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4 changes: 2 additions & 2 deletions doap_tsfile.rdf
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<homepage rdf:resource="https://tsfile.apache.org" />
<asfext:pmc rdf:resource="https://tsfile.apache.org" />

<shortdesc>The mission of Apache TsFile is the creation and maintenance of software related to a columnar storage file format designed for time series data.</shortdesc>
<description>TsFile is a columnar storage file format designed for time series data, which supports efficient compression, high throughput of read and write, and compatibility with various frameworks, such as Spark and Flink. It is easy to integrate TsFile into IoT big data processing frameworks.</description>
<shortdesc>The mission of Apache TsFile is the creation and maintenance of software related to a high-performance columnar storage file format designed for industrial time-series data.</shortdesc>
<description>TsFile is a high-performance columnar storage file format designed for industrial time-series data, featuring multi-language interfaces, high compression ratios, high read/write throughput, and fast random access capabilities. It is ideal for scenarios such as building high-quality datasets, managing data assets, conducting data analytics, and training AI models.</description>

<bug-database rdf:resource="https://github.com/apache/tsfile/issues" />
<mailing-list rdf:resource="dev@tsfile.apache.org" />
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2 changes: 1 addition & 1 deletion src/README.md
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heroText: File Format for Internet of Things
heroText: Open-source File Format for Industrial Time-Series Datasets
tagline: TsFile is a high-performance columnar storage file format designed for industrial time-series data, featuring multi-language interfaces, high compression ratios, high read/write throughput, and fast random access capabilities. It is ideal for scenarios such as building high-quality datasets, managing data assets, conducting data analytics, and training AI models.
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2 changes: 1 addition & 1 deletion src/zh/README.md
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heroText: 物联网时序数据文件格式
heroText: 工业时序数据集的开源文件格式
tagline: TsFile 是一种为工业时序数据设计的高性能列式存储文件格式,支持多语言接口、高压缩比、高读写吞吐、快速随机访问。适用于构建高质量数据集、数据资产管理、数据分析与 AI 模型训练等场景。
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