Kafka　is　a　kind　of　message　middleware　with　high　throughput.　However,　this　algorithm　has　the　problem　that　load　balancing　can　reduce　the　efficiency　of　consumer　message　processing.　The　coordinator　in　this　algorithm　optimizes　and　adjusts　the　number　of　consumers　based　on　the　correspondence　between　consumers　and　partitions　according　to　different　load　balancing　scenarios,　and　then　updates　the　correspondence　between　consumers　and　partitions　in　a　reverse　order　of　business　load.　This　algorithm　prioritizes　the　business　partitions　with　heavy　load　and　improves　the　efficiency　of　message　transmission.　And　build　the　Fabric　consortium　chain　to　verify　the　performance　of　the　algorithm.　Experimental　results　show　that　the　proposed　algorithm　improves　the　consensus　speed　by　2%　-7%　when　the　central　processing　unit　(CPU)　resource　consumption　is　5%　lower　than　that　of　other　algorithm,　and　the　consensus　link　can　still　be　available　even　when　three　out　of　six　Kafka　nodes　are　out　of　service,　which　improves　the　efficiency　and　stability　of　the　Kafka　load　balancing　algorithm.　©　2023　Inst.　of　Scientific　and　Technical　Information　of　China.　All　rights　reserved.