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Radish : Compiling Efficient Query Plans for Distributed Shared Memory
| Content Provider | Semantic Scholar |
|---|---|
| Author | Myers, Brandon Halperin, Daniel Nelson, Jacob |
| Copyright Year | 2014 |
| Abstract | We present Radish, a query compiler that generates distributed programs. Recent efforts have shown that compiling queries to machine code for a single-core can remove iterator and control overhead for significant performance gains. So far, systems that generate distributed programs only compile plans for single processors and stitch them together with messaging. In this paper, we describe an approach for translating query plans into distributed programs by targeting the partitioned global address space (PGAS) parallel programming model as an intermediate representation. This approach affords a natural adaptation of pipelining techniques used in singlecore query compilers and an overall simpler design. We adapt pipelined algorithms to PGAS languages, describe efficient data structures for PGAS query execution, and implement techniques for mitigating the overhead resulting from handling a multitude of fine-grained tasks. We evaluate Radish on graph benchmark and application workloads and find that it is 4× to 100× faster than Shark, a recent distributed query engine optimized for in-memory execution. Our work makes important first steps towards ensuring that query processing systems can benefit from future advances in parallel programming and co-mingle with state-of-the-art parallel programs. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.cs.washington.edu/tr/2014/10/UW-CSE-14-10-01.pdf |
| Alternate Webpage(s) | http://www.cs.washington.edu/public_files/grad/tech_reports/radish.pdf |
| Alternate Webpage(s) | https://homes.cs.washington.edu/~bdmyers/papers/UW-CSE-14-10-01.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
