Multi-granularity frequent pattern data mining based on Apriori algorithm (select GutenBerg data set and DBLP data set for mining)

Table of contents Data Warehouse Big Job – Frequent Pattern Mining 1 Experimental Overview 2 This report mainly includes the following parts: 2 The application possibilities of multiple support values are explored. 2 Experimental Principle 2 2.1 Apriori algorithm principle 2 2.2 Apriori algorithm performance 3 Experimental environment setup and operation 3 3.1 Pattern Mining […]

C++ concurrent programming (5): std::unique_lock, mutex ownership transfer, lock granularity

std::unique_lockflexible locking Reference Blog Sharing data between threads – using mutexes to protect shared data C ++ multi-threaded unique_lock detailed explanation Multithreaded programming (5) – unique_lock Compared with std::lock_guard, std::unqiue_lock is not directly related to the data type of the mutex, so it is more flexible to use It can pass in additional parameters during […]

How OpenCL obtains the minimum thread parallel granularity

Since OpenCL is a standard computing language developed for various processor devices. Therefore, unlike CUDA, its query items for device features are higher-level, and it does not provide some lower-level feature queries. For example, you can only obtain the maximum work group size using OpenCL’s device query API, but cannot obtain the minimum thread parallelism […]

Redis custom lock granularity distributed lock solution (SpringBoot version)

1. Introduction to Redis distributed lock Redis distributed lock is a distributed lock scheme implemented based on Redis. In a distributed system, multiple processes or threads may compete for the same resource at the same time, so it is necessary to use distributed locks to ensure that only one process or thread can access the […]