**SMA** (**S**mall **M**aterialized **A**ggrates) is used to speed up the query process on materialized data cube in TDengine. TDengine 3.0 gives more flexibility on the SMA configurations.
There are two kinds of SMA in TDengine:
1. Block-wise SMA
2. Time-range-wise SMA
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```plantuml
@startmindmap mind_map_test
* SMA
** Block SMA
** Time-Range SMA
@endmindmap
```
-->
![SMA in TDengine 3.0](http://www.plantuml.com/plantuml/png/Km02X-AInAAItCoybDp40WKG7Gzan9Ua5fTmWUIr589z7I4iBGMddFpaR6I1aCpSLDsWnBpqLBYeGsfU2jGu0000)
## Block-wise SMA
Block-wise SMA is created by default when the data are committed. Since time-series data are saved as block data in files, a corresponding SMA is create when the data block is written. The default block-wise SMA includes:
1. sum(*)
2. max(*)
3. min(*)
By default, the system will create SMA for each column except those columns with type *binary* and *nchar*. However, users can change the behavior by the keyword **NOSMA** to disable the SMA for a certain column like below:
```SQL
# create a super table with the SMA on column b disabled
create table st (ts timestamp, a int, b int NOSMA, c double) tags (tg1 binary(10), tg2 int);
```
## Time-range-wise SMA
In addition to the default block-wise SMA, users can create their own SMAs ondemand. Below is an example to create a SMA.
```SQL
# create a SMA every 10 minutes with SMA of sum, max and min
create sma_indx sma_5min on st (sum(*), max(*), min(*), twa(*)) interval(10m);
```
Users can also drop a time-range-wise SMA like below:
```SQL
# drop the sma index
drop sma_index sma_5min on st;
```
**NOTE: Creating a SMA index is a heavy operation which may take a long time and block the write operation. So create the time-range-wise SMA when creating the table or when there are not too much data.**