Under　differential　privacy,　to　solve　the　optimal　publishing　problem　with　multiple　consistency　constraints,　an　approximation　method　of　multiple　consistency　constraints　was　proposed　by　the　theoretical　analysis　of　the　principle　of　optimal　consistency　release.　The　main　idea　was　to　divide　the　consistency　constraint　problem　into　several　consistency　constraint　sub-problems　and　then　achieve　the　original　problem＇s　optimal　consistency　release　by　solving　each　consistency　constraint　sub-problem　repeatedly　and　independently.　The　advantage　was　that　after　the　consistency　constraint　problem　divided,　the　sub-problems　were　often　easier　to　solve,　or　the　technology　to　achieve　optimal　and　consistent　release　of　sub-problems　is　quite　mature.　Therefore　more　complex　differential　privacy　optimal　release　problem　could　be　solved.　After　analysis,　the　approximation　method＇s　convergence　was　fully　demonstrated,　ensuring　that　any　partition　of　consistency　constrained　sub-problems　can　always　achieve　the　optimal　consistency　release　of　the　original　problem.　Furthermore,　taking　the　sales　histogram　publishing　as　an　example,　based　on　the　approximation　method　of　multiple　consistency　constraints,　a　parallel　algorithm　was　designed　with　optimal　consistency　release　under　differential　privacy.　The　experimental　results　show　that　the　algorithm＇s　efficiency　is　400　times　higher　than　that　of　the　general　solution,　and　the　algorithm　can　process　millions　of　large-scale　data.　©　2021,　Editorial　Board　of　Journal　on　Communications.　All　right　reserved.