The article describes how GF Securities designed and implemented a unified big‑data empowerment layer based on Apache Kyuubi to address data‑centric challenges, improve efficiency, ensure controllable governance, and support agile data scenarios across ingestion, processing, storage, and security.
This article explains the design and implementation of a unified data security control platform that protects user privacy and corporate data across multiple big‑data components (Hive, Hetu, GaussDB) by integrating Apache Ranger, custom authorization APIs, asynchronous processing, distributed locking, and SDK‑based authentication to achieve fine‑grained, one‑stop permission management.
This guide explains how to install, configure, and use the lightweight, Vim‑integrated terminal file manager Ranger on Linux, covering its three‑pane layout, essential commands, preview capabilities for files, images, and PDFs, as well as customization through its configuration files.
This article details Bilibili's implementation of Apache Ranger for fine‑grained access control across Hadoop, HDFS, Hive, Spark, and Presto, covering architecture, API redesign, admin optimizations, gray‑release strategies, permission pre‑checks, data masking, and future plans for incremental policy loading.
Bilibili’s data platform redesigns Ranger‑based access control by simplifying HDFS and Hive policy APIs, parallelizing policy loading, adding gray‑release and pre‑check mechanisms, integrating fine‑grained Hive authorization with data‑masking, extending support to Spark and Presto, and planning incremental loading, policy fusion, and a NameNode proxy to boost security and performance.
This article describes the evolution from an unsecured data warehouse to a comprehensive big‑data access control system at BanYu, detailing the background, data access methods, design goals, authentication and authorization mechanisms, policy configuration, integration with Metabase, and the overall workflow that balances security with efficiency.
BanYu’s early data warehouse lacked any access controls, prompting the creation of a comprehensive big‑data permission system that integrates authentication and authorization across Hive, Presto, HDFS, and Metabase using LDAP, Ranger policies, workflow automation, and both synchronous and asynchronous policy initialization.
This guide introduces the terminal‑based file manager Ranger, covering installation, its four‑column interface, navigation shortcuts, built‑in commands like chmod and edit, and how it offers a powerful alternative to traditional cd‑based file browsing on Linux.
Didi’s big‑data platform secures user access by adding a custom password‑based Hadoop authentication stored on the NameNode and managed through its Shumeng user‑management service, while enforcing column‑level, role‑based permissions via an Apache Ranger‑powered system that classifies data, generates policies, and now governs millions of assets.
This guide introduces four powerful open‑source terminal file managers for Linux—nnn, ranger, cfiles, and dfshow—detailing their key features, platform support, command‑line usage, and where to find their source repositories.
Discover a curated list of 11 powerful Linux terminal commands and shortcuts—including clipboard tricks, sudo shortcuts, background execution, scheduling, process management, file browsing, shutdown cancellation, and YouTube video downloading—to dramatically boost your productivity and streamline everyday tasks.
The article outlines Youzan’s evolving security architecture for its big‑data platform—starting with Apache Ranger‑based permission control, moving to a centralized permission‑management service for easier requests and audits, and finally implementing column‑level masking via SQL rewriting to protect sensitive data while balancing usability.
This guide shares eleven practical Linux command‑line techniques—from essential shortcut keys and sudo shortcuts to background execution, scheduling, process management, file browsing, shutdown cancellation, and YouTube video downloading—helping seasoned and new users work faster and smarter in the terminal.
