Django:随机查询慢-尽管优化

Question

我有一个构建API，它应该返回来自一个大型查询集的10个随机选择的结果。

我有以下4种型号：

class ScrapingOperation(models.Model):
    completed = models.BooleanField(default=False)
    (...)

    indexes = [
        models.Index(fields=['completed'], name='completed_idx'),
        models.Index(fields=['trusted'], name='trusted_idx'),
    ]

    @property
    def ads(self):
        """returns all ads linked to the searches of this operation"""
        return Ad.objects.filter(searches__in=self.searches.all())


class Search(models.Model):
    completed = models.BooleanField(default=False)
    scraping_operation = models.ForeignKey(
            ScrapingOperation,
            on_delete=models.CASCADE,
            related_name='searches'
    )
    (...)


class Ad(models.Model):
    searches = models.ManyToManyField('scraper.Search', related_name='ads')
    (...)


class Label(models.Model):
     value = models.Integerfield()
     linked_ad = models.OneToOneField(
         Ad, on_delete=models.CASCADE, related_name='labels'
     )

数据库中当前有400.000 + Ad对象，但平均每个ScrapingOperation有14000个Ad对象链接到它。我希望API从这些+/- 14000中返回10个随机结果，这些结果还没有一个链接的Label对象(每个操作最多只有几百个)

因此，必须从包含14.000个对象的查询中返回10个随机结果。

早期版本只能返回一个结果，但使用的sort_by('?')方法要慢得多。当我不得不放大它来返回随机的10个Ad对象时，我使用了一种基于this stackoverflow answer的新方法。

下面是选择(并返回)10个随机对象的代码：

# Get all ads linked to the last completed operation
last_op_ads = ScrapingOperation.objects.filter(completed=True).last().ads

# Get all ads that don't have an label yet
random_ads = last_op_ads.filter(labels__isnull=True)

# Get list ids of all potential ads
id_list = random_ads.values_list('id', flat=True)
id_list = list(id_list)

# Select a random sample of 10, get objects with PK matches
samples = rd.sample(id_list, min(len(id_list), 10))
selected_samples = random_ads.filter(id__in=samples)

return selected_samples

然而，尽管我优化了这个查询，但是这个查询需要10+几秒钟才能完成，从而创建了一个非常慢的API。

这种长延迟仅仅是随机查询所固有的吗？(如果是的话，其他程序员如何处理这一限制？)或者我的代码中是否有我遗漏的错误/低效率？

编辑:基于响应，我在下面包含了原始sql查询(注意:这些查询在本地环境上运行，只包含生产环境中包含的数据的5% )。

{'sql': 'SELECT "scraper_scrapingoperation"."id", 
"scraper_scrapingoperation"."date_started", 
"scraper_scrapingoperation"."date_completed",
"scraper_scrapingoperation"."completed", 
"scraper_scrapingoperation"."round", 
"scraper_scrapingoperation"."trusted" FROM "scraper_scrapingoperation" 
WHERE "scraper_scrapingoperation"."completed" = true ORDER BY 
"scraper_scrapingoperation"."id" DESC LIMIT 1', 'time': '0.001'}


{'sql': 'SELECT "database_ad"."id" FROM "database_ad" INNER JOIN 
"database_ad_searches" ON ("database_ad"."id" = 
"database_ad_searches"."ad_id") LEFT OUTER JOIN "classifier_label" ON
("database_ad"."id" = "classifier_label"."ad_id") WHERE 
("database_ad_searches"."search_id" IN (SELECT U0."id" FROM 
"scraper_search" U0 WHERE U0."scraping_operation_id" = 6) AND 
"classifier_label"."id" IS NULL)', 'time': '1.677'}

编辑2:我尝试了另一种方法，使用更深层次的参数

        random_ads = ScrapingOperation.objects.prefetch_related(
            'searches__ads__labels',
        ).filter(completed=True).last().ads.exclude(
            labels__isnull=True
        )

        id_list = random_ads.values_list('id', flat=True)
        id_list = list(id_list)

        samples = rd.sample(id_list, min(
            len(id_list), 10))

        selected_samples = random_ads.filter(
            id__in=samples)

        return selected_samples

它生成以下SQL查询：

{'time': '0.008', 'sql': 'SELECT "scraper_search"."id", 
"scraper_search"."item_id", "scraper_search"."date_started", 
"scraper_search"."date_completed", "scraper_search"."completed", 
"scraper_search"."round", "scraper_search"."scraping_operation_id", 
"scraper_search"."trusted" FROM "scraper_search" WHERE 
"scraper_search"."scraping_operation_id" IN (6)'}


 {'time': '0.113', 'sql': 'SELECT ("database_ad_searches"."search_id")
 AS "_prefetch_related_val_search_id", "database_ad"."id", 
 "database_ad"."item_id", "database_ad"."item_state", 
 "database_ad"."title", "database_ad"."seller_id", 
 "database_ad"."url", "database_ad"."price", 
 "database_ad"."transaction_type", "database_ad"."transaction_method",
 "database_ad"."first_seen", "database_ad"."last_seen", 
 "database_ad"."promoted" FROM "database_ad" INNER JOIN 
 "database_ad_searches" ON ("database_ad"."id" = 
 "database_ad_searches"."ad_id") WHERE 
 "database_ad_searches"."search_id" IN (130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160)'}


{'time': '0.041', 'sql': 'SELECT "classifier_label"."id", 
"classifier_label"."set_by_id", "classifier_label"."ad_id", 
"classifier_label"."date", "classifier_label"."phone_type", 
"classifier_label"."seller_type", "classifier_label"."sale_type" FROM
"classifier_label" WHERE "classifier_label"."ad_id" IN (1, 3, 6, 10, 20, 29, 30, 35, 43, (and MANY more of these numbers) ....'}



{'time': '1.498', 'sql': 'SELECT "database_ad"."id" FROM "database_ad"
INNER JOIN "database_ad_searches" ON ("database_ad"."id" = "database_ad_searches"."ad_id") LEFT OUTER JOIN "classifier_label" ON 
("database_ad"."id" = "classifier_label"."ad_id") WHERE 
("database_ad_searches"."search_id" IN (SELECT U0."id" FROM
"scraper_search" U0 WHERE U0."scraping_operation_id" = 6) AND NOT 
("classifier_label"."id" IS NOT NULL))'}

每个ScrapingOperation 'only‘都有+/- 14000链接广告，但是生产中的广告总数是400.000 (而且还在增长)。上面的所有代码都在我的本地环境中返回有效的结果(只包含5%的数据)，但是在生产中返回API上的502个错误。

Answer 1

我会尝试先隔离链接广告，然后使用一个生成的随机列的顺序从它们中得到10个随机的广告。我不确定这在生成的sql中如何有效。当然，我更喜欢在任务上创建一个存储过程，因为这是明确的数据挖掘操作，其结果是随机样本。