daslab.seas.harvard.edu lab

AdaptiveDenormalizationZezhou (Alex)Liu,Stratos Idreos

Normalization Denormalization AdaptiveDenormalization

lessstorage/updatecostsslowqueries(joins)

morestorage/updatecostsfastqueries(scans,nojoins)

lessstorage/updatecostsfastqueries(scans)

• basedataliesinanormalizedstate• hotdataisadaptivelyandpartiallydenormalized on-demand

• enablestheadvantagesofbothnormalizationanddenormalization

• futurequeriescanbenefitfromfasterqueryprocessingoverthedenormalized data

• stillmaintainstheefficientspaceutilization,updates,andloadingtimecharacteristicsfoundinnormalizedschemas

Inthetimeittakestojoininputsof100millionrowsinanormalizedschema,wecanperforma(logical)joinbyscanningover10billionrowsindenormalizedschema.Thedisparityislargerwhenahigherpercentageofrowsareselected.

• Queriesenrichexistingpartialuniversaltablesverticallyand/orhorizontally.

• Futurequeriesreplacejoinsoverthesedataregionswithscansoverthepartialuniversaltables

• Amortizesoverhead&costofdenormalization

T1 T2 PartialUniversalTable

Operateswithinthegivenmemorybudgetbydroppingregionsofthepartialuniversaltableinresponsetomemorypressures.

Adaptivelydenormalizes onlyregionsofthedataastheyarequeriedandonlydatathathasnotyetbeendenormalized bypreviousqueries.

Q1 Q2 Q3

Adaptivedenormalization (AD)achievessignificantbenefitsevenwhentherequireddataisonlypartiallydenormalized.

Adaptivedenormalization (AD)improvessignificantlyoverrepeatedjoinpatternswithoutpenalizingthefirstjoinqueries.