Construction method of distributed object database

Abstract

The invention provides a distributed object database (ODB) storage system for coping with complex data, wherein a single piece of data, namely an object, a database fragment, main and standby data andthe single piece of data all support elastic expansion, data index separation, and efficient underlying storage communication depending Apache top-level project Avro; the whole system comprises an ODB task client module, an ODB read-write service module, an ODB index module and an ODB underlying storage module, and the ODB task client module is used for submitting an object query and object update task to an ODB read-write service; the ODB read-write service module is used for receiving a query and update request of the task client and interacting with the ODB index module and the ODB underlying storage module; the ODB index module is used for updating or quickly searching a single or batch object data index; and the ODB underlying storage module is used for receiving the query and storing the object instance.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a method for constructing a distributed object database dealing with complex data. Background technique [0002] Object database (ODB, Object Database), as the name implies, refers to an object-oriented database—a database that represents data in the form of objects and classes. In object-oriented terms, objects are real entities and classes are collections of objects. Object-oriented databases follow the basic principles of object-oriented programming. Simply put, object-oriented database = object-oriented programming + database, its characteristics are as attached figure 1 As shown, it satisfies the inheritance, encapsulation and polymorphism of object-oriented programming at the same time, and also satisfies the read-write, integrity and concurrency of the basic database. Each data value for ODB query and storage update is a complete object instance. [0003]...

AI Technical Summary

Problems solved by technology

[0004] 1) The key-value pair storage document format represented by MongoDB has excellent query and storage performance, and the query is supported by multiple index modes, which is very convenient to use, but its single data currently does not exceed 16M. Complicated business support is somewhat powerless

[0005] 2) Listed storage represented by Hbase has obvious advantages at the storage level, but its query support is not friendly enough;

[0006] 3) The graph database represented by Neo4J stores relational networks, but the current graph database is not ideal in terms of distribution, and a single piece of data is generally relatively simple, and the query efficiency is greatly reduced when the amount of data is large

[0010] 1) It is mainly a stand-alone embedded application, which means that its scalability is not good enough to support massive data storage;

[0011] 2) Secondly, at the level of use, when storing objects, it does not add optimized serialization storage technology support, which means that there are some low efficiency and data redundancy problems in its storage and deserialization analysis;

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