ClickHouse: настоящее и будущееTrading & financial data Fintech Insurance Investment banking Blockchain Gambling Adult Business intelligence ClickHouse — доступная система 9 ClickHouse можно развернуть: • На своих серверах • В облаках; инкрементальная агрегация в оперативке • Выполнение запросов с использованием GPU • Интеграция с ML & AI. Обработка графов • Batch jobs • Data Hub Support For Semistructured Data 27 JSO data type:0 码力 | 32 页 | 2.62 MB | 1 年前3
ClickHouse: настоящее и будущееTrading & financial data Fintech Insurance Investment banking Blockchain Gambling Adult Business intelligence ClickHouse — доступная система 9 ClickHouse можно развернуть: • На своих серверах • В облаках; инкрементальная агрегация в оперативке • Выполнение запросов с использованием GPU • Интеграция с ML & AI. Обработка графов • Batch jobs • Data Hub Support For Semistructured Data 27 JSO data type:0 码力 | 32 页 | 776.70 KB | 1 年前3- ClickHouse in ProductionEvents Pusher 36 / 97 ClickHouse in Production: Summary Queried from › Web-interface › Business Intelligence Tools › Other DBMS › User Applications (API) › Command line Communicate with › Other DBMSs ›0 码力 | 100 页 | 6.86 MB | 1 年前3
- 7. UDF in ClickHouseArea = 16,30 2 About CraiditX CraiditX 氪信, a finance AI startup since 2015 The Main Business • AI-based risk control • AI-based marketing • AI-based customer service • ... Our Partners and Customers Begin Content Area = 16,30 3 About Me Chenzhang HU 胡宸章 R&D Engineer at CraiditX Focusing on AI systems and algorithms Active GitHub User • https://github.com/hczhcz • Interested in computer system0 码力 | 29 页 | 1.54 MB | 1 年前3
- 6. ClickHouse在众安的实践为什么发生？ 什么会发生？ 什么是最佳决策？ 分析性数据仓库 数据洞察与可视化 数据治理 预测分析与机器学习 CHAPTER 众安集智平台与clickhouse 02 集智平台 X-Brain AI 开放平台 计算框架 Hadoop, JStorm, Spark Streaming, Flink 离线/实时任务监控 数据、模型存储 Hive, HBase, Clickhouse, Kylin 数据流转、建模、机器学习任务的全生命周 期管理 • 大规模在线任务监控、自动模型性能监测、 重训练与发布 • 追溯数据血缘，数据、算法模型版本管理 • 支持算法模型结果的可重现、可审计 • 缓解AI/机器学习带来的潜在伦理与法律担忧 全生命周期管理 追溯与可重现 洞察平台架构 Why Clickhouse? Clickhosue 性能 高效的数据导入和查询性能 开源 低成本，免费 压缩比0 码力 | 28 页 | 4.00 MB | 1 年前3
- 1. Machine Learning with ClickHousemy_favorite_model.bin › Build CatBoost evaluation library. Follow the instruction at https://catboost.ai/docs/concepts/c-plus-plus-api_dynamic-c-pluplus-wrapper.html You need to get libcatboostmodel.so ›0 码力 | 64 页 | 1.38 MB | 1 年前3
- 0. Machine Learning with ClickHouse my_favorite_model.bin › Build CatBoost evaluation library. Follow the instruction at https://catboost.ai/docs/concepts/c-plus-plus-api_dynamic-c-pluplus-wrapper.html You need to get libcatboostmodel.so ›0 码力 | 64 页 | 1.38 MB | 1 年前3
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