Abstract: This paper described how the Monte Carlo database system (MCDB) can be used to easily implement Baye-sian inference via Markov chain Monte Carlo (MCMC) over very large datasets．Linear Bayesian regression,LDA and Dirichlet clustering were used as examples to demonstrate this task．To implement an MCMC simulation in MCDB,a programmer specifies dependencies among variables and how they parameterize one another using the SQL language．This paper devised a simple scheme for developing large scale machine learning systems with SQL,which with the help of MCDB,can automaticly deal with parallelization and optimization problems,to achieve high efficiency in computation．

Key words: Bayesian inference,Parallel algorithms,SQL,Distributed system