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Databricks 中基于图形的可观察性数据分析与凭证售卖.pdf

上传人: Fl****zo 编号:718644 2025-06-22 12页 1.11MB

1、Graph-Powered Observability Data Analysis in Databricks with Credential VendingXinyu Liu,Danfeng Xu,Eric Sun2025-06-10AgendaObservability DataOptimize Data Layout of Huge volume of Distributed TracesForensic and Analytical Use Cases:Service Graph and Root Cause AnalysisPuppyGraphGraph analytics on t

2、op of Open Table Formats without ETLCredential VendingQuery+VisualizationFuture Innovation2DataObservability DataDistributed TracesStored in DatabricksPartitioned by Day or HourSub-partitioned by prefix(trace_id)Z-Order by(trace_id,span_id)Volume(per day)1826B events 16002900 GiB10001700 filesRetent

3、ion6+months instead of 1 week3OverviewGatewayprotobuf payloadDataDogAgentDual PublishDistributed Traces4Sample Data from Delta LakeSpan 1Span 3Span 2Span 4Span 5Trace 69101266Graph-Powered AnalysisService Topology GraphServicesTrace spansAugment/Overlay entity labels and metrics(failure,latency,thro

4、ughput)5How can we quickly and easily understand the causes and effects of service failures?PuppyGraphSupporting Credential VendingSupporting graph queries via Cypher and Gremlin6Query your Databricks data as a graph w/o ETLing data to another GraphDBCredential VendingManaged by Unity CatalogCredent

5、ialDownscopedTemporary“Lazy”token renew Safe and integrated approach7How does PuppyGraph access data?12345Credential Vending Request to Unity CatalogPOST/temporary-table-credentials Response for S3 AccessAccess Key/Secret Key pairSession TokenShort-lifeS3 Path POST/api/2.1/unity-catalog/temporary-ta

6、ble-credentials operation:READ,table_id:f84c88a7-7b14-4c32-90b3-8d45e1e53f5e 200 OK aws_temp_credentials:access_key_id:AKIAIOSFODNN7EXAMPLE,secret_access_key:wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY,session_token:IQoJb3JpZ2luX2VjEHsaDnVzLWVhc3QtMS1maXBzIkYwRAI

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本文介绍了在Databricks中使用基于图的可观测性数据分析。关键点如下: 1. **可观测性数据**:分布式追踪数据存储在Databricks中,每天处理18~26B事件,数据量达1600~2900 GiB,保留时间超过6个月。 2. **数据优化**:数据按天或小时分区,并通过Z-Order优化布局。 3. **PuppyGraph**:无需ETL,直接在开源表格式上进行图分析,支持通过Cypher和Gremlin进行图查询。 4. **凭证分发**:通过Unity Catalog管理凭证,实现安全且集成的数据访问方式。 5. **分析应用**:服务拓扑图和根本原因分析,通过叠加实体标签和指标来增强理解服务故障的因果关系。 6. **未来创新**:包括跨异构数据源的统一图分析、图驱动的异常检测和增量图处理等。 核心数据引用:每天处理18~26B事件,数据量达1600~2900 GiB,支持超过6个月的保留期。
"如何高效分析数十亿追踪事件?" "PuppyGraph怎样简化图查询操作?" "未来图分析技术的创新方向?"
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