Question

我有以下查询

engagement_metrics = EngagementMetric.where(engagement_id: engagement_ids).order('metrics_date desc').limit(7).group_by { |p| p.metrics_date }

会产生类似这样的内容

{
    "2016-05-13": [
        {
            "id": 4,
            "provider": "facebook",
            "likes": -2,
            "comments": 0,
            "shares": 0,
            "views": 0,
            "reach": 0,
            "reactions": {
                "sad_count": "0",
                "wow_count": "-1",
                "haha_count": "0",
                "like_count": "-1",
                "love_count": "0",
                "angry_count": "0"
            }
        },
        {
            "id": 5,
            "provider": "facebook",
            "likes": 2,
            "comments": 2,
            "shares": 2,
            "views": 2,
            "reach": 0,
            "reactions": {
                "sad_count": "0",
                "wow_count": "0",
                "haha_count": "0",
                "like_count": "0",
                "love_count": "0",
                "angry_count": "0"
            }
        }
    ],
    "2016-05-12": [
        {
            "id": 3,
            "provider": "facebook",
            "likes": 1,
            "comments": 3,
            "shares": 0,
            "views": 0,
            "reach": 0,
            "reactions": {
                "sad_count": "1",
                "wow_count": "0",
                "haha_count": "0",
                "like_count": "0",
                "love_count": "0",
                "angry_count": "0"
            },
            "engagement_id": 1,
            "participation_id": 1,
            "campaign_id": 1,
            "influencer_authorization_id": 1,
            "influencer_id": 1,
            "social_account_id": 1,
            "metrics_date": "2016-05-12",
            "status": "processed",
            "deleted_at": null,
            "created_at": "2016-05-14T11:36:55.995Z",
            "updated_at": "2016-05-14T11:36:55.995Z"
        }
    ],
    "2016-05-11": [
        {
            "id": 2,
            "provider": "facebook",
            "likes": 0,
            "comments": 16,
            "shares": 0,
            "views": 0,
            "reach": 0,
            "reactions": {
                "sad_count": "0",
                "wow_count": "0",
                "haha_count": "0",
                "like_count": "0",
                "love_count": "0",
                "angry_count": "0"
            }
        }
    ],
    "2016-05-10": [
        {
            "id": 1,
            "provider": "facebook",
            "likes": 3,
            "comments": 4,
            "shares": 0,
            "views": 0,
            "reach": 0,
            "reactions": {
                "sad_count": "0",
                "wow_count": "1",
                "haha_count": "0",
                "like_count": "1",
                "love_count": "1",
                "angry_count": "0"
            }
        }
    ]
}

这是迭代获取如下数据的最佳方式

[
    {
        "date": "24/03/16",
        "metrics": {
            "likes_count": "29",
            "comments_count": "456",
            "shares_count": "234",
            "views_count": "65",
            "clicks_count": "123"
        }
    },
    {
        "date": "25/03/16",
        "metrics": {
            "likes_count": "345",
            "comments_count": "234",
            "shares_count": "876",
            "views_count": "345",
            "clicks_count": "45"
        }
    },
    {
        "date": "26/03/16",
        "metrics": {
            "likes_count": "345",
            "comments_count": "265",
            "shares_count": "243",
            "views_count": "165",
            "clicks_count": "87"
        }
    },
    {
        "date": "27/03/16",
        "metrics": {
            "likes_count": "376",
            "comments_count": "87",
            "shares_count": "54",
            "views_count": "754",
            "clicks_count": "34"
        }
    },
    {
        "date": "28/03/16",
        "metrics": {
            "likes_count": "103",
            "comments_count": "324",
            "shares_count": "405",
            "views_count": "87",
            "clicks_count": "354"
        }
    },
    {
        "date": "29/03/16",
        "metrics": {
            "likes_count": "23",
            "comments_count": "65",
            "shares_count": "234",
            "views_count": "87",
            "clicks_count": "34"
        }
    },
    {
        "date": "30/03/16",
        "metrics": {
            "likes_count": "98",
            "comments_count": "576",
            "shares_count": "34",
            "views_count": "365",
            "clicks_count": "212"
        }
    }
]

Answer 1

出于性能原因，您应该始终尽力在数据库中进行分组（使用return (int) players.stream() .filter(p -> p.level > average) .count();）而不是ruby代码（java -cp /path/to/my/jar/dependencies -jar file.jar com.package.of.my.main.class.MyMainClass "any arguments if any"）。我认为您可以使用自定义选择和分组检索您请求的内容，即给定列的每日总和：

java -jar file.jar

即。这将汇总每日组中的所有数据并返回结果。如果您希望在“metrics”子项下使用.appear（可以使用custom as_json method完成），您只需要构建一个不同的JSON。

ActiveRecord计算列的总和并将它们分组

1 个答案: