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Selected Earlier Work · Interactive Analytics at Scale

Interactive Analytics at Scale: BlinkDB, VerdictDB, and SnappyData

Systems for interactive analytics over massive data with explicit guarantees on accuracy and response time.

SnappyData

Research question

Can large-scale analytics become interactive while making accuracy and latency tradeoffs explicit?

Approach

Use sampling, error estimation, stochastic planning, and platform-independent execution to expose bounded tradeoffs and reusable analytics systems.

Commercialization and acquisition

BlinkDB was commercialized through SnappyData, which was later acquired by TIBCO.

Key results

  • BlinkDB uses adaptive, multi-dimensional sampling to answer interactive SQL queries with explicit error or response-time bounds.
  • VerdictDB brings approximate query processing to existing SQL engines without requiring a new database.
  • BlinkDB was commercialized through SnappyData, which was later acquired by TIBCO.

Publications

Paper ↗Technical Report ↗Project ↗
Cite
@inproceedings{7c357390-71f0-46af-b841-6dd64ddd5193,
  title = {BlinkDB: queries with bounded errors and bounded response times on very large data},
  author = {Sameer Agarwal and Barzan Mozafari and Aurojit Panda and Henry Milner and Samuel Madden and Ion Stoica},
  booktitle = {ACM European Conference on Computer Systems},
  year = {2013},
  doi = {10.1145/2465351.2465355}
}
Paper ↗Code ↗Project ↗
Cite
@inproceedings{2120f282-9549-4542-91fb-e9d4cf1d6c2f,
  title = {The analytical bootstrap: a new method for fast error estimation in approximate query processing},
  author = {Kai Zeng and Shi Gao and Barzan Mozafari and Carlo Zaniolo},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2014},
  doi = {10.1145/2588555.2588579}
}

VerdictDB: Universalizing Approximate Query Processing

Yongjoo Park, Barzan Mozafari, Joseph Sorenson, Junhao Wang

SIGMOD 2018 · ACM SIGMOD International Conference on Management of Data

Paper ↗Project ↗
Cite
@inproceedings{ed762d26-878b-453f-b272-09d069f37d64,
  title = {VerdictDB: Universalizing Approximate Query Processing},
  author = {Yongjoo Park and Barzan Mozafari and Joseph Sorenson and Junhao Wang},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2018},
  doi = {10.1145/3183713.3196905}
}
Paper ↗Technical Report ↗Project ↗
Cite
@article{6d32861d-ba95-4e8b-91c3-bc689ec60e12,
  title = {Join on Samples: A Theoretical Guide for Practitioners},
  author = {Dawei Huang and Dong Young Yoon and Seth Pettie and Barzan Mozafari},
  journal = {Proceedings of the VLDB Endowment},
  year = {2019},
  doi = {10.14778/3372716.3372726}
}

SnappyData

Barzan Mozafari

Encyclopedia of Big Data Technologies 2019

Paper ↗Project ↗
Cite
@inproceedings{f48324cb-ef73-4f50-9ed9-7a8dfec3079f,
  title = {SnappyData},
  author = {Barzan Mozafari},
  booktitle = {Encyclopedia of Big Data Technologies},
  year = {2019},
  doi = {10.1007/978-3-319-63962-8_258-1}
}
Paper ↗Code ↗Project ↗
Cite
@inproceedings{9438c730-b302-49f6-bed8-3a77c1e7a2c2,
  title = {Demonstration of VerdictDB, the Platform-Independent AQP System},
  author = {Wen He and Yongjoo Park and Idris Hanafi and Jacob Yatvitskiy and Barzan Mozafari},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2018},
  doi = {10.1145/3183713.3193538}
}
Paper ↗Project ↗
Cite
@inproceedings{e6de4a52-07a5-47c5-8196-ace46d2a49c2,
  title = {SnappyData: A Unified Cluster for Streaming, Transactions and Interactive Analytics},
  author = {Barzan Mozafari and Jags Ramnarayan and Sudhir Menon and Yogesh Mahajan and Soubhik Chakraborty and Hemant Bhanawat and Kishor Bachhav},
  booktitle = {Conference on Innovative Data Systems Research},
  year = {2017}
}
Paper ↗Project ↗
Cite
@inproceedings{cea59a03-38c4-4acb-bd2d-a41ecabe154a,
  title = {SnappyData: A Hybrid Transactional Analytical Store Built On Spark},
  author = {Jags Ramnarayan and Barzan Mozafari and Sumedh Wale and Sudhir Menon and Neeraj Kumar and Hemant Bhanawat and Soubhik Chakraborty and Yogesh Mahajan and Rishitesh Mishra and Kishor Bachhav},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2016},
  doi = {10.1145/2882903.2899408}
}
Paper ↗Technical Report ↗Project ↗
Cite
@inproceedings{fb040b81-82bc-493d-9322-fd576b39c635,
  title = {Visualization-aware sampling for very large databases},
  author = {Yongjoo Park and Michael J. Cafarella and Barzan Mozafari},
  booktitle = {IEEE International Conference on Data Engineering},
  year = {2016},
  doi = {10.1109/ICDE.2016.7498287}
}
Paper ↗Project ↗
Cite
@inproceedings{40bace5f-2a47-4fe3-b90a-bd42d385640b,
  title = {Knowing when you're wrong: building fast and reliable approximate query processing systems},
  author = {Sameer Agarwal and Henry Milner and Ariel Kleiner and Ameet Talwalkar and Michael I. Jordan and Samuel Madden and Barzan Mozafari and Ion Stoica},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2014},
  doi = {10.1145/2588555.2593667}
}