| dc.contributor.author | Spiegelberg, Leonhard F | |
| dc.contributor.author | Kraska, Tim | |
| dc.date.accessioned | 2021-12-17T16:25:20Z | |
| dc.date.available | 2021-09-20T18:21:39Z | |
| dc.date.available | 2021-12-17T16:25:20Z | |
| dc.date.issued | 2019 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/132284.2 | |
| dc.description.abstract | © 2019 VLDB Endowment. Spark became the defacto industry standard as an execution engine for data preparation, cleaning, distributed machine learning, streaming and, warehousing over raw data. However, with the success of Python the landscape is shifting again; there is a strong demand for tools which better integrate with the Python landscape and do not have the impedance mismatch like Spark. In this paper, we demonstrate Tuplex (short for tuples and exceptions), a Pythonnative data preparation framework that allows users to develop and deploy pipelines faster and more robustly while providing bare-metal execution times through code compilation whenever possible. | en_US |
| dc.language.iso | en | |
| dc.publisher | VLDB Endowment | en_US |
| dc.relation.isversionof | 10.14778/3352063.3352109 | en_US |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs License | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
| dc.source | VLDB Endowment | en_US |
| dc.title | Tuplex: Robust, Efficient Analytics When Python Rules | en_US |
| dc.type | Article | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.relation.journal | Proceedings of the VLDB Endowment | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
| dc.date.updated | 2021-01-11T16:52:56Z | |
| dspace.orderedauthors | Spiegelberg, LF; Kraska, T | en_US |
| dspace.date.submission | 2021-01-11T16:52:58Z | |
| mit.journal.volume | 12 | en_US |
| mit.journal.issue | 12 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Publication Information Needed | en_US |
