Query processing is an important concern in the field of distributed databases and also grid databases. The main problem is if a query can be decomposed into sub-queries that require operations in geographically separated databases, the sequence and the sites must be determined for performing this set of operations.
This paper has presented a query processing method for retrieving stream of video frames. A video query processor should support video-based operations for search by content and streaming, new video query types, and the incorporation of video methods and operators in generating, optimizing and executing query plans.
Many research papers on query processing and optimization use standard benchmarks like TPC-H, TPC-DS, or the Star Schema Benchmark (SSB). While these benchmarks have proven their value for evaluating query engines, we argue that they are not good bench-marks for the cardinality estimation component of query optimiz-ers.
Related work on join query optimization in distributed databases is to calculate the size of the data on two different machines and then to send the table having smaller size to. into client database and join query processing time.. This paper presents the join query optimization in distributed databases. One method for the join query is.
Volcano-An Extensible and Parallel Query Evaluation System Goetz Graefe Abstract-To investigate the interactions of extensibility and parallelism in database query processing, we have developed a new dataflow query execution system called Volcano. The Vol- cano effort provides a rich environment for research and edu-.
Scalable data analysis and query processing Scalable data processing in new settings, including interactive exploration, metadata management, cloud and serverless environments, and machine learning; query processing on compressed, semi-structured, and streaming data; query processing with additional constraints, including fairness, resource utilization, and cost.