OpenTSDB简单使用

################################################################
创建metric：
两种方式，选择其一即可。不管何种导入方式都必须先设置metric。 
1. 事先在opentsdb中创建metric。如生成两个名为mymetric.data_1和mymetric.data_2的metric。如下：
tsdb mkmetric mymetric.data_1 mymetric.data_21

2.设置自动生成metric。修改opentsdb.conf设置：
tsd.core.auto_create_metrics = true


################################################################
数据写入：
1.telnet方式
telnet localhost 4242
put sys.cpu.user 1436333416 23 host=web01 user=10001

2.API方式
URL：
http://116.196.114.194:4242/api/put?summary
参数：
[
{
"metric": "sys.cpu.nice",
"timestamp": 1502190111,
"value": 18,
"tags": {
"host": "web01",
"dc": "lga"
}
},
{
"metric": "sys.cpu.nice",
"timestamp": 1502190171,
"value": 26,
"tags": {
"host": "web02",
"dc": "lga"
}
}
]
返回：
{
"success": 2,
"failed": 
}

3.import方式，批量导入
导入文件格式：
[root@test0926ryc001-master2 test]# cat opentsdb.txt 
mymetric.test.data 1479303678 0.841470984808 host=xyd_host
mymetric.test.data 1479303679 0.909297426826 host=xyd_host
mymetric.test.data 1479303680 0.14112000806 host=xyd_host
mymetric.test.data 1479303681 -0.756802495308 host=xyd_host
mymetric.test.data 1479303682 -0.958924274663 host=xyd_host
执行命令：
/root/src/opentsdb-2.4.RC2/build/tsdb import --config=/root/src/opentsdb-2.4.RC2/opentsdb.conf opentsdb.txt

################################################################
数据查询：
一、返回metric=test的近10秒的所有时序数据

1.Get方式：
/api/query?start=10s-ago&m=test
2.Post方式：
{
"start": "10s-ago",
"queries": [{
"aggregator": "none",
"metric": "test"
}]
}

返回：
[
    {
        "metric": "test",
        "tags": {
            "device": "D47899",
            "label": "6015",
        },
        "aggregateTags": [],
        "dps": {
            "1525343027": 26.26,
            "1525343032": 25.32
        }
    },
    {
        "metric": "test",
        "tags": {
            "device": "D47899",
            "label": "6019",
        },
        "aggregateTags": [],
        "dps": {
            "1525343027": 25.32,
            "1525343032": 26.74
        }
},
……
    {
        "metric": "test",
        "tags": {
            "device": "D47899",
            "label": "6010",
        },
        "aggregateTags": [],
        "dps": {
            "1525343027": 26.8,
            "1525343032": 25.75
        }
    }
]
二、使用filters实现tags条件查询：
1.Get方式：
/api/query?start=10s-ago&m=sum:test{device=*，label=1001|1002}
注：device和label都为tag
2.Post方式：
{
    "start": "10s-ago",
    "queries": [
        {
            "aggregator": "sum",
            "metric": "test",
            "filters": [
                {
                   "type":"wildcard",
                   "tagk":"device",
                   "filter":"*",
                   "groupBy":true
                },
                {
                   "type":"literal_or",
                   "tagk":"label",
                   "filter":"1001|1002",
                   "groupBy":true
                }
            ]
        }
    ]
}
返回：
[
    {
        "metric": "test",
        "tags": {
            "label": "1001",
            "device": "A11223",
            "status": "0"
        },
        "aggregateTags": [],
        "dps": {
            "1525344862": 24.76,
            "1525344867": 24.98
        }
    },
    {
        "metric": "app.services.temperature",
        "tags": {
            "label": "1002",
            "device": "A11224",
            "status": "0"
        },
        "aggregateTags": [],
        "dps": {
            "1525344862": 25.75,
            "1525344867": 24.74
        }
    }
]
三、对每个时序近两小时的数据点按小时分组计算(使用downsample)
1.Get方式：
/api/query?start=2h-ago&m=sum:1h-count：test{device=*，label=1001|1002}
2.Post方式：
{
    "start": "2h-ago",
    "queries": [
        {
            "aggregator": "sum",
            "metric": "test",
            "downsample": "1h-count", 
            "filters": [
                {
                   "type":"literal_or",
                   "tagk":"device",
                   "filter":"*",
                   "groupBy":true
                },
                {
                   "type":"literal_or",
                   "tagk":"label",
                   "filter":"1001|1002",
                   "groupBy":true
                }
            ]
        }
    ]
}
返回：
[
    {
        "metric": "test",
        "tags": {
            "label": "1001",
            "device": "A11223",
            "status": "0"
        },
        "aggregateTags": [],
        "dps": {
            "1525341600": 720,
            "1525345200": 91
        }
    },
    {
        "metric": "test",
        "tags": {
            "label": "1002",
            "device": "A11224",
            "status": "0"
        },
        "aggregateTags": [],
        "dps": {
            "1525341600": 720,
            "1525345200": 91
        }
    }
]