Question

我真的难以接受一个问题。在我的网站上，无论何时平移地图，都会触发AJAX调用，在数据库中执行查询。问题是，AJAX调用需要2-10秒，这是不可接受的。

我的数据库中有大约500,000条记录。我注意到我添加的记录越多，它就越慢。这是正确的，但为什么它特别缓慢且如此不一致？

我正在使用Digital Ocean。当我检查控制面板时，CPU / RAM /磁盘都运行在非常低的水平。

AJAX呼叫代码：

def filter_closed_listings(request):
    zoom = int(request.GET.get('zoomLevel'))
    minLat = request.GET.get('minLat')
    maxLat = request.GET.get('maxLat')
    minLng = request.GET.get('minLng')
    maxLng = request.GET.get('maxLng')

    sold = request.GET.get('sold')
    property_type = request.GET.get('pType')
    building_style = request.GET.get('bType')
    showActiveListings = request.GET.get('showActiveListings')
    showSoldListings = request.GET.get('showSoldListings')
    showEndedListings = request.GET.get('showEndedListings')
    bed = request.GET.get('bed')
    bath = request.GET.get('bath')
    low_price = request.GET.get('low')
    high_price = request.GET.get('high')
    includePandL = request.GET.get('includePandL')
    transaction_type = request.GET.get('transactionType')

    ended_time_difference = datetime.date.today() + datetime.timedelta(-int(sold)) # Date check
    print(ended_time_difference)
    # Initial filter with map bounds and date check
    data = Listing.objects.filter(la__gt=minLat).filter(la__lt=maxLat).filter(lo__gt=minLng).filter(lo__lt=maxLng)

    data = data.filter(transaction_type=transaction_type)

    # 0 is 'Any'.  Therefore a filter is done if selection is not 'Any'.
    if not property_type == '0':
        if property_type == '1':
            data = data.filter(Q(property_type='Condo Apt') | Q(property_type='Comm Element Condo'))
        elif property_type == '2':
            data = data.filter(property_type='Detached')
        elif property_type == '3':
            data = data.filter(property_type='Semi-Detached')
        elif property_type == '4':
            data = data.filter(Q(property_type='Att/Row/Twnhouse') | Q(property_type='Condo Townhouse'))
        else:
            data = data.exclude(Q(property_type='Condo Apt') | Q(property_type='Comm Element Condo') | Q(property_type='Detached') | Q(property_type='Semi-Detached') | Q(property_type='Att/Row/Twnhouse') | Q(property_type='Condo Townhouse'))

    if showActiveListings == 'n':
        data = data.filter(Q(status='Ter') | Q(status='Exp') | Q(status='Sld') | Q(status='Lsd'))

    if showSoldListings == 'n':
        if transaction_type == 'Sale':
            data = data.exclude(status='Sld')
        else:
            data = data.exclude(status='Lsd')
    else:
        if transaction_type == 'Sale':
            data = data.exclude(Q(status='Sld') & Q(sold_date__lt=ended_time_difference))
        else:
            data = data.exclude(Q(status='Lsd') & Q(sold_date__lt=ended_time_difference))

    if showEndedListings == 'n':
        data = data.exclude(Q(status='Ter') | Q(status='Exp'))
    else:
        data = data.exclude(Q(status='Exp') & Q(expiry_date__lt=ended_time_difference)).exclude(Q(status='Ter') & Q(terminated_date__lt=ended_time_difference))

    if includePandL == 'false':
        data = data.exclude(Q(property_type='Parking Space') | Q(property_type='Locker'))
    # Bedrooms check
    if not bed == 'undefined':
        bed = bed.split(',')

        queries = [Q(bedrooms_ag=b) for b in bed]
        query = queries.pop()
        if bed.pop() == '6':
            query = Q(bedrooms_ag__gte=5)
        for i in queries:
            query |= i
        #print(query)
        data = data.filter(query)

    # Bathrooms check
    if not bath == 'undefined':
        bath = bath.split(',')

        queries = [Q(washrooms=b) for b in bath]
        query = queries.pop()
        if bath.pop() == '6':
            query = Q(washrooms__gte=5)
        for i in queries:
            query |= i
        #print(query)
        data = data.filter(query)

    # Filters low price and high price
    if high_price == '0' and low_price == '0':
        pass
    elif high_price =='0':
        data = data.filter(Q(Q(list_price__gte=low_price) & Q(list_price__lte=999999999) & Q(sold_price__isnull=True)) | Q(Q(sold_price__gte=low_price) & Q(sold_price__lte=999999999) & Q(sold_price__isnull=False))) # Nested Q object.  Use list price if sold price is null.
    else:
        data = data.filter(Q(Q(list_price__gte=low_price) & Q(list_price__lte=high_price) & Q(sold_price__isnull=True)) | Q(Q(sold_price__gte=low_price) & Q(sold_price__lte=high_price) & Q(sold_price__isnull=False)))

    if data.count() > 500:
        return JsonResponse({'over500': True})
    data = data.values('id', 'la', 'lo')
    # Determines lat/lng precision based on zoom level
    for i in data:
        if zoom >= 13:
            i['lo'] = round(i['lo'], 4)
            i['la'] = round(i['la'], 4)
        elif zoom > 9 and zoom < 13:
            i['lo'] = round(i['lo'], 2)
            i['la'] = round(i['la'], 2)
        else:
            i['lo'] = round(i['lo'], 1)
            i['la'] = round(i['la'], 1)



    return JsonResponse({'results': list(data)}) # This uses list() which is bad design.  But only 3 fields are passed and highly unlikely to change so this can stay like this.

AJAX通话需要很长时间（2-4秒）

0 个答案: