Python 是否在嵌套字典中添加缺少的键？

我有一本字典，用来根据数据库中的数据建立图表。 我有以下工作代码：

datasets = []

for row in data:
    # add serie if not exists already
    if not any(d['label'] == row['sql_id'] for d in datasets):
        serie = {'label':row['sql_id'],'backgroundColor':GetRandomHexColor(),'data':[]}
        datasets.append(serie)

    serie = next(item for item in datasets if item['label'] == row['sql_id'])
    serie['data'].append({'x': row['sample_time'],'y':row['resources_consumed']})

这将构建此表单的词汇表：

{
"datasets": [{
    "data": [{
        "y": 3,
        "x": "2017-12-22 16:01"
    }, {
        "y": 23,
        "x": "2017-12-22 16:02"
    }, {
        "y": 33,
        "x": "2017-12-22 16:03"
    }, {
        "y": 12,
        "x": "2017-12-22 16:04"
    }, {
        "y": 5,
        "x": "2017-12-22 16:05"
    }, {
        "y": 13,
        "x": "2017-12-22 16:06"
    }, {
        "y": 17,
        "x": "2017-12-22 16:11"
    }, {
        "y": 24,
        "x": "2017-12-22 16:12"
    }, {
        "y": 12,
        "x": "2017-12-22 16:13"
    }, {
        "y": 9,
        "x": "2017-12-22 16:14"
    }, {
        "y": 10,
        "x": "2017-12-22 16:15"
    }, {
        "y": 24,
        "x": "2017-12-22 16:16"
    }, {
        "y": 28,
        "x": "2017-12-22 16:17"
    }, {
        "y": 4,
        "x": "2017-12-22 16:18"
    }, {
        "y": 18,
        "x": "2017-12-22 16:19"
    }, {
        "y": 25,
        "x": "2017-12-22 16:20"
    }, {
        "y": 25,
        "x": "2017-12-22 16:21"
    }, {
        "y": 14,
        "x": "2017-12-22 16:22"
    }, {
        "y": 10,
        "x": "2017-12-22 16:23"
    }, {
        "y": 9,
        "x": "2017-12-22 16:24"
    }],
    "backgroundColor": "#01F79A",
    "label": "3qkhfbf2kyvhk"
}, {
    "data": [{
        "y": 3,
        "x": "2017-12-22 16:01"
    }, {
        "y": 14,
        "x": "2017-12-22 16:02"
    }, {
        "y": 12,
        "x": "2017-12-22 16:03"
    }, {
        "y": 9,
        "x": "2017-12-22 16:04"
    }, {
        "y": 7,
        "x": "2017-12-22 16:05"
    }, {
        "y": 20,
        "x": "2017-12-22 16:06"
    }, {
        "y": 2,
        "x": "2017-12-22 16:10"
    }, {
        "y": 16,
        "x": "2017-12-22 16:11"
    }, {
        "y": 10,
        "x": "2017-12-22 16:12"
    }, {
        "y": 11,
        "x": "2017-12-22 16:13"
    }, {
        "y": 9,
        "x": "2017-12-22 16:14"
    }, {
        "y": 15,
        "x": "2017-12-22 16:15"
    }, {
        "y": 13,
        "x": "2017-12-22 16:16"
    }, {
        "y": 8,
        "x": "2017-12-22 16:17"
    }, {
        "y": 8,
        "x": "2017-12-22 16:18"
    }, {
        "y": 12,
        "x": "2017-12-22 16:19"
    }, {
        "y": 14,
        "x": "2017-12-22 16:20"
    }, {
        "y": 13,
        "x": "2017-12-22 16:21"
    }, {
        "y": 12,
        "x": "2017-12-22 16:22"
    }, {
        "y": 9,
        "x": "2017-12-22 16:23"
    }, {
        "y": 8,
        "x": "2017-12-22 16:24"
    }],
    "backgroundColor": "#743967",
    "label": "8u125dk9nfc0q"
}, {
    "data": [{
        "y": 1,
        "x": "2017-12-22 16:02"
    }, {
        "y": 1,
        "x": "2017-12-22 16:03"
    }, {
        "y": 1,
        "x": "2017-12-22 16:04"
    }, {
        "y": 2,
        "x": "2017-12-22 16:11"
    }, {
        "y": 1,
        "x": "2017-12-22 16:12"
    }, {
        "y": 2,
        "x": "2017-12-22 16:15"
    }, {
        "y": 2,
        "x": "2017-12-22 16:16"
    }, {
        "y": 1,
        "x": "2017-12-22 16:17"
    }, {
        "y": 2,
        "x": "2017-12-22 16:19"
    }, {
        "y": 1,
        "x": "2017-12-22 16:20"
    }, {
        "y": 1,
        "x": "2017-12-22 16:22"
    }, {
        "y": 1,
        "x": "2017-12-22 16:24"
    }],
    "backgroundColor": "#CA3582",
    "label": "b9nbhsbx8tqz5"
}, {
    "data": [{
        "y": 1,
        "x": "2017-12-22 16:02"
    }, {
        "y": 1,
        "x": "2017-12-22 16:04"
    }, {
        "y": 2,
        "x": "2017-12-22 16:11"
    }, {
        "y": 1,
        "x": "2017-12-22 16:12"
    }, {
        "y": 1,
        "x": "2017-12-22 16:14"
    }, {
        "y": 2,
        "x": "2017-12-22 16:15"
    }, {
        "y": 1,
        "x": "2017-12-22 16:19"
    }, {
        "y": 2,
        "x": "2017-12-22 16:20"
    }, {
        "y": 1,
        "x": "2017-12-22 16:22"
    }, {
        "y": 1,
        "x": "2017-12-22 16:24"
    }],
    "backgroundColor": "#8697A2",
    "label": "dp0vgyb1hsfjb"
}, {
    "data": [{
        "y": 5,
        "x": "2017-12-22 16:04"
    }, {
        "y": 4,
        "x": "2017-12-22 16:05"
    }, {
        "y": 8,
        "x": "2017-12-22 16:13"
    }, {
        "y": 1,
        "x": "2017-12-22 16:14"
    }, {
        "y": 9,
        "x": "2017-12-22 16:18"
    }, {
        "y": 8,
        "x": "2017-12-22 16:22"
    }, {
        "y": 1,
        "x": "2017-12-22 16:23"
    }],
    "backgroundColor": "#034D27",
    "label": "7726bj0dhtnmt"
}, {
    "data": [{
        "y": 12,
        "x": "2017-12-22 16:04"
    }, {
        "y": 12,
        "x": "2017-12-22 16:13"
    }, {
        "y": 12,
        "x": "2017-12-22 16:18"
    }, {
        "y": 10,
        "x": "2017-12-22 16:22"
    }],
    "backgroundColor": "#B3FDF5",
    "label": "cmx7t67z8wa74"
}, {
    "data": [{
        "y": 2,
        "x": "2017-12-22 16:04"
    }, {
        "y": 1,
        "x": "2017-12-22 16:05"
    }, {
        "y": 4,
        "x": "2017-12-22 16:12"
    }, {
        "y": 1,
        "x": "2017-12-22 16:15"
    }, {
        "y": 1,
        "x": "2017-12-22 16:17"
    }, {
        "y": 1,
        "x": "2017-12-22 16:22"
    }, {
        "y": 2,
        "x": "2017-12-22 16:24"
    }],
    "backgroundColor": "#3A74FB",
    "label": "ft7wcqu3hzvca"
}, {
    "data": [{
        "y": 7,
        "x": "2017-12-22 16:05"
    }, {
        "y": 6,
        "x": "2017-12-22 16:14"
    }, {
        "y": 6,
        "x": "2017-12-22 16:18"
    }, {
        "y": 6,
        "x": "2017-12-22 16:23"
    }],
    "backgroundColor": "#9733FC",
    "label": "7mwz4m103nn1k"
}, {
    "data": [{
        "y": 8,
        "x": "2017-12-22 16:05"
    }, {
        "y": 9,
        "x": "2017-12-22 16:14"
    }, {
        "y": 8,
        "x": "2017-12-22 16:18"
    }, {
        "y": 12,
        "x": "2017-12-22 16:23"
    }],
    "backgroundColor": "#383B19",
    "label": "9nrjf616y6g22"
}]
}

问题是我需要添加缺失的时间序列，以防它们不存在于每个数据列表中。 如果系列1是日期“2017-12-22 16:23”，则其他系列都需要有值或无值的日期。如果该值在数组中不存在，那么我需要为

y

添加一个0值

如果不为循环执行大量嵌套的

，我不知道如何有效地执行该操作

编辑：

目前我有这样的想法：

{
"datasets": [{
    "data": [{
        "y": 3,
        "x": "2017-12-22 16:01"
    }, {
        "y": 23,
        "x": "2017-12-22 16:02"
    }, {
        "y": 33,
        "x": "2017-12-22 16:03"
    }, {
        "y": 12,
        "x": "2017-12-22 16:04"
    }, {
        "y": 5,
        "x": "2017-12-22 16:05"
    }],
    "backgroundColor": "#01F79A",
    "label": "3qkhfbf2kyvhk"
}, {
    "data": [{
        "y": 9,
        "x": "2017-12-22 16:04"
    }, {
        "y": 7,
        "x": "2017-12-22 16:05"
    }, {
        "y": 20,
        "x": "2017-12-22 16:06"
    }, {
        "y": 2,
        "x": "2017-12-22 16:10"
    }, {
        "y": 16,
        "x": "2017-12-22 16:11"
    }],
    "backgroundColor": "#743967",
    "label": "8u125dk9nfc0q"
}]
}

我想要的是：

{
"datasets": [{
    "data": [{
        "y": 3,
        "x": "2017-12-22 16:01"
    }, {
        "y": 23,
        "x": "2017-12-22 16:02"
    }, {
        "y": 33,
        "x": "2017-12-22 16:03"
    }, {
        "y": 12,
        "x": "2017-12-22 16:04"
    }, {
        "y": 5,
        "x": "2017-12-22 16:05"
    },{
        "y": 0,
        "x": "2017-12-22 16:06"
    }, {
        "y": 0,
        "x": "2017-12-22 16:10"
    }, {
        "y": 0,
        "x": "2017-12-22 16:11"
    }],
    "backgroundColor": "#01F79A",
    "label": "3qkhfbf2kyvhk"
}, {
    "data": [{
        "y": 0,
        "x": "2017-12-22 16:01"
    }, {
        "y": 0,
        "x": "2017-12-22 16:02"
    }, {
        "y": 0,
        "x": "2017-12-22 16:03"
    },{
        "y": 9,
        "x": "2017-12-22 16:04"
    }, {
        "y": 7,
        "x": "2017-12-22 16:05"
    }, {
        "y": 20,
        "x": "2017-12-22 16:06"
    }, {
        "y": 2,
        "x": "2017-12-22 16:10"
    }, {
        "y": 16,
        "x": "2017-12-22 16:11"
    }],
    "backgroundColor": "#743967",
    "label": "8u125dk9nfc0q"
}]
}

每个系列都必须有不同的时间戳。如果序列中不存在时间戳，我必须将其与0 y值相加

以下是我从数据库中获得的初始数据：

查询：

cursor.execute('SELECT strftime(\'%%Y-%%m-%%d %%H:%%M\',s.sample_time) as sample_time,\n'
                       '    id,\n'
                       '    dbid,\n'
                       '    sql_id,\n'
                       '    sql_plan_hash_value,\n'
                       '    sid,\n'
                       '    serial,\n'
                       '    count(sql_id) as resources_consumed\n'
                       'FROM sash s\n'
                       'where sql_id in (select sql_id from (\n'
                       '                                  select\n'
                       '                                      id,\n'
                       '                                      dbid,\n'
                       '                                      SQL_ID ,\n'
                       '                                      sql_plan_hash_value,\n'
                       '                                      sid,\n'
                       '                                      serial,\n'
                       '                                      count(*) as resources_consumed\n'
                       '                                 from sash\n'
                       '                                 where sid = %s \n'
                       '                                 and   serial = %s \n'
                       '                                 and   dbid = %s \n'
                       '                                 group by sql_id,sql_plan_hash_value,sid,serial,dbid\n'
                       '                         order by resources_consumed desc LIMIT 10)\n'
                       '             )\n'
                       'and sample_time between datetime(\'now\',\'localtime\',\'-60 minutes\') and datetime(\'now\',\'localtime\')        \n'
                       'and sid= %s \n'
                       'and serial= %s \n'
                       'group by strftime(\'%%Y-%%m-%%d %%H:%%M\',s.sample_time),sql_id,sql_plan_hash_value,sid,serial,dbid\n'
                       'order by strftime(\'%%Y-%%m-%%d %%H:%%M\',s.sample_time)', [sid, serial, dbid, sid, serial])

输出：

    [{
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:41',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59389,
    'resources_consumed': 1
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:41',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59395,
    'resources_consumed': 2
}, {
    'sql_id': u'0m9b1dywgrdqj',
    'sql_plan_hash_value': 3103504081L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59469,
    'resources_consumed': 1
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59511,
    'resources_consumed': 17
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59421,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59503,
    'resources_consumed': 8
}, {
    'sql_id': u'dp0vgyb1hsfjb',
    'sql_plan_hash_value': 3272358443L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59454,
    'resources_consumed': 1
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59510,
    'resources_consumed': 8
}, {
    'sql_id': u'1xc91cuvu7j11',
    'sql_plan_hash_value': 3080963105L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59555,
    'resources_consumed': 3
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59577,
    'resources_consumed': 26
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59532,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59578,
    'resources_consumed': 8
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59565,
    'resources_consumed': 3
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59644,
    'resources_consumed': 17
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59623,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59642,
    'resources_consumed': 11
}, {
    'sql_id': u'dp0vgyb1hsfjb',
    'sql_plan_hash_value': 3272358443L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59614,
    'resources_consumed': 2
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59648,
    'resources_consumed': 3
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59665,
    'resources_consumed': 3
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59649,
    'resources_consumed': 1
}, {
    'sql_id': u'7726bj0dhtnmt',
    'sql_plan_hash_value': 453825145,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59718,
    'resources_consumed': 11
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59707,
    'resources_consumed': 13
}, {
    'sql_id': u'cmx7t67z8wa74',
    'sql_plan_hash_value': 4270729444L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59705,
    'resources_consumed': 19
}, {
    'sql_id': u'0m9b1dywgrdqj',
    'sql_plan_hash_value': 3103504081L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59765,
    'resources_consumed': 2
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59768,
    'resources_consumed': 10
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59770,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59764,
    'resources_consumed': 11
}, {
    'sql_id': u'dp0vgyb1hsfjb',
    'sql_plan_hash_value': 3272358443L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59754,
    'resources_consumed': 1
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:48',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59779,
    'resources_consumed': 4
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:48',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59788,
    'resources_consumed': 5
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:48',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59789,
    'resources_consumed': 1
}]

这里有一个用于Python 2的东西，它满足了我的需求。我留下了一些
print（）
调用，其中显示了内部构建和使用的两个重要数据结构的内容。看到它们里面有什么应该会更容易理解它是如何工作的

from __future__ import print_function
from collections import defaultdict
from pprint import pformat
from random import randint
from series import data

def indent(text, amount, char=' '):
    """ Indent each line of text by indicated number of characters. """
    padding = amount * char
    return ''.join(padding+line for line in text.splitlines(True))

def GetRandomHexColor():
    return '#{:06X}'.format(randint(0, 0xffffff))


# Extract the needed information from data grouped so that the sample times
# are grouped together by sql_id.
timestamps = defaultdict(dict)
for row in data:
    timestamps[row['sql_id']][row['sample_time']] = row['resources_consumed']
print('timestamps:')
print(indent(pformat(dict(timestamps)), 4))

# Create a sorted list of all the unique timestamps that exist.
master_series = sorted(set(stamp for stamps in timestamps.values()
                            for stamp in stamps))
print()
print('master_series:')
print(indent(pformat(master_series), 4))

# Create list of entries where each has a sublist that consists of values for
# every timestamp in the master_series.
datasets = [{'label': sql_id,
             'backgroundColor': GetRandomHexColor(),
             'data': [{'y': timestamps[sql_id][stamp]
                                if stamp in timestamps[sql_id] else 0,
                       'x': stamp} for stamp in master_series]
            } for sql_id in sorted(timestamps)]
print()
print('datasets:')
print(indent(pformat(datasets), 4))

输出：

    [{
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:41',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59389,
    'resources_consumed': 1
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:41',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59395,
    'resources_consumed': 2
}, {
    'sql_id': u'0m9b1dywgrdqj',
    'sql_plan_hash_value': 3103504081L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59469,
    'resources_consumed': 1
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59511,
    'resources_consumed': 17
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59421,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59503,
    'resources_consumed': 8
}, {
    'sql_id': u'dp0vgyb1hsfjb',
    'sql_plan_hash_value': 3272358443L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59454,
    'resources_consumed': 1
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:42',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59510,
    'resources_consumed': 8
}, {
    'sql_id': u'1xc91cuvu7j11',
    'sql_plan_hash_value': 3080963105L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59555,
    'resources_consumed': 3
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59577,
    'resources_consumed': 26
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59532,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59578,
    'resources_consumed': 8
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:43',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59565,
    'resources_consumed': 3
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59644,
    'resources_consumed': 17
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59623,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59642,
    'resources_consumed': 11
}, {
    'sql_id': u'dp0vgyb1hsfjb',
    'sql_plan_hash_value': 3272358443L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59614,
    'resources_consumed': 2
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:44',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59648,
    'resources_consumed': 3
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59665,
    'resources_consumed': 3
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59649,
    'resources_consumed': 1
}, {
    'sql_id': u'7726bj0dhtnmt',
    'sql_plan_hash_value': 453825145,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59718,
    'resources_consumed': 11
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59707,
    'resources_consumed': 13
}, {
    'sql_id': u'cmx7t67z8wa74',
    'sql_plan_hash_value': 4270729444L,
    'sample_time': u'2017-12-23 10:45',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59705,
    'resources_consumed': 19
}, {
    'sql_id': u'0m9b1dywgrdqj',
    'sql_plan_hash_value': 3103504081L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59765,
    'resources_consumed': 2
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59768,
    'resources_consumed': 10
}, {
    'sql_id': u'50kcsz2gh1w84',
    'sql_plan_hash_value': 2667639044L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59770,
    'resources_consumed': 1
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59764,
    'resources_consumed': 11
}, {
    'sql_id': u'dp0vgyb1hsfjb',
    'sql_plan_hash_value': 3272358443L,
    'sample_time': u'2017-12-23 10:47',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59754,
    'resources_consumed': 1
}, {
    'sql_id': u'3qkhfbf2kyvhk',
    'sql_plan_hash_value': 2234478098L,
    'sample_time': u'2017-12-23 10:48',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59779,
    'resources_consumed': 4
}, {
    'sql_id': u'8u125dk9nfc0q',
    'sql_plan_hash_value': 2470916118L,
    'sample_time': u'2017-12-23 10:48',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59788,
    'resources_consumed': 5
}, {
    'sql_id': u'ft7wcqu3hzvca',
    'sql_plan_hash_value': 2265968010L,
    'sample_time': u'2017-12-23 10:48',
    'dbid': 312109145,
    'sid': 64,
    'serial': 16655,
    'id': 59789,
    'resources_consumed': 1
}]

时间戳：
{u'0m9b1dywgrdqj'：{u'2017-12-23 10:42'：1，u'2017-12-23 10:47'：2}，
u'1xc91cuvu7j11'：{u'2017-12-23 10:43'：3}，
u'3QKHFF2KYVHK'：{u'2017-12-23 10:41'：1，
u'2017-12-23 10:42:17，
u'2017-12-23 10:43:26，
u'2017-12-23 10:44:17，
u'2017-12-23 10:45:3，
u'2017-12-23 10:47:10，
u'2017-12-23 10:48'：4}，
u'50kcsz2gh1w84'：{u'2017-12-23 10:42'：1，
u'2017-12-23 10:43:1，
u'2017-12-23 10:44:1，
u'2017-12-23 10:45:1，
u'2017-12-23 10:47'：1}，
u'7726bj0dhtnmt'：{u'2017-12-23 10:45'：11}，
u'8u125dk9nfc0q'：{u'2017-12-23 10:42'：8，
u'2017-12-23 10:43:8，
u'2017-12-23 10:44:11，
u'2017-12-23 10:45:13，
u'2017-12-23 10:47:11，
u'2017-12-23 10:48'：5}，
u'cmx7t67z8wa74'：{u'2017-12-23 10:45'：19}，
u'dp0vgyb1hsfjb'：{u'2017-12-23 10:42'：1，
u'2017-12-23 10:44:2，
u'2017-12-23 10:47'：1}，
u'ft7wcqu3hzvca'：{u'2017-12-23 10:41'：2，
u'2017-12-23 10:42:8，
u'2017-12-23 10:43:3，
u'2017-12-23 10:44:3，
u'2017-12-23 10:48'：1}
master_系列：
[u'2017-12-23 10:41'，
u'2017-12-23 10:42'，
u'2017-12-23 10:43'，
u'2017-12-23 10:44'，
u'2017-12-23 10:45'，
u'2017-12-23 10:47'，
u'2017-12-23 10:48']
数据集：
[{'backgroundColor'：'BBF2C0'，
'data'：[{'x'：u'2017-12-23 10:41'，'y'：0}，
{'x'：u'2017-12-23 10:42'，'y'：1}，
{'x'：u'2017-12-23 10:43'，'y'：0}，
{'x'：u'2017-12-23 10:44'，'y'：0}，
{'x'：u'2017-12-23 10:45'，'y'：0}，
{'x'：u'2017-12-23 10:47'，'y'：2}，
{'x'：u'2017-12-23 10:48'，'y'：0}]，
“标签”：u'0m9b1dywgrdqj'}，
{'backgroundColor'：'09BC4F'，
'data'：[{'x'：u'2017-12-23 10:41'，'y'：0}，
{'x'：u'2017-12-23 10:42'，'y'：0}，
{'x'：u'2017-12-23 10:43'，'y'：3}，
{'x'：u'2017-12-23 10:44'，'y'：0}，
{'x'：u'2017-12-23 10:45'，'y'：0}，
{'x'：u'2017-12-23 10:47'，'y'：0}，
{'x'：u'2017-12-23 10:48'，'y'：0}]，
“标签”：u'1xc91cuvu7j11'}，
{'backgroundColor'：'19F805'，
“数据”：[{'x'：u'2017-12-23 10:41'，'y'：1}，
{'x'：u'2017-12-23 10:42'，'y'：17}，
{'x'：u'2017-12-23 10:43'，'y'：26}，
{'x'：u'2017-12-23 10:44'，'y'：17}，
{'x'：u'2017-12-23 10:45'，'y'：3}，
{'x'：u'2017-12-23 10:47'，'y'：10}，
{'x'：u'2017-12-23 10:48'，'y'：4}]，
“标签”：u'3qkhfbf2kyvhk'}，
{'backgroundColor'：'A85778'，
'data'：[{'x'：u'2017-12-23 10:41'，'y'：0}，
{'x'：u'2017-12-23 10:42'，'y'：1}，
{'x'：u'2017-12-23 10:43'，'y'：1}，
{'x'：u'2017-12-23 10:44'，'y'：1}，
{'x'：u'2017-12-23 10:45'，'y'：1}，
{'x'：u'2017-12-23 10:47'，'y'：1}，
{'x'：u'2017-12-23 10:48'，'y'：0}]，
“标签”：u'50kcsz2gh1w84'}，
{'backgroundColor'：'9FEC4A'，
'data'：[{'x'：u'2017-12-23 10:41'，'y'：0}，
{'x'：u'2017-12-23 10:42'，'y'：0}，
{'x'：u'2017-12-23 10:43'，'y'：0}，
{'x'：u'2017-12-23 10:44'，'y'：0}，
{'x'：u'2017-12-23 10:45'，'y'：11}，
{'x'：u'2017-12-23 10:47'，'y'：0}，
{'x'：u'2017-12-23 10:48'，'y'：0}]，
“标签”：u'7726bj0dhtnmt'}，
{'backgroundColor'：'4FBF10'，
'data'：[{'x'：u'2017-12-23 10:41'，'y'：0}，
{'x'：u'2017-12-23 10:42'，'y'：8}，
{'x'：u'2017-12-23 10:43'，'y'：8}，
{'x'：u'2017-12-23 10:44'，'y'：11}，
{'x'：u'2017-12-23 10:45'，'y'：13}，
{'x'：u'2017-12-23 10:47'，'y'：11}，
{'x'：u'2017-12-23 10:48'，'y'：5}]，
“标签”：u'8u125dk9nfc0q'}，
{'backgroundColor'：'ED6D56'，
'data'：[{'x'：u'2017-12-23 10:41'，'y'：0}，
{'x'：u'2017-12-23 10:42'，'y'：0}，
{'x'：u'2017-12-23 10:43'，'y'：0}，
{'x'：u'2017-12-23 10:44'，'y'：0}，
{'x'：u'2017-12-23 10:45'，'y'：19}，
{'x'：u'2017-12-23 10:47'，'y'：0}，
{'x'：u'2017-12-23 10:48'，'y'：0}]，
“标签”：u'cmx7t67z8wa74'}，
{'backgroundColor'：'8E3D97'，