YARN 简单总结
YARN 的简单使用总结
Data engineering at Meta
High-Level Overview of the internal tech stack
Data Ingestion: Architectural Patterns
data ingestion 的几种架构：Unified Data Repository、Data Virtualization、ETL、ELT、Stream Processing
Hive MetaStore的实现和优化
Hive MetaStore的实现原理，Hive Thrift 客户端和服务端的实现，MetaCat对 HMS 的兼容以及优化，Spark调用 HMS 的逻辑
Analyzing and Comparing Lakehouse Storage Systems
讨论了 LakeHouse 系统设计的难点，在不可变高延迟的对象存储之上，增加事务特性，三大系统都使用了OCC做隔离，事务实现都用了MVCC，源数据库管理delta和hudi用了表格式，iceberg用了层次存储(单节点处理)，数据更新三者都支持CoW(适合读多写少场景)，hudi和iceberg支持MoR(适合写多的场景)
系统调优
一些系统调优的排查工具汇总
Doris Advanced
Pipeline Execution Engine, Nereids-the Brand New Planner, High-Concurrency Point Query, Materialized View, Statistics, Join Optimization. Multi-catalog, Spark Doris Connector, Other Connector, Plugin Development Manual, CloudCanal Data Import, DBT Doris Adapter, UDF, cluster management, Data Admin, Other Manager, Maintenance and Monitor, Metadata Operations and Maintenance
Doris Basic
Introduce Doris,include: Data Model(Aggregate Model,Unique Model,Duplicate Model), Data Partition(Rollup),Index(Inverted Index,BloomFilter Index,NGram BloomFilter Index,Bitmap Index). Import Scenes,Import Way(Broker Load,Routine Load,Spark Load,Stream Load,MySql Load,S3 Load,Insert Into,Importing Data in JSON Format,Min Load Replica Num),Export,Update and Delete