The invention discloses a connected piece identification method based on association matrix compression and branch pointer vector update, which solves the problem of how to efficiently and reliably perform network connected piece identification. The invention comprises the following steps: step 1, generating a branch-node association matrix of the network according to the network branch-node related information; step 2, searching the zero-column of the branch-node association matrix to identify an isolated node; step 3, "compressing" the branch-node association matrix by rows, leaving only thecolumn labels of non-zero elements to obtain a plurality of binary connected sets; step 4, performing column scan on the branch-node association matrix and updating the branch pointer vector; and step 5, merging and growing the binary connected set according to the final branch pointer vector to obtain the final connected slice set. The method avoids a large number of graph search and logic operations, with no need to perform matrix decomposition operation, and is efficient and reliable to be suitable for advantages of accelerating by using sparse technology, etc.