Metadata Management For Cloud Data Warehouse

As the data of enterprises grow exponentially,more new data businesses emerge.And,the traditional data warehouse platforms with low performance and scalability are unable to cope with current production demands and cloud data warehouses are gradually becoming the primary choice for enterprises to store and manage data.Metadata is the description of all data objects,data processes and data processing flows in the data warehouses,which is crucial to the stable operation of the data warehouse.With the rapid development of cloud data warehouse,its complexity and heterogeneity also increase,and it has been a new challenge to ensure the high availability,scalability and data consistency of metadata management in cloud data warehouse.This article focuses on the problems of data source heterogeneity,inconsistent metadata storage formats,low query efficiency,and poor scalability in the cloud data warehouse scenario.A metadata management system based on Foundation DB is implemented,and a key-value mapping relationship and representation rules for the metadata model under metadata management are designed.At the same time,an external lock management strategy based on a key-value database is proposed for the global DDL lock management issue under unified metadata management.Specifically,the main work of this article includes the following aspects:1.Implementation of a metadata management system based on Foundation DB:This article proposes a design scheme for a metadata management system called FDML(Foundation DB Meta Layer)and implements the system based on Foundation DB.When processing large-scale data,this system can effectively store and manage metadata.Different data sources can access data through the data interface provided by the FDML system in this article,which avoids the complexity of managing metadata that is scattered in different data sources and the difficulty of ensuring consistency.The FDML system in this article utilizes the high performance,high availability,and high scalability features of the Foundation DB database,supports fast queries of metadata,and improves the efficiency and scalability of metadata management.2.Proposing rules for key-value mapping and representation of the metadata model:This article proposes a rule for representing metadata information,which converts metadata information of different types and structures into key-value pairs and stores them in a key-value database.In order to make metadata management more flexible and universal,and at the same time reduce the redundancy of metadata storage and improve query efficiency,this method divides metadata information into different logical subspaces based on the ordered storage feature of Foun-dation DB key-value.In addition,this article also proposes a method based on the serialization and deserialization mapping relationship of Protocol Buffer,which can construct key-value representations of class relationship models and semi-structured models,achieve effective management and query of metadata information,and support conversion between different data structures and types,providing better support for data management.3.Building an external lock management strategy based on key-value database:This article constructs an external lock management strategy based on a key-value database,which simulates the external lock request queue of a database by introducing two sets of key-value pairs in each metadata table,where these two sets of key-value pairs respectively identify the lock request queue of the table and the latest version number,and implement the lock management of metadata tables through the persistent method of the database.In order to ensure the atomicity of lock operations in this strategy,the operations of acquiring and releasing locks are encapsulated in Foundation DB transactions.Compared to maintaining a global lock table or a distributed coordinator,the lock management strategy proposed in this article based on a key-value database reduces the overhead of lock management.At the same time,this strategy introduces a global timestamp and supports snapshot recovery function,providing better support for data management.In summary,this article addresses the metadata management issues in cloud data warehouse scenarios by proposing three approaches.These approaches include building a metadata management system based on Foundation DB,which improves the efficiency and reduces the cost of metadata management.The work provides a reference for researchers in the field of large-scale cloud data warehouses to address metadata management issues.