Improved Distributed Query Processing
| Author(s) | : | Prachi Bhonde, Saylee Dalu, Viraj Deshmukh, Tushar Shedge |
| Institution | : | Computer Engineering, AISSMS’s IOIT |
| Published In | : | Vol. 4, Issue 12 — December 2017 |
| Page No. | : | - |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Systems like distributed message queue and stream processing platform are being used for scaling hugenumber of partitions of data streams and on the commodity hardware, this data streams are having high velocity. APIused for programming by these systems is low level, so requires more coding which increases the maintenanceand learning time of the programmer. These systems don’t have the sufficient capability of querying in SQL like Hive,Impala or Presto big data systems. Here we are defining the minimal extension set to standard SQL for manipulation andquerying of data streams. Streaming SQL have the prototype of above extensions. A tool for streaming SQL that compilesstreaming SQL into physical plans performed on Samza which is an open-source distributed stream processingframework. Here we are comparing the performance of streaming SQL queries with similar Samza applications anddiscussing the improvements in usability.
Prachi Bhonde, Saylee Dalu, Viraj Deshmukh, Tushar Shedge, “Improved Distributed Query Processing”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 12, pp. -, December 2017.
