Admin: GROUPBY HASH query plan

Mon, 01 Jan 0001 00:00:00 +0000

Here's an example of how GROUPBY HASH operations look in EXPLAIN output.

=> EXPLAIN SELECT COUNT(DISTINCT annual_income)
     FROM customer_dimension
     WHERE customer_region='NorthWest';

The output shows that the optimizer chose the less efficient GROUPBY HASH path, which means the projection was not presorted on the annual_income column. If such a projection is available, the optimizer would choose the GROUPBY PIPELINED algorithm.

Access Path:
+-GROUPBY NOTHING [Cost: 256, Rows: 1 (NO STATISTICS)] (PATH ID: 1)
|  Aggregates: count(DISTINCT customer_dimension.annual_income)
| +---> GROUPBY HASH (LOCAL RESEGMENT GROUPS) [Cost: 253, Rows: 10K (NO STATISTICS)] (PATH ID: 2)
| |      Group By: customer_dimension.annual_income
| | +---> STORAGE ACCESS for customer_dimension [Cost: 227, Rows: 50K (NO STATISTICS)] (PATH ID: 3)
| | |      Projection: public.customer_dimension_super
| | |      Materialize: customer_dimension.annual_income
| | |      Filter: (customer_dimension.customer_region = 'NorthWest'
...

Admin: GROUPBY PIPELINED query plan

Mon, 01 Jan 0001 00:00:00 +0000

If you have a projection that is already sorted on the customer_gender column, the optimizer chooses the faster GROUPBY PIPELINED operation:

 => EXPLAIN SELECT COUNT(distinct customer_gender) from customer_dimension;
Access Path:
 +-GROUPBY NOTHING [Cost: 22, Rows: 1] (PATH ID: 1)
 |  Aggregates: count(DISTINCT customer_dimension.customer_gender)
 |  Execute on: Query Initiator
 | +---> GROUPBY PIPELINED [Cost: 20, Rows: 10K] (PATH ID: 2)
 | |      Group By: customer_dimension.customer_gender
 | |      Execute on: Query Initiator
 | | +---> STORAGE ACCESS for customer_dimension [Cost: 17, Rows: 50K (3 RLE)] (PATH ID: 3)
 | | |      Projection: public.customer_dimension_DBD_1_rep_vmartdb_design_vmartdb_design_node0001
 | | |      Materialize: customer_dimension.customer_gender
 | | |      Execute on: Query Initiator

Similarly, the use of an equality predicate, such as in the following query, preserves GROUPBY PIPELINED:

=> EXPLAIN SELECT COUNT(DISTINCT annual_income)    FROM customer_dimension
   WHERE customer_gender = 'Female';

 Access Path: +-GROUPBY NOTHING [Cost: 161, Rows: 1] (PATH ID: 1)
 |  Aggregates: count(DISTINCT customer_dimension.annual_income)
 | +---> GROUPBY PIPELINED [Cost: 158, Rows: 10K] (PATH ID: 2)
 | |      Group By: customer_dimension.annual_income
 | | +---> STORAGE ACCESS for customer_dimension [Cost: 144, Rows: 47K] (PATH ID: 3)
 | | |      Projection: public.customer_dimension_DBD_1_rep_vmartdb_design_vmartdb_design_node0001
 | | |      Materialize: customer_dimension.annual_income
 | | |      Filter: (customer_dimension.customer_gender = 'Female')

Tip

If EXPLAIN reports GROUPBY HASH, modify the projection design to force it to use GROUPBY PIPELINED.

OpenText Analytics Database 26.2.x – GROUP BY paths

Admin: GROUPBY HASH query plan

Admin: GROUPBY PIPELINED query plan

Tip