Segment metadata queries return per segment information about:
{ "queryType":"segmentMetadata", "dataSource":"sample_datasource", "intervals":["2013-01-01/2014-01-01"] }
There are several main parts to a segment metadata query:
| property | description | required? |
|---|---|---|
| queryType | This String should always be “segmentMetadata”; this is the first thing Druid looks at to figure out how to interpret the query | yes |
| dataSource | A String defining the data source to query, very similar to a table in a relational database | yes |
| intervals | A JSON Object representing ISO-8601 Intervals. This defines the time ranges to run the query over. | yes |
| toInclude | A JSON Object representing what columns should be included in the result. Defaults to “all”. | no |
| merge | Merge all individual segment metadata results into a single result | no |
| context | An additional JSON Object which can be used to specify certain flags. | no |
The format of the result is:
[ { "id" : "some_id", "intervals" : [ "2013-05-13T00:00:00.000Z/2013-05-14T00:00:00.000Z" ], "columns" : { "__time" : { "type" : "LONG", "size" : 407240380, "cardinality" : null }, "dim1" : { "type" : "STRING", "size" : 100000, "cardinality" : 1944 }, "dim2" : { "type" : "STRING", "size" : 100000, "cardinality" : 1504 }, "metric1" : { "type" : "FLOAT", "size" : 100000, "cardinality" : null } }, "size" : 300000 } ]
There are 3 types of toInclude objects.
The grammar is as follows:
"toInclude": { "type": "all"}
The grammar is as follows:
"toInclude": { "type": "none"}
The grammar is as follows:
"toInclude": { "type": "list", "columns": [<string list of column names>]}