1. A concurrent on-line analytical processing (OLAP)-oriented database query processing method, for performing, on the basis of predicate vector-based memory OLAP star-join optimization, concurrent OLAP query processing based on a batch query predicate vector bit operation, wherein: the predicate vector-based memory OLAP star-join optimization comprises the following steps: loading a dimension table in a memory; vectorizing a predicate operation result in a query; completing a bitmap filtering operation for a multi-table star-join through a bit operation on predicate vectors of multiple query-related dimension tables, so as to select a fact table tuple satisfying a condition; and mapping a dimension table primary key to a memory offset address of a memory column-stored dimensional attribute so as to implement direct access to a dimension table group-by attribute value; and the concurrent OLAP query processing based on the batch query predicate vector bit operation comprises the following steps: grouping concurrent queries in a designated time window, and performing the concurrent queries in a batch processing manner; using a multi-bit predicate vector to store a predicate operation result of a concurrent query group, wherein each bit of each data item of the multi-bit predicate vector corresponds to a designated query predicate operation result flag bit; performing a bit operation in a unit of the multi-bit predicate vector when a star-join bitmap filtering operation is performed, wherein a position of 1 in an operation result represents a query number satisfying predicate conditions in all dimension tables; and invoking a HASH aggregate processing thread corresponding to 1 in bits of a predicate vector result to complete iterative aggregate calculation on a current fact table tuple.