tf.data: A Machine Learning Data Processing Framework

Summary: tf.data is a compositional framework and runtime for high-throughput ML input pipelines, hiding parallelism, caching, overlap, and tuning. Fleet-scale analysis shows diverse preprocessing consumes substantial training resources, motivating cross-job sharing and storage-level projection. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: h8aab8372df9b0f76
Venue: VLDB
Year: 2021
Pagerank: 9.0820315e-05
Overall Rank: 2,062 | 86.18%
DOI: 10.14778/3476311.3476374
PDF: Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

1. Derek G. Murray (Lacework)
2. Jiří Šimša (Google)
3. Ana Klimovic (ETH Zurich)
4. Ihor Indyk (Google)

BibTeX Citation

@article{murray_vldb21,
        title = {{tf.data: A Machine Learning Data Processing Framework}},
        author = {Murray, Derek G. and Šimša, Jiří and Klimovic, Ana and Indyk, Ihor},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {12},
        pages = {2945--2958},
        doi = {10.14778/3476311.3476374},
        url = {https://doi.org/10.14778/3476311.3476374},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 16 of 16 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,672	End-to-end Optimization of Machine Learning Prediction Queries	2022	SIGMOD	8.1301225e-05
3,598	Where Is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines	2022	SIGMOD	7.1596688e-05
3,800	FastFlow: Accelerating Deep Learning Model Training with Smart Offloading of Input Data Pipeline	2023	VLDB	6.9931619e-05
5,410	GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning	2023	SIGMOD	6.1317831e-05
6,318	Progressive Compressed Records: Taking a Byte out of Deep Learning Data	2021	VLDB	5.7964881e-05
6,679	UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads	2022	VLDB	5.6956362e-05
7,369	Bullion: A Column Store for Machine Learning	2025	CIDR	5.5261972e-05
7,848	FusionFlow: Accelerating Data Preprocessing for Machine Learning with CPU-GPU Cooperation	2024	VLDB	5.4236801e-05
9,097	TensorSocket: Shared Data Loading for Deep Learning Training	2026	SIGMOD	5.208561e-05
9,099	Scheduling Data Processing Pipelines for Incremental Training on MLP-based Recommendation Models	2025	SIGMOD	5.208561e-05
9,146	Modyn: Data-Centric Machine Learning Pipeline Orchestration	2025	SIGMOD	5.2065925e-05
10,016	MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training	2025	SIGMOD	5.0825892e-05
10,040	cedar: Optimized and Unified Machine Learning Input Data Pipelines	2025	VLDB	5.0786422e-05
10,731	Mixtera: A Data Plane for Foundation Model Training	2026	SIGMOD	4.9605343e-05
10,765	FlatStor: An Efficient Embedded-Index Based Columnar Data Layout for Multimodal Data Workloads	2026	VLDB	4.9605343e-05
11,314	GPEmu: A GPU Emulator for Faster and Cheaper Prototyping and Evaluation of Deep Learning System Research	2025	VLDB	4.9605343e-05

Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
105	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00033605348
295	LINQ: Reconciling Objects, Relations and XML in the .NET Framework	2006	SIGMOD	0.00021876398
1,472	Analyzing and Mitigating Data Stalls in DNN Training	2021	VLDB	0.00010529036
2,199	Extending Relational Query Processing with ML Inference	2020	CIDR	8.8664379e-05
3,179	HELIX: Accelerating Human-in-the-loop Machine Learning	2018	VLDB	7.5444132e-05
3,224	Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics	2021	VLDB	7.503511e-05

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