42 lines
1.8 KiB
Markdown
42 lines
1.8 KiB
Markdown
# Small Materialized Aggragates
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**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.
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There are two kinds of SMA in TDengine:
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1. Block-wise SMA
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2. Time-range-wise SMA
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<!--
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```plantuml
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@startmindmap mind_map_test
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* SMA
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** Block-wise SMA
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** Time-range-wise SMA
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@endmindmap
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``` -->
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## Block-wise SMA
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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:
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1. sum(*)
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2. max(*)
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3. min(*)
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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:
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```SQL
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# create a super table with the SMA on column b disabled
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create table st (ts timestamp, a int, b int NOSMA, c double) tags (tg1 binary(10), tg2 int);
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```
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## Time-range-wise SMA
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In addition to the default block-wise SMA, users can create their own SMAs ondemand. Below is an example to create a SMA.
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```SQL
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# create a SMA every 10 minutes with SMA of sum, max and min
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create sma_indx sma_10min on st (sum(*), max(*), min(*), twa(*)) interval(10m);
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```
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Users can also drop a time-range-wise SMA like below:
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```SQL
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# drop the sma index
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drop sma_index sma_5min on st;
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```
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**NOTE: Creating an 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.** |