From 0 to 1: The Cassandra Distributed Database
- 6 hours on-demand video
- 93 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- Set up a cluster, keyspaces, column families and manage them
- Run queries using the CQL command shell
- Design primary keys and secondary indexes with partitioning and clustering considerations
- Use the Cassandra Java driver to connect and run queries on the cluster
Cassandra manages huge datasets using it's columnar layout which is more efficient and saves space.
If you are unfamiliar with softwares that require working with a shell/command line environment, this video will be helpful for you. It explains how to update the PATH environment variable, which is needed to set up most Linux/Mac shell based softwares.
- The basics of SQL and traditional relational databases
- The basics of Java in order to use the Cassandra Java library
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 tasks
- Designing primary keys and secondary indexes, partitioning and clustering keys
- Restrictions on queries based on primary and secondary key design
- Tunable consistency using quorum and local quorum. Read and write consistency in a node
- Architecture and Storage components: Commit Log, MemTable, SSTables, Bloom Filters, Index File, Summary File and Data File
- A real world project: A Miniature Catalog Management System using the Cassandra Java driver
- Yup! Engineers and analysts who understand traditional, relational databases and want to move to big data storage systems
- Nope! Students who are just starting out understanding databases and have no prior experience with one