I have a clustered column index table for our IOT metrics (timers data). It contains more than 1 billion lines and is structured like this:
CREATE TABLE [dbo].[Data](
[DeviceId] [bigint] NOT NULL,
[MetricId] [smallint] NOT NULL,
[TimeStamp] [datetime2](2) NOT NULL,
[Value] [real] NOT NULL
)
CREATE CLUSTERED INDEX [PK_Data] ON [dbo].[Data] ([TimeStamp],[DeviceId],[MetricId])
CREATE CLUSTERED COLUMNSTORE INDEX [PK_Data] ON [dbo].[Data] WITH (DROP_EXISTING = ON, MAXDOP = 1, DATA_COMPRESSION = COLUMNSTORE_ARCHIVE)
Between 2008 and the present, there are about 10,000 different DeviceId values, and TimeStamps. A typical query for this table is as follows:
SET STATISTICS TIME, IO ON
SELECT
[DeviceId]
,[MetricId]
,DATEADD(hh, DATEDIFF(day, '2005-01-01', [TimeStamp]), '2005-01-01') As [Date]
,MIN([Value]) as [Min]
,MAX([Value]) as [Max]
,AVG([Value]) as [Avg]
,SUM([Value]) as [Sum]
,COUNT([Value]) as [Count]
FROM
[dbo].[Data]
WHERE
[DeviceId] = 6077129891325167032
AND [MetricId] = 1000
AND [TimeStamp] BETWEEN '2017-07-01' AND '2017-07-30'
GROUP BY
[DeviceId]
,[MetricId]
,DATEDIFF(day, '2005-01-01', [TimeStamp])
ORDER BY
[DeviceId]
,[MetricId]
,DATEDIFF(day, '2005-01-01', [TimeStamp])
When I execute this query, I get this for performance metrics:
Since at the moment such a request, as indicated above, is too much reading segments, I consider:
Table 'Data'. Scan count 2, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 5257, lob physical reads 9, lob read-ahead reads 4000.
Table 'Data'. Segment reads 11, segment skipped 764.
Request Plan:

This is not very optimized. I believe that 11 segments were read to extract only 212 out of 1 billion source lines (before grouping / aggregation)
, Niko Neugebauer https://github.com/NikoNeugebauer/CISL/blob/master/Azure/alignment.sql, :

MetricId TimeStamp 100%. , DeviceId ? Clustered (Rowstore), , ?