','num'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables07')
def tables07():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table07''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['dish','num'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables08')
def tables08():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table08 order by serv_score desc limit 5''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['shop_name','serv_score'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)@app.route('/tables09')
def tables09():cur = mysql.connection.cursor()cur.execute('''SELECT * FROM table09''')#row_headers = [x[0] for x in cur.description] # this will extract row headersrow_headers = ['name','nums'] # this will extract row headersrv = cur.fetchall()json_data = []#print(json_data)for result in rv:json_data.append(dict(zip(row_headers, result)))return json.dumps(json_data, ensure_ascii=False)if __name__ == "__main__":app.run(debug=True)
这篇关于计算机毕业设计hadoop+spark+hive物流快递大数据分析平台 物流预测系统 物流信息爬虫 物流大数据 机器学习 深度学习 知识图谱 大数据的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！
