Druid - Order data by timestamp column - time-series

Question

I've set up a Druid cluster to ingest real-time data from Kafka.
Question
Does Druid support fetching data that's sorted by timestamp? For example, let's say I need to retrieve the latest 10 entries from a Datasource X. Can I do this by using a LimitSpec (in the Query JSON) that includes the timestamp field? Or is there another better option supported Druid?
Thanks in advance.

Answer 1

Get unaggregated rows
To get unaggregated rows, you can do a query with "queryType: "select".
Select queries are also useful when pagination is needed - they let you set a page size, and automatically return a paging identifier for use in future queries.
In this example, if we just want the top 10 rows, we can pass in "pagingSpec": { "pageIdentifiers": {}, "threshold": 10 }.
Order by timestamp
To order these rows by "timestamp", you can pass in "descending": "true".
Looks like most Druid query types support the descending property.
Example Query:
{
"queryType": "select",
"dataSource": "my_data_source",
"granularity": "all",
"intervals": [ "2017-01-01T00:00:00.000Z/2017-12-30T00:00:00.000Z" ],
"descending": "true",
"pagingSpec": { "pageIdentifiers": {}, "threshold": 10 }
}
Docs on "select" type queries

Answer 2

You can use a group by query to do this, So group by __time as an extraction function then set granularity to all and use the limitSpec to sort/limit that will work. Now if you want to use a timeseries query it is more tricky to get the latest 10. One way to do it is to set the granularity to the desired one let say Hour then set the interval to be 10H starting from the most recent point in time. This sounds more easy to say than achieve. I will go the first way unless you have a major performance issue.
{
"queryType": "groupBy",
"dataSource": "wikiticker",
"granularity": "all",
"dimensions": [
{
"type": "extraction",
"dimension": "__time",
"outputName": "extract_time",
"extractionFn": {
"type": "timeFormat"
}
},
],
"limitSpec": {
"type": "default",
"limit": 10,
"columns": [
{
"dimension": "extract_time",
"direction": "descending"
}
]
},
"aggregations": [
{
"type": "count",
"name": "$f2"
},
{
"type": "longMax",
"name": "$f3",
"fieldName": "added"
}
],
"intervals": [
"1900-01-01T00:00:00.000/3000-01-01T00:00:00.000"
]
}