From 0 to 1: The Cassandra Distributed Database

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Course Summary :

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 indexespartitioning 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

What am I going to get from this course?

  • 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

Pre-Requisites :

  • The basics of SQL and traditional relational databases
  • The basics of Java in order to use the Cassandra Java library

Target Audience :

  • 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

Curriculum :

Section 1 - You, This Course and Us
      1 : You, This Course and Us01:45
    Section 2 - Introduction: Cassandra as a distributed, decentralized, columnar store
        2 : Downloads for Sec 2 - Introduction and Shell commands
        3 : A Column-Oriented Database
        4 : Requirements For A Product Catalog System
        5 : What Is Cassandra?
        6 : Cassandra Vs HBase
      Section 3 - Install And Set Up
          7 : Install Cassandra (Mac and Unix based systems)
          8 : Install the Cassandra Cluster Manager (Mac and Unix)
          9 : Install Maven On Your Machine02:20
        Section 4 - The Cassandra Cluster Manager
            10 : Download for sec 4 CCMClusterManagement.pdf
            11 : Create A Cassandra Cluster On Your Local Machine
            12 : Basic CCM Commands
          Section 5 - The Cassandra Data Mode
              13 : download for sec 5 DataModel.pdf
              14 : Columns And Column Families
              15 : Super Column Family And Keyspace
              16 : Comparing Cassandra With A Relational Database
            Section 6 - Shell Commands
                17 : download for sec 6
                18 : Connect To Cassandra And Create A Keyspace
                19 : Column Families And Their Properties
                20 : Modify Column Families
                21 : Insert Data Into A Column Family
                22 : Advanced Data Types: Collections And Counters
                23 : Update Simple And Collection Data Types
                24 : Manage Cluster Roles
              Section 7 - Keys And Indexes: Primary Keys, Partition Keys, Clustering Key, Secondary Indexe
                  25 : Download for sec 7
                  26 : Partition Keys: Distributing Data Across Cluster Nodes
                  27 : Partition Keys: Properties
                  28 : Clustering Keys: Data Layout On A Node
                  29 : Restrictions On Partition Keys
                  30 : Restrictions On Clustering Keys
                  31 : Secondary Indexes
                  32 : Restrictions On Secondary Indexes
                  33 : Allow Filtering
                Section 8 - Tunable Consistency
                    34 : Download for sec 8
                    35 : Write Consistency Levels And Hinted Handoff
                    36 : Read Consistency Levels
                    37 : Replication Factors And Quorum Value
                  Section 9 - Storage Systems
                      38 : Download for section 9
                      39 : Overview Of Cassandra Storage Components
                      40 : The SSTable And Its Components
                      41 : Row Cache And Key Cache
                      42 : Anatomy Of A Write Request
                      43 : Anatomy Of A Read Request And The Gossip Protocol
                    Section 10 - A Mini-Project: A Miniature Catalog Management System In Java
                        44 : Download for section 10
                        45 : Overview And Basic Setup
                        46 : Create A Session And Execute Our First Query
                        47 : Create A Column Family
                        48 : Check If A Column Family Has Been Created
                        49 : Insert Data Into The Listings Column Family
                        50 : Insert Data Into The Products Column Family
                        51 : Search For Products
                        52 : Delete A Listing
                        53 : Update Mulitple Column Families Using Logged Batch


Instructor :

Loonycorn A 4-ppl team;ex-Google.


Loonycorn is us, Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh. Between the four of us, we have studied at Stanford, IIM Ahmedabad, the IITs and have spent years (decades, actually) working in tech, in the Bay Area, New York, Singapore and Bangalore. Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too Swetha: Early Flipkart employee, IIM Ahmedabad and IIT Madras alum Navdeep: longtime Flipkart employee too, and IIT Guwahati alum We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Unanth! We hope you will try our offerings, and think you'll like them :-)


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