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所在平台: Udemy |
课程主页: https://www.udemy.com/course/from-0-to-1-the-cassandra-distributed-database/
课程评论：没有评论
**课程名称：Cassandra分布式数据库：从0到1** **课程概述：** 本课程由经验丰富的团队讲授，成员包含两名斯坦福毕业的前谷歌工程师和两名前Flipkart首席分析师，拥有数据处理领域数十年的实践经验。 **解决痛点：** * **数据量巨大、难以管理：** 学习如何搭建多节点集群，实现数据的分布式存储。 * **数据结构非结构化、属性不断扩展：** Cassandra作为列式数据库，能够高效存储属性可变的数据，避免空间浪费。 * **高可用性需求：** 掌握Cassandra的分区和复制机制，确保即使节点故障，数据也能保持可用。 **课程内容亮点：** * **Cassandra集群管理：** 使用Cassandra Cluster Manager (CCM) 设置和管理集群。 * **Cassandra查询语言 (CQL)：** 学习创建keyspaces、column families，执行CRUD操作及其他管理任务。 * **数据建模：** 设计主键、二级索引、分区键和聚簇键，并理解查询限制。 * **一致性控制：** 掌握可调一致性，包括quorum和local quorum，以及读写一致性。 * **架构与存储组件：** 深入了解Commit Log, MemTable, SSTables, Bloom Filters, Index File, Summary File, Data File等核心组件。 * **实践项目：** 完成一个使用Cassandra Java驱动的迷你目录管理系统。 **适合人群：** * 传统数据库难以应对海量、非结构化数据的用户。 * 追求数据高可用性的开发者和运维人员。 **本课程将带您全面掌握Cassandra分布式数据库，从基础概念到实际应用。**
Taught by a team which includes 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scale data processing. Has your data gotten huge, unwieldy and hard to manage with a traditional database? Is your data unstructured with an expanding list of attributes? Do you want to ensure your data is always available even with server crashes? Look beyond Hadoop - the Cassandra distributed database is the solution to your problems. Let's parse that. Huge, unwieldy data: This course helps your set up a cluster with multiple nodes to distribute data across machines Unstructured: Cassandra is a columnar store. There are no empty cells or space wasted when you store data with variable and expanding attributes Always available: Cassandra uses partitioning and replication to ensure that your data is available even when nodes in a cluster go down What's included in this course: The Cassandra Cluster Manager (CCM) to set up and manage your cluster The Cassandra Query Language (CQL) to create keyspaces, column families, perform CRUD operations on column families and other administrative tasksDesigning primary keys and secondary indexes, partitioning and clustering keysRestrictions on queries based on primary and secondary key designTunable consistency using quorum and local quorum. Read and write consistency in a nodeArchitecture and Storage components: Commit Log, MemTable, SSTables, Bloom Filters, Index File, Summary File and Data FileA real world project: A Miniature Catalog Management System using the Cassandra Java driver
