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The benchmark framework reports on the number of rows used to scale the measured operation. However, depending on the operation the result table size may be a factor in assessing performance. For example, an operation reducing 100 million rows to 10 rows may be assessed differently than an operation reducing 1 million rows to 10 rows. There is also the benefit of another number to track to ensure each benchmark test is comparable to the previous run.
Added a result_row_count column to benchmark results
Make it optional: Should -1 be used for benchmarks where result count does not apply?
Update appropriate tables in the benchmark-tables.py script in GCloud
The text was updated successfully, but these errors were encountered:
The benchmark framework reports on the number of rows used to scale the measured operation. However, depending on the operation the result table size may be a factor in assessing performance. For example, an operation reducing 100 million rows to 10 rows may be assessed differently than an operation reducing 1 million rows to 10 rows. There is also the benefit of another number to track to ensure each benchmark test is comparable to the previous run.
The text was updated successfully, but these errors were encountered: