This is the the replication package to our paper ShuffleBench: A Benchmark for Large-Scale Data Shuffling Operations with Distributed Stream Processing Frameworks, which introduces ShuffleBench, a novel benchmark to evaluate the performance of modern stream processing frameworks.

See the README.md file inside the shufflebench-replication.zip for documentation and usage instructions.

Comprehensive financial and analytical metrics for Shuffle, including key performance indicators, market data, and ecosystem analytics.

Heart failure (HF) affects at least 26 million people worldwide, so predicting adverse events in HF patients represents a major target of clinical data science. However, achieving large sample sizes sometimes represents a challenge due to difficulties in patient recruiting and long follow-up times, increasing the problem of missing data. To overcome the issue of a narrow dataset cardinality (in a clinical dataset, the cardinality is the number of patients in that dataset), population-enhancing algorithms are therefore crucial. The aim of this study was to design a random shuffle method to enhance the cardinality of an HF dataset while it is statistically legitimate, without the need of specific hypotheses and regression models. The cardinality enhancement was validated against an established random repeated-measures method with regard to the correctness in predicting clinical conditions and endpoints. In particular, machine learning and regression models were employed to highlight the benefits of the enhanced datasets. The proposed random shuffle method was able to enhance the HF dataset cardinality (711 patients before dataset preprocessing) circa 10 times and circa 21 times when followed by a random repeated-measures approach. We believe that the random shuffle method could be used in the cardiovascular field and in other data science problems when missing data and the narrow dataset cardinality represent an issue.

Dataset Card for "wikipedia20220301en-bookcorpusopen-chunked-shuffled"

num_examples: 33.5 million download_size: 15.3 GB dataset_size: 26.1 GB

This dataset combines wikipedia20220301.en and bookcorpusopen, and splits the data into smaller chunks, of size ~820 chars (such that each item will be at least ~128 tokens for the average tokenizer). The order of the items in this dataset has been shuffled, meaning you don't have to use dataset.shuffle, which is slower to iterate over.… See the full description on the dataset page: https://huggingface.co/datasets/sradc/chunked-shuffled-wikipedia20220301en-bookcorpusopen.

Dataset used for the analyses in the research article "Shuffling Softly, Sighing Deeply: A Digital Inquiry into Representations of Older Men and Women in Literature for Different Ages" submitted to the journal Social Sciences. Data was obtained using a syntactic parser developed in collaboration with TEXTUA, the Text Mining Centre of the University of Antwerp. For copyright reasons, part of the data, which contains full sentences from the texts, was removed. However, the resulting dataset is sufficient to replicate the study.

The filenames are formatted as follows: age of the intended reader_AUTHOR_book title_year_character's age_gender_word type.json

The following word types associated with relevant characters were extracted from the texts:

1: verbs

2: possessions

3: attributive adjectives

4: predicative adjectives

Detailed Price metrics and analytics for Shuffle, including historical data and trends.

P-value computed by Fisher’s exact test is 1.28 × 10−21.

This dataset provides information about the number of properties, residents, and average property values for Shuffle Drive cross streets in Saint Louis, MO.

Detailed Gas used metrics and analytics for Shuffle, including historical data and trends.

URL: https://geoscience.data.qld.gov.au/dataset/bh015852

Detailed Token trading volume metrics and analytics for Shuffle, including historical data and trends.

Detailed price prediction analysis for Shuffle on Jul 13, 2025, including bearish case ($0.218), base case ($0.242), and bullish case ($0.266) scenarios with Buy trading signal based on technical analysis and market sentiment indicators.

Customs records of Netherlands An are available for SHUFFLE MIX B.V.. Learn about its Importer, supply capabilities and the countries to which it supplies goods

P-value computed by Fisher’s exact test is 1.90 × 10−149.

Customs records of are available for SHUFFLE CO.,LTD. Learn about its Importer, supply capabilities and the countries to which it supplies goods

Customs records of are available for SHUFFLE MASTER GMBH. Learn about its Importer, supply capabilities and the countries to which it supplies goods

This dataset is about book series. It has 1 row and is filtered where the books is Shuffle the Shoemaker. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Customs records of are available for SHUFFLE MASTER GMBH AND CO. Learn about its Importer, supply capabilities and the countries to which it supplies goods

This dataset is about book subjects. It has 1 row and is filtered where the books is Shuffle and squelch : poems and rhymes for children. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Detailed Fully diluted market cap metrics and analytics for Shuffle, including historical data and trends.