Population mobility comprehensive data monitoring system based on Hadoop

1. Project introduction

1. Background

With the development of society and the advancement of science and technology, the phenomenon of population mobility has become more complex and frequent. Effectively managing and monitoring population mobility is of great significance to urban planning, resource allocation, public safety and other aspects. However, traditional population flow data collection and analysis methods can no longer meet the needs of large-scale and complex data processing. Therefore, it is imperative to develop a comprehensive data monitoring system for population mobility based on Hadoop.

2. Problems with existing solutions

Although some population mobility data monitoring systems currently exist, they face the following problems:

Incomplete data collection: Existing systems often only collect partial data and cannot cover all population mobility information.
Low data processing efficiency: In the face of massive data, the existing system has limited data processing capabilities and cannot provide analysis results in a timely and accurate manner.
Insufficient real-time monitoring capabilities: For real-time changes in population mobility, the existing system cannot achieve real-time monitoring and early warning.

3. The significance of this topic

This topic aims to develop a comprehensive data monitoring system for population mobility based on Hadoop to solve the problems of existing solutions. Through the research on this topic, we will achieve the following goals:

Comprehensive collection of population mobility data: Collect and integrate population mobility data from various sources through Hadoop's big data storage and processing capabilities.
Improve data processing efficiency: Use Hadoop's efficient parallel processing mechanism to process and analyze large-scale data quickly and accurately.
Real-time monitoring and early warning: Through real-time data stream processing technology, the population flow status is monitored, abnormal situations are discovered in a timely manner and early warnings are issued.

Through the research on this topic, we will provide more comprehensive, accurate and real-time data support for urban management, resource allocation, public safety and other fields, which will help improve the scientific nature and effectiveness of decision-making. At the same time, the research results of this topic also have extensive promotion and application value, and have important reference significance for complex data processing problems in other similar fields.

2. Development environment

• Big data technology: Hadoop, Spark, Hive
• Development technology: Python, Django framework, Vue, Echarts
• Software tools: Pycharm, DataGrip, Anaconda, VM virtual machine

3. Project presentation-Population flow comprehensive data monitoring system based on Hadoop

4. Code display

 public ServerResponseEntity<IPage<MyOrderDto>> myOrder(@RequestParam(value = "status") Integer status, PageParam<MyOrderDto> page) {<!-- -->
        String userId = SecurityUtils.getUser().getUserId();
        IPage<MyOrderDto> myOrderDtoIpage = myOrderService.pageMyOrderByUserIdAndStatus(page, userId, status);
        return ServerResponseEntity.success(myOrderDtoIpage);
    }

    /**
     * cancel order
     */
    @PutMapping("/cancel/{orderNumber}")
    @Operation(summary = "Cancel order based on order number", description = "Cancel order based on order number")
    @Parameter(name = "orderNumber", description = "Order Number", required = true)
    public ServerResponseEntity<String> cancel(@PathVariable("orderNumber") String orderNumber) {<!-- -->
        String userId = SecurityUtils.getUser().getUserId();
        Order order = orderService.getOrderByOrderNumber(orderNumber);
        if (!Objects.equals(order.getUserId(), userId)) {<!-- -->
            throw new YamiShopBindException("You do not have permission to obtain the order information");
        }
        if (!Objects.equals(order.getStatus(), OrderStatus.UNPAY.value())) {<!-- -->
            throw new YamiShopBindException("The order has been paid and the order cannot be canceled");
        }
        List<OrderItem> orderItems = orderItemService.getOrderItemsByOrderNumber(orderNumber);
        order.setOrderItems(orderItems);
        // cancel order
        orderService.cancelOrders(Collections.singletonList(order));

        // clear cache
        for (OrderItem orderItem : orderItems) {<!-- -->
            productService.removeProductCacheByProdId(orderItem.getProdId());
            skuService.removeSkuCacheBySkuId(orderItem.getSkuId(), orderItem.getProdId());
        }
        return ServerResponseEntity.success();
    }


    /**
     * confirm the receipt of goods
     */
    @PutMapping("/receipt/{orderNumber}")
    @Operation(summary = "Confirm receipt according to order number", description = "Confirm receipt according to order number")
    public ServerResponseEntity<String> receipt(@PathVariable("orderNumber") String orderNumber) {<!-- -->
        String userId = SecurityUtils.getUser().getUserId();
        Order order = orderService.getOrderByOrderNumber(orderNumber);
        if (!Objects.equals(order.getUserId(), userId)) {<!-- -->
            throw new YamiShopBindException("You do not have permission to obtain the order information");
        }
        if (!Objects.equals(order.getStatus(), OrderStatus.CONSIGNMENT.value())) {<!-- -->
            throw new YamiShopBindException("The order has not been shipped and the receipt cannot be confirmed");
        }
        List<OrderItem> orderItems = orderItemService.getOrderItemsByOrderNumber(orderNumber);
        order.setOrderItems(orderItems);
        // confirm the receipt of goods
        orderService.confirmOrder(Collections.singletonList(order));

        for (OrderItem orderItem : orderItems) {<!-- -->
            productService.removeProductCacheByProdId(orderItem.getProdId());
            skuService.removeSkuCacheBySkuId(orderItem.getSkuId(), orderItem.getProdId());
        }
        return ServerResponseEntity.success();
    }

    /**
     * Delete order
     */
    @DeleteMapping("/{orderNumber}")
    @Operation(summary = "Delete order based on order number", description = "Delete order based on order number")
    @Parameter(name = "orderNumber", description = "Order Number", required = true)
    public ServerResponseEntity<String> delete(@PathVariable("orderNumber") String orderNumber) {<!-- -->
        String userId = SecurityUtils.getUser().getUserId();

        Order order = orderService.getOrderByOrderNumber(orderNumber);
        if (order == null) {<!-- -->
            throw new YamiShopBindException("The order does not exist");
        }
        if (!Objects.equals(order.getUserId(), userId)) {<!-- -->
            throw new YamiShopBindException("You do not have permission to obtain the order information");
        }
        if (!Objects.equals(order.getStatus(), OrderStatus.SUCCESS.value()) & amp; & amp; !Objects.equals(order.getStatus(), OrderStatus.CLOSE.value())) {<! -- -->
            throw new YamiShopBindException("The order is not completed or closed, and the order cannot be deleted");
        }

        // Delete order
        orderService.deleteOrders(Collections.singletonList(order));

        return ServerResponseEntity.success("Deletion successful");
    }

    /**
     * Get my order quantity
     */
    @GetMapping("/orderCount")
    @Operation(summary = "Get my order quantity", description = "Get my order quantity")
    public ServerResponseEntity<OrderCountData> getOrderCount() {<!-- -->
        String userId = SecurityUtils.getUser().getUserId();
        OrderCountData orderCountMap = orderService.getOrderCount(userId);
        return ServerResponseEntity.success(orderCountMap);
    }


}

5. Project Summary

Through in-depth exploration and practice of a population mobility comprehensive data monitoring system based on Hadoop, this study clarifies the advantages and value of this system in processing large-scale population mobility data. In view of the shortcomings of traditional population mobility data collection and analysis methods, this study achieved comprehensive collection, efficient processing and real-time monitoring of various population mobility data by introducing Hadoop technology.

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