A Method for Optimizing Concurrent Query of Memory Database OLTP&OLAP

Abstract

The invention relates to a memory database OLTP and OLAP concurrency query optimization method. The method includes the steps that (1) by means of two query processing engines, independent storage engines are adopted to a dimension table and a fact table; (2) the dimension table is updated through an embedded concurrency control mechanism of the independent storage engines, the fact table is equivalent to multiple continuous arrays in logic and maintains two dynamic data structures, namely a read record pointer and a write record pointer, the read record pointer records the position of the last record inquired through OLPA currently, and the write record pointer records the insert position of a new record; (3) an OLTP transactional queue and an OLAP transactional queue are independently executed with the read pointer and the write pointer as boundaries, the fact table adopts a column storage horizontal fragmentation model based on the fixed number of columns, N columns of storage records serve as an independent column storage container, and each column storage container adopts an independent data compression mechanism; (4) an access function on compressed data or non-compressed data is provided through access interfaces of the column storage containers when OLAP query has access to the column storage containers.

Description

technical field [0001] The present invention relates to a query optimization method for hybrid OLAP (analytical query processing) and OLTP (transactional query processing), in particular to an in-memory database OLTP&OLAP concurrent query optimization method for OLAP mode and load characteristics in the field of database management technology . Background technique [0002] Database technology can be divided into two main types: transactional query processing (on-line transaction processing, OLTP) and analytical query processing (on-line analytical processing, OLAP). Add, delete, and modify operations, the transaction execution time is short, need to meet the ACID (atomicity, consistency, isolation, persistence) characteristics, and need to ensure the correctness of transaction execution through a complex concurrency control mechanism; analytical query processing mainly Represented by the multi-dimensional analysis processing in the data warehouse using the multi-dimensiona...

AI Technical Summary

Problems solved by technology

Therefore, in the mixed OLTP&OLAP load, the core problem of the update operation is the concurrency control problem caused by a large number of insert-only update loads on the fact table, and the execution time of the OLAP query on the dimension table is relatively short (mainly used to generate connection Hash table), and the execution time on the fact table is longer, so the efficiency of the concurrency control mechanism on the dimension table has no significant impact on the overall OLAP query processing time

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