Columnar data warehouses generally implement UPDATE by simply appending more rows and somehow flagging the "shadowed" rows as deleted. This benchmark would be more realistic if about 10% of the data in each table were deleted and replaced with similar data, so that there's some junk lying around that has to be skipped over by the query planner.
Columnar data warehouses generally implement UPDATE by simply appending more rows and somehow flagging the "shadowed" rows as deleted. This benchmark would be more realistic if about 10% of the data in each table were deleted and replaced with similar data, so that there's some junk lying around that has to be skipped over by the query planner.