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When retrieving from an aggregator, we execute the within condition first and then execute the on condition on its results. This could be optimized by including compare conditions which concern group by attributes and other attributes available in the internal aggregate stores as well.
i.e. When there's an avg function in the aggregator, it would be internally stored as sum and count. Hence we can't do above, if the on condition is something similar to "on avgPrice > 100". However, the said optimization is applicable if the on condition is similar to "on symbol == 'WSO2'", where 'symbol' is a group by attribute (since group by attributes are stored internally as well).
The text was updated successfully, but these errors were encountered:
niveathika
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Incremental Processing: Optimize the within condition by adding group by elements (and other elements available in persisting tables)
Incremental Aggregation: Optimize the within condition by adding group by elements (and other elements available in persisting tables)
May 3, 2019
When retrieving from an aggregator, we execute the within condition first and then execute the on condition on its results. This could be optimized by including compare conditions which concern group by attributes and other attributes available in the internal aggregate stores as well.
i.e. When there's an avg function in the aggregator, it would be internally stored as sum and count. Hence we can't do above, if the on condition is something similar to "on avgPrice > 100". However, the said optimization is applicable if the on condition is similar to "on symbol == 'WSO2'", where 'symbol' is a group by attribute (since group by attributes are stored internally as well).
The text was updated successfully, but these errors were encountered: