...
FROM
TableA
JOIN
TableB ON
TableA.FirstName LIKE '%' + TableB.SearchTerm + '%' OR
TableA.LastName LIKE '%' + TableB.SearchTerm + '%'
....
Now, this isn't going to be the best of queries. Consider full text search instead (I'm not too familiar with it)
This OR could be split into a UNION
First things first, I notice that your 'what I do now' query:
SELECT TOP (1)
ca.SensorValue,
ca.Date
FROM sys.partitions AS p
CROSS APPLY
(
SELECT TOP (1)
v.Date,
v.SensorValue
FROM SensorValues AS v
WHERE
$PARTITION.SensorValues_Date_PF(v.Date) = p.[partition_number]
AND v.DeviceId = @fDeviceId
AND v.SensorId = @fSensorId
AND v.Date <= @fDate
ORDER BY
v.Date DESC
) AS ca
WHERE
p.[partition_number] <= $PARTITION.SensorValues_Date_PF(@fDate)
AND p.[object_id] = OBJECT_ID(N'dbo.SensorValues', N'U')
AND p.index_id = 1
ORDER BY
p.[partition_number] DESC,
ca.Date DESC;
...produces an execution plan like this:
This execution plan has an estimated total cost of 0.02 units. Over 50% of this estimated cost is the final Sort, running in Top-N mode. Now estimates are just that, but sorts can be expensive in general, so let's remove it without changing the semantics:
SELECT TOP (1)
ca.SensorId,
ca.SensorValue,
ca.Date
FROM
(
-- Partition numbers
SELECT DISTINCT
partition_number = prv.boundary_id
FROM
sys.partition_functions AS pf
JOIN sys.partition_range_values AS prv ON
prv.function_id = pf.function_id
WHERE
pf.name = N'SensorValues_Date_PF'
AND prv.boundary_id <= $PARTITION.SensorValues_Date_PF(@fDate)
) AS p
CROSS APPLY
(
SELECT TOP (1)
v.Date,
v.SensorValue,
v.SensorId
FROM dbo.SensorValues AS v
WHERE
$PARTITION.SensorValues_Date_PF(v.Date) = p.partition_number
AND v.DeviceId = @fDeviceId
AND v.SensorId = @fSensorId
AND v.Date <= @fDate
ORDER BY
v.Date DESC
) AS ca
ORDER BY
p.partition_number DESC,
ca.Date DESC
Now the execution plan has no blocking operators, and no sorts in particular. The estimated cost of the new query plan below is 0.01 units and the total cost is distributed evenly over the data access methods:
With the improvement in place, all we need to produce a result for each Sensor ID is to make a list of Sensor IDs and APPLY the previous code to each one:
SELECT
PerSensor.SensorId,
PerSensor.SensorValue,
PerSensor.Date
FROM
(
-- Sensor ID list
VALUES
(@fSensorId1),
(@FSensorId2),
(@FSensorId3)
) AS Sensor (Id)
CROSS APPLY
(
-- Optimized code applied to each sensor
SELECT TOP (1)
ca.SensorId,
ca.SensorValue,
ca.Date
FROM
(
-- Partition numbers
SELECT DISTINCT
partition_number = prv.boundary_id
FROM
sys.partition_functions AS pf
JOIN sys.partition_range_values AS prv ON
prv.function_id = pf.function_id
WHERE
pf.name = N'SensorValues_Date_PF'
AND prv.boundary_id <= $PARTITION.SensorValues_Date_PF(@fDate)
) AS p
CROSS APPLY
(
SELECT TOP (1)
v.Date,
v.SensorValue,
v.SensorId
FROM dbo.SensorValues AS v
WHERE
$PARTITION.SensorValues_Date_PF(v.Date) = p.partition_number
AND v.DeviceId = @fDeviceId
AND v.SensorId = Sensor.Id--@fSensorId1
AND v.Date <= @fDate
ORDER BY
v.Date DESC
) AS ca
ORDER BY
p.partition_number DESC,
ca.Date DESC
) AS PerSensor;
The query plan is:
Estimated query plan cost for three Sensor IDs is 0.011 - half that of the original single-sensor plan.
Best Answer
In SQL Server you can only select columns that are part of the
GROUP BYclause, or aggregate functions on any of the other columns. I've blogged about this in detail here. So you have two options:Add the additional columns to the
GROUP BYclause:Add some aggregate function on the relevant columns:
The second solution is mostly a workaround and an indication that you should fix something more general with your query.