Data　stream　clustering　is　an　importance　issue　in　data　stream　mining.　In　most　of　the　existing　algorithms,　only　the　continuous　features　are　used　for　clustering.　In　this　paper,　we　introduce　an　algorithm　HDenStream　for　clustering　data　stream　with　heterogeneous　features.　The　HDenstream　is　also　a　density-based　algorithm,　so　it　is　capable　of　clustering　arbitrary　shapes　and　handling　outliers.　Theoretic　analysis　and　experimental　results　show　that　HDenStream　is　effective　and　efficient.