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利用 Netflix Maestro 和 Apache Iceberg 实现高效增量处理.pdf

上传人: 竿*** 编号:981536 2025-11-29 52页 3.64MB

1、Efficient Incremental Processing with Netflix Maestro and Apache IcebergNovember 19,2024,QConf San Francisco 2024Jun He Netflix2OutlineEfficient Incremental Processing with Netflix Maestro and Apache Iceberg01Introduction02Architectural design03Use cases&examples04Takeaways&future improvements3Effic

2、ient Incremental Processing with Netflix Maestro and Apache IcebergIntroduction4Efficient Incremental Processing with Netflix Maestro and Apache IcebergIntroductionLandscape of data insights at Netflix5Efficient Incremental Processing with Netflix Maestro and Apache IcebergData for Business NeedsExi

3、sting and new business initiativesStreamingGamesAdsLive6Efficient Incremental Processing with Netflix Maestro and Apache IcebergCommon ProblemsData AccuracyData FreshnessCost EfficiencyExabyte data warehouseBusiness needs for new initiativesMore than$150M per year7Efficient Incremental Processing wi

4、th Netflix Maestro and Apache IcebergLate Arriving DataKey challengeEvent timeProcessing timeTable Partition10:20PM8:20AMhour=22hour=8Late arriving event8Efficient Incremental Processing with Netflix Maestro and Apache IcebergBig Data Analytics PlatformBDAP tech stackand other BDAP internal services

5、9Efficient Incremental Processing with Netflix Maestro and Apache IcebergExisting SolutionsLookback windowIgnoring late arriving data Data accuracy Data freshness Cost efficiency Data accuracy Data freshness Cost efficiency10Efficient Incremental Processing with Netflix Maestro and Apache IcebergInc

6、remental ProcessingWhat is itIncremental processing is an approach to process data in batch but only on new or changed data.capturing incremental data changes tracking their states(i.e.whether a change is processed by a workflow or not).11Efficient Incremental Processing with Netflix Maestro and Apa

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根据《Efficient IncrementalProcessing with NetflixMaestro and ApacheIceberg》文章,以下是全文关键点: 1. **背景**:Netflix在处理大量数据时面临数据准确性、新鲜度和成本效率的挑战。 2. **解决方案**:采用Netflix Maestro和Apache Iceberg实现高效增量处理。 3. **增量处理**:仅处理新或更改的数据,提高效率。 4. **Apache Iceberg**:提供高性能格式,支持元数据管理和存储分离。 5. **Maestro**:Netflix的流程编排器,支持多种工作流和集成。 6. **案例**:通过多阶段管道和IPS模式展示增量处理的应用。 7. **效益**:提高数据准确性、新鲜度和成本效率,降低维护成本。 8. **未来**:计划进一步优化和扩展IPS功能。
"Apache Iceberg加速数据洞察?" "Netflix Maestro如何简化数据处理?" 成本效益的秘密?"
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