[2012.06743] Are We Ready For Learned Cardinality Estimation?

Cardinality estimation is a fundamental but long unresolved problem in query optimization. Recently, multiple papers from different research groups consistently report that learned models have the potential to replace existing cardinality estimators. In this paper, we ask a forward-thinking question: Are we ready to deploy these learned cardinality models in production? Our study consists of three main parts. Firstly, we focus on the static environment (i.e., no data updates) and compare five new learned methods with eight traditional methods on four real-world datasets under a unified workload setting. The results show that learned models are indeed more accurate than traditional methods, but they often suffer from high training and inference costs. Secondly, we explore whether these learned models are ready for dynamic environments (i.e., frequent data updates). We find that they cannot catch up with fast data up-dates and return large errors for different reasons. For less frequent

1 mentions: @Maxwell_110
Date:

Referring Tweets

@Maxwell_110
@Maxwell_110 DBMS の「cardinality estimation」 における ML model の実用性検証 📝 t.co/XR05zM4wLS データ更新有/無の環境下で,5 つの ML 手法を,学習・推論時間や精度の観点で MySQL 等の従来手法と比較 その結果,ML 手法の精度は高いものの,いくつかの理由で導入はまだ早いと結論づけている t.co/1h2iv7TqX3

Related Entries

RSNA-MICCAI Brain Tumor Radiogenomic Classification | Kaggle
Read more RSNA-MICCAI Brain Tumor Radiogenomic Classification | Kaggle
0 users, 1 mentions 2021/08/09 09:08
recommenders/examples at main · microsoft/recommenders · GitHub
Read more recommenders/examples at main · microsoft/recommenders · GitHub
0 users, 1 mentions 2021/09/07 22:40
[1604.02532] T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos
Read more [1604.02532] T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos
0 users, 1 mentions 2021/12/15 22:37
GitHub - ConnorDonegan/geostan: Bayesian spatial analysis
Read more GitHub - ConnorDonegan/geostan: Bayesian spatial analysis
0 users, 1 mentions 2022/03/31 22:40
[2108.01099] Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data
Read more [2108.01099] Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data
0 users, 1 mentions 2022/04/21 22:37
[1904.03751] DeepGCNs: Can GCNs Go as Deep as CNNs?
Read more [1904.03751] DeepGCNs: Can GCNs Go as Deep as CNNs?
0 users, 1 mentions 2022/06/05 22:37

ML-Newsについて

機械学習の技術に関する情報は流速も早いし、分野も多様でキャッチアップが大変です。Twitterで機械学習用のリストを作っても、普段は機械学習以外の話題が多く流れており、効率的に情報収集するのは困難です。

ML-NewsはSNSを情報源とした機械学習に特化したニュースサイトです。機械学習に関する論文ブログライブラリコンペティション発表資料勉強会などの最新の情報を効率的に収集できます。

機械学習を応用した自然言語処理、画像認識、情報検索などの分野の情報や機械学習で必要になるデータ基盤やMLOpsの話題もカバーしています。
安定したサイト運営のためにGitHub sponsorを募集しています。

お知らせ

  • 2021/12/31: デザインを刷新しました
  • 2021/04/08: 日本語Kaggleのカテゴリを新設しました