Apache Kyuubi 1.6.0 Documentation
0 码力 | 391 页 | 5.41 MB | 2 年前Apache Kyuubi 1.6.0版本文档记录了该版本的多项改进,包括新增功能、错误修复、依赖版本升级和文档更新。主要内容涵盖对Spark 3.0的末日支持,Flink版本升级至1.14.5和1.15.1,修复了Kyuubi启动失败的问题,优化了JDBC连接处理,改进了日志记录和安全认证机制,以及增强与Iceberg、Delta Lake等存储 connectors的兼容性。此外,文档还涉及性能优化、测试改进和构建工具的完善。
Apache Kyuubi 1.6.0 Documentation
0 码力 | 195 页 | 3.88 MB | 2 年前Apache Kyuubi 是一个高性能的统一 JDBC 和 SQL 执行引擎,旨在帮助用户在大数据场景下像处理普通数据一样方便地进行数据处理和分析。它基于 Apache Spark 构建,支持多租户、高可用性和弹性资源管理,提供统一的 SQL 接口以处理 ETL、BI 分析等多种工作负载。文档详细介绍了其安装、配置、客户端使用、授权机制以及与不同数据源的连接器支持。
Apache Kyuubi 1.7.0 Documentation
0 码力 | 206 页 | 3.78 MB | 2 年前Apache Kyuubi 1.7.0 is a high-performance SQL execution engine designed to facilitate handling big data through a standardized JDBC interface. It supports multi-tenancy and high availability, ensuring secure and efficient data access. Kyuubi relies on Apache Spark for high-performance queries and integrates with various data sources via connectors. The system provides robust security, load balancing, and elastic resource management. It offers tools for monitoring, configuration, and extension, making it a versatile platform for data processing and analytics. The document also covers migration guidelines and best practices for deploying and maintaining Kyuubi in production environments.
Apache Kyuubi 1.7.2 Documentation
0 码力 | 211 页 | 3.79 MB | 2 年前Kyuubi Release 1.7.2 Apache Kyuubi Community Sep 18, 2023 ADMIN GUIDE 1 A Unified Gateway 3 1.1 Application Programming Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Multi-tenancy . . . . . . . . . . . . . .
Apache Kyuubi 1.8.0 Documentation
0 码力 | 220 页 | 3.82 MB | 2 年前Apache Kyuubi 1.8.0 is a unified multi-tenant JDBC interface built on Apache Spark, designed for large-scale data processing and analytics. It supports high performance, scalability, and security, with features like session management, resource elasticity, and integration with external systems. The document details configurations, monitoring, security, and migration guidelines, highlighting improvements and changes from previous versions. It also compares Kyuubi with HiveServer2 and Spark Thrift Server, emphasizing its enhanced capabilities in multi-tenancy, concurrency, and data security.
Apache Kyuubi 1.7.2-rc0 Documentation
0 码力 | 211 页 | 3.79 MB | 2 年前Apache Kyuubi 1.7.2 is a distributed and multi-tenant gateway designed to provide serverless SQL services for data warehouses and lakehouses. It supports multiple computing frameworks such as Spark, Flink, and Hive, enabling unified access to distributed datasets. The system features end-to-end multi-tenancy with centralized authentication and resource security, high availability through load balancing and failure detection, and fine-grained data security. Additionally, it offers various APIs and protocols for client connections, including Hive Thrift, RESTful APIs, and MySQL compatibility. The release also emphasizes community engagement and provides detailed guides for installation, configuration, and contributing to the project.
Apache Kyuubi 1.5.2 Documentation
0 码力 | 267 页 | 5.80 MB | 2 年前文档详细介绍了Apache Kyuubi 1.5.2的构建、运行、配置、监控和故障排除方法。Kyuubi是一个基于Apache Spark的统一多租户JDBC接口,支持Hive、Spark SQL、Flink、Trino等多种SQL引擎。文档还涵盖了环境要求、日志配置、测试运行、调试工具以及与Kubernetes、DBeaver、DataGrip等工具的集成指南。Kyuubi通过JDBC接口实现了大数据分析和业务开发的无缝衔接,并支持高可用性、负载均衡和数据湖技术,如Iceberg、Delta Lake和Hudi。
Apache Kyuubi 1.5.2 Documentation
0 码力 | 172 页 | 6.94 MB | 2 年前文档详细介绍了Apache Kyuubi 1.5.2的功能和配置,包括高可用性部署、监控机制、社区贡献指南以及版本发布流程。Kyuubi通过与Apache Zookeeper和Apache Curator的集成实现服务发现和协调,支持多租户隔离并依赖于Apache Spark进行查询处理。文档还涵盖了构建指南、配置详细信息以及如何使用JDBC连接到Kyuubi。
Apache Kyuubi 1.5.0 Documentation
0 码力 | 267 页 | 5.80 MB | 2 年前Welcome to Kyuubi’s documentation! Kyuubi™ is a unified multi-tenant JDBC interface for large-scale data processing and analytics, built on top of Apache Spark™ [http://spark.apache.org/]. In general, the complete ecosystem of Kyuubi falls into the hier
Apache Kyuubi 1.8.1 Documentation
0 码力 | 222 页 | 3.84 MB | 2 年前Apache Kyuubi 1.8.1 documentation provides comprehensive guidance on setting up and managing a unified gateway for large-scale data processing. It covers serverless SQL capabilities, high availability, multi-tenancy, and various engine configurations. The document also details extension points for custom functionality, session configuration management, and hot upgrade procedures. Additionally, it includes specific instructions for upgrading from previous versions and optimizing Spark SQL operations, such as small file merging and skewed join optimization.
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