SQL databases use two entirely different group by algorithms. The first one, the hash algorithm, aggregates the input records in a temporary hash table. Once all input records are processed, the hash table is returned as the result. The second algorithm, the sort/group algorithm, first sorts the input data by the grouping key so that the rows of each group follow each other in immediate succession. Afterwards, the database just needs to aggregate them. In general, both algorithms need to materialize an intermediate state, so they are not executed in a pipelined manner. Nevertheless the sort/group algorithm can use an index to avoid the sort operation, thus enabling a pipelined group by.
Note
MySQL 8.0 doesn’t use the hash algorithm. Nevertheless, the optimization for the sort/group algorithm works as described below.
Consider the following query. It delivers yesterday’s revenue grouped by PRODUCT_ID:
SELECT product_id, sum(eur_value)
FROM sales
WHERE sale_date = TRUNC(sysdate) - INTERVAL '1' DAY
GROUP BY product_idKnowing the index on SALE_DATE and PRODUCT_ID from the previous section, the sort/group algorithm is more appropriate because an INDEX RANGE SCAN automatically delivers the rows in the required order. That means the database avoids materialization because it does not need an explicit sort operation—the group by is executed in a pipelined manner.
- DB2
Explain Plan ------------------------------------------------------------ ID | Operation | Rows | Cost 1 | RETURN | | 675 2 | GRPBY (COMPLETE) | 25 of 387 ( 6.46%) | 675 3 | FETCH SALES | 387 of 387 (100.00%) | 675 4 | IXSCAN SALES_DT_PR | 387 of 1009326 ( .04%) | 24 Predicate Information 4 - START (Q1.SALE_DATE = (CURRENT DATE - 1 DAYS)) STOP (Q1.SALE_DATE = (CURRENT DATE - 1 DAYS))- Oracle
--------------------------------------------------------------- |Id |Operation | Name | Rows | Cost | --------------------------------------------------------------- | 0 |SELECT STATEMENT | | 17 | 192 | | 1 | SORT GROUP BY NOSORT | | 17 | 192 | | 2 | TABLE ACCESS BY INDEX ROWID| SALES | 321 | 192 | |*3 | INDEX RANGE SCAN | SALES_DT_PR | 321 | 3 | ---------------------------------------------------------------
The Oracle database’s execution plan marks a pipelined SORT GROUP BY operation with the NOSORT addendum. The execution plan of other databases does not mention any sort operation at all.
Support My Work
I offer SQL training, tuning and consulting. Buying my book “SQL Performance Explained” (from €9.95) also supports my work on this website.
The pipelined group by has the same prerequisites as the pipelined order by, except there are no ASC and DESC modifiers. That means that defining an index with ASC/DESC modifiers should not affect pipelined group by execution. The same is true for NULLS FIRST/LAST. Nevertheless there are databases that cannot properly use an ASC/DESC index for a pipelined group by.
Warning
PostgreSQL does not automatically do a pipelined group by if the index treats the NULL value as the smallest possible value. Adding an order by clause with the index order bypasses this problem.
The Oracle database cannot read an index backwards in order to execute a pipelined group by that is followed by an order by.
More details are available in the respective appendices: PostgreSQL, Oracle.
If we extend the query to consider all sales since yesterday, as we did in the example for the pipelined order by, it prevents the pipelined group by for the same reason as before: the INDEX RANGE SCAN does not deliver the rows ordered by the grouping key (compare Figure 6.1).
SELECT product_id, sum(eur_value)
FROM sales
WHERE sale_date >= TRUNC(sysdate) - INTERVAL '1' DAY
GROUP BY product_id- DB2
Explain Plan -------------------------------------------------------------------- ID | Operation | Rows | Cost 1 | RETURN | | 12527 2 | GRPBY (FINAL) | 25 of 25 (100.00%) | 12527 3 | TBSCAN | 25 of 25 (100.00%) | 12527 4 | SORT (INTERMEDIATE) | 25 of 25 (100.00%) | 12527 5 | GRPBY (HASHED PARTIAL) | 25 of 8050 ( .31%) | 12527 6 | FETCH SALES | 8050 of 8050 (100.00%) | 12526 7 | RIDSCN | 8050 of 8050 (100.00%) | 375 8 | SORT (UNIQUE) | 8050 of 8050 (100.00%) | 375 9 | IXSCAN SALES_DT_PR | 8050 of 1009326 ( .80%) | 372The following
whereclause was used to obtain this result:WHERE sale_date >= CURRENT_DATE - 1 MONTH.Compared to the Oracle execution plan, this looks overly complex. This is due to two circumstances:
DB2 explicitly shows a sort operation by physical storage location between the index access and the table access (operations 7 and 8).
DB2 performs a two-phase aggregation: first it does a partial aggregate to reduce the amount of data to be sorted as early as possible (operation 5) then it does a regular
SORT+GRPBY.
- Oracle
--------------------------------------------------------------- |Id |Operation | Name | Rows | Cost | --------------------------------------------------------------- | 0 |SELECT STATEMENT | | 24 | 356 | | 1 | HASH GROUP BY | | 24 | 356 | | 2 | TABLE ACCESS BY INDEX ROWID| SALES | 596 | 355 | |*3 | INDEX RANGE SCAN | SALES_DT_PR | 596 | 4 | ---------------------------------------------------------------
Instead, the Oracle database uses the hash algorithm. The advantage of the hash algorithm is that it only needs to buffer the aggregated result, whereas the sort/group algorithm materializes the complete input set. In other words: the hash algorithm needs less memory.
As with pipelined order by, a fast execution is not the most important aspect of the pipelined group by execution. It is more important that the database executes it in a pipelined manner and delivers the first result before reading the entire input. This is the prerequisite for the advanced optimization methods explained in the next chapter.
Tip
Can you think of any other database operation—besides sorting and grouping—that could possibly use an index to avoid sorting?
