Query data

Request path and method

Request content

Request content in JSON format

Timestamp unit judge

The timestamp unit is second or millisecond. TSDB judges the time unit by the numeric value according to the following rules:

• When the timestamp range is [4284768,9999999999]: the unit is second, and the time range is [1970-02-20 00:59:28, 2286-11-21 01:46:39].
• When the timestamp range is [10000000000,9999999999999]: the unit is millisecond, and the time range is [1970-04-27 01:46:40.000, 2286-11-21 01:46:39.999].
• When the timestamp range is (-∞,4284768) or (9999999999999,+∞): the time range is [1970-04-27 01:46:40.000, 2286-11-21 01:46:39.999].

Note: This description is only applicable to the data write (/api/put) and data query (api/query) APIs.

Single timestamp data query

TSDB supports single timestamp data query by setting the start time same as the end time. For example, “start”：1356998400, “end”：1356998400。

Supports millisecond accuracy

TSDB timestamp supports millisecond accuracy. When the timestamps of the data written in are in milliseconds, reading data needs passing parameter msResolution:true.

Subquery in JSON format

Note:

1. A query can contain no more than 200 subqueries.
2. In the scenario where both tags and filters are specified, the post specified filter conditions take effect.
3. For details about “downsample”, “tags”, and “filters”, see the corresponding descriptions below.

Query example

Request: POST/api/query

Body:

{
  "start": 1356998400,
  "end": 1356998460,
  "queries": [
    {
      "aggregator": "sum",
      "metric": "sys.cpu.0"
    },
    {
      "aggregator": "sum",
      "metric": "sys.cpu.1"
    }
  ]
}

Data subpage query (Limit and Offset) description

Limit: The maximum number of returned subquery data points. The default value is 0, which indicates no limit on the number of returned data points.

Offset: The offset of returned subquery data points. The default value is 0, which indicates no offset of returned data points.

Note: Negative limit and offset are not allowed.

Example

If you want to return data points from 1001 to 1500, set limit for 500 and offset for 1000.

{
   "start":1346046400,
   "end":1347056500,
   "queries":[
      {
         "aggregator":"avg",
         "downsample":"2s-sum",
         "index":0,
         "metric":"sys.cpu.0",
         "limit":"500",
         "offset":"1000",
         "tags":{
            "host":"localhost",
            "appName":"hitsdb"
         }
      }
   ]
}

dpValue description

Filter the final returned data points according to the value limit conditions set by users. Filter conditions of “>”, “<”, “=”, “<=”, “>=”, “!=” are available.

Example

{
   "start":1346046400,
   "end":1347056500,
   "queries":[
      {
         "aggregator":"avg",
         "downsample":"2s-sum",
         "metric":"sys.cpu.0",
         "dpValue":">=500",
         "tags":{
            "host":"localhost",
            "appName":"hitsdb"
         }
      }
   ]
}

Downsample description

When the query time scope is large, only data of certain precision are needed to be returned. The query format is as follows:

<interval><units>-<aggregator>[-fill policy]

Wherein:

• interval: It is a numeric value, such as 5 and 60. “0all” indicates that the time dimension is aggregated to a point.

• units: s indicates second, m indicates minute, d indicates day, n indicates month, y indicates year.

  Note: supports calendar based downsampling. To use calendar boundaries, append a c to the interval time units. For example, 1 dc indicates a calendar day from 00:00 to 24:00.

• aggregator: the specifications of downsampling operators are as follows.

Note:When the aggregation operator of downsampling is specified as rfirst , rlast , Rmin or Rmax , fill policy cannot be specified in the down sampling expression.

Fill policy

Through downsample, all the time series are split up according to the specified precision and data in each downsampled range is calculated for one time. If a downsampled range has no value, the fill policy can be used to enter a specific value at this time point. For example, when the timestamp of a time series after downsample is t+0, t+20, t+30, if fill policy is not specified, the time series has only three values. If fill policy is specified to null, the time series has four values, and the value at the time point t+10 is null.

The following table lists the relationship between the fill policy and specific filling value.

Fixed Fill Policy

Method: Fill the fixed value after “#”. Allows positive and negative values. The format is as follow:

<interval><units>-<aggregator>[-fill policy]

Example: 1h-sum-fixed#6, 1h-avg-fixed#-8

Downsampling example

Example: 1m-avg, 1h-sum-zero, 1h-sum-near

Note: Downsampling is not a must when querying. You can specify the value as null or (“”), for example, {“downsample”: null} or {“downsample”: “”}, so that data point dowmsampling is not triggered。

Aggregation description

After downsampling, multiple time series are generated and their timestamps are aligned. Aggregation is the action of combining these multiple time series into one by aggregating the values at each timestamp. During aggregation, each time series must have a value at each timestamp. If a time series has no value at a timestamp, interpolation is performed. The details about interpolation are as follows.

Interpolation

If a time series has no value at a timestamp and the fill policy is not used in this case to fill a value, and meanwhile, one of other time series to be aggregated has a value at the timestamp, then a value is interpolated to this time series at the timestamp.

For example, when the downsampling and aggregation conditions are {“downsample”: “10s-avg”, “aggregator”: “sum”}, and there are two time series that need to use “sum” for aggregation, after downsampling by “10s-avg”, the timestamps of the two time series that have values are:

line 1: t+0, t+10, t+20, t+30
line 2: t+0, t+20, t+30

The line 2 lacks the value at the time point “t+10”. Therefore, before aggregation, a value is interpolated for line 2 at “t+10”. The interpolation method is determined by the aggregation operator. For details, see the following operator table.

Filters description

You can specify a filter in any of the following ways:

• Specify a filter when specifying the TagKey:

  • tagk = *: Perform “groupBy” for the Tagv of the Tagk to aggregate the values under the same Tagv.

  • tagk = tagv1|tagv2: Aggregate the values under Tagv 1 and Tagv 2 of the TagKey respectively.

• Specify a filter in JSON format:

Filter type description

Query example

Example of queries without filter

Body:

{
  "start": 1356998400,
  "end": 1356998460,
  "queries": [
    {
      "aggregator": "sum",
      "metric": "sys.cpu.0"
    },
    {
      "aggregator": "sum",
      "metric": "sys.cpu.1"
    }
  ]
}

Example of queries with filter

Body:

{
  "start": 1356998400,
  "end": 1356998460,
  "queries": [
    {
      "aggregator": "sum",
      "metric": "sys.cpu.0",
      "rate": "true",
      "filters": [
        {
          "type": "wildcard",
          "tagk": "host",
          "filter": "*",
          "groupBy": true
        },
        {
          "type": "literal_or",
          "tagk": "dc",
          "filter": "lga|lga1|lga2",
          "groupBy": false
        }
      ]
    }
  ]
}

Query result description

For a successful query, the HTTP response code is “200” and the response is returned in JSON format, as shown in the following table:

Response example:

[
    {
        "metric": "tsd.hbase.puts",
        "tags": {"appName": "hitsdb"},
        "aggregateTags": [
            "host"
        ],
        "dps": {
            "1365966001": 25595461080,
            "1365966061": 25595542522,
            "1365966062": 25595543979,
            "1365973801": 25717417859
        }
    }
]