The invention discloses a
graph database query acceleration method and
system. The method comprises the following steps: constructing panoramic query
observation data through non-intrusive log interception and structured
processing; the
query statement is analyzed into an
abstract syntax tree, semantic normalization
processing is carried out, and a unique hash value is generated; predicting a hotspot query template and high-frequency parameters thereof based on a popularity value
score model, and asynchronously preloading a result to a cache; dynamically calculating adaptive survival time for each cache item according to the data change frequency and the access popularity; and constructing a multi-level cache architecture comprising a local cache, a
distributed cache and a
database built-in cache, and performing intelligent routing and collaborative backfilling based on a hash value. According to the method, intelligent and transparent acceleration of
graph database query is realized, the query performance is remarkably improved, the
database load is reduced, and the problems of redundancy, high
cold start delay and difficulty in balancing
cache consistency caused by grammar difference in traditional cache are solved.