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Performance numbers were collected and compared between AOT, DGTT, and PBG being the insert targeting tables. 

A dedicated z13 LPAR with six CPs and a full rack Mako machine were used to evaluate the performance of AOT. All of the tables that the queries reference were accelerated. For the DGTT and PBG cases, the accelerator returned data to Db2 to insert. For the AOT case, the accelerator inserted returning data directly into the AOT on the accelerator side. 

The results are shown in Figure 10-1. 

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Queries RI101 ~ RI104 are complex selects with a few returned rows for insert. Queries RI101 ~ RI104 contain different subselect statement. Little performance difference was observed among AOT, DGTT, and PBG as most time was spent at query in IDAA. 

Queries RI201 ~ RI210 are simple selects with many rows returned for insert. The advantage of using AOT to insert directly is significant (up to 163X between AOT and DGTT, and 267X between AOT and PBG). We exhausted the work file space in Db2 subsystem in RI208 for DGTT scenario and did not continue the query. 

Queries RI301 ~ RI303 are simple selects with 1 million returned rows of 16, 32, and 48 columns respectively. Again, AOT shows the benefit. 

Queries RI401 ~ RI403 are simple selects with 1 million returned rows of the same number of columns of integer, char or varchar, and date columns, respectively. 

When AOTs are used as the target of insert from select, the select and insert parts were run on the accelerator. Almost no CPU cost was left on Db2 side. 

These experiments demonstrate the benefit of the use of AOT when more than 300,000 rows are processed. 

