Working with Apache Cassandra: Indexes, Aggregations, & Programmatic Access

Apache Cassandra    |    Expert
  • 10 videos | 1h 1m 34s
  • Includes Assessment
  • Earns a Badge
Rating 4.5 of 8 users Rating 4.5 of 8 users (8)
Apache Cassandra is a distributed NoSQL technology meant for large-scale data, so programmatic access to Cassandra is especially important. Cassandra supports client libraries in several major programming languages, like Java, Python, and C#. Developers use these to connect to Cassandra and to work with it from code. Begin by creating and using indexes in Cassandra. Then, define and invoke user-defined functions (UDFs) to perform aggregations. Finally, you'll create a Java Maven project with the datastax library as a dependency and connect to a Cassandra database using that library. You will create a Cassandra session, execute various operations using the datastax APIs, and confirm that these queries went through successfully. Upon completion, you will be able to create indexes on Cassandra tables, perform grouping and aggregation operations, leverage UDFs, and work programmatically with Cassandra from a Java client.


  • Discover the key concepts covered in this course
    Create indexes on columns
    Create indexes on continuous columns and query them
    Perform grouping and aggregation queries
    Create and use user-defined functions (udfs)
  • Run atomic queries
    Connect to cassandra from java
    Insert rows into cassandra tables from java
    Perform update and delete operations from java
    Summarize the key concepts covered in this course


  • 1m 27s
  • 7m 34s
  • Locked
    3.  Querying Tables with Indexes
    8m 45s
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    4.  Performing Grouping and Aggregations
    8m 6s
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    5.  Creating User-defined Functions (UDFs)
    5m 14s
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    6.  Running Atomic Queries
    4m 48s
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    7.  Connecting to Cassandra from Programmatic APIs
    9m 7s
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    8.  Modifying Cassandra Tables from Java
    6m 41s
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    9.  Updating and Deleting Data from Java
    7m 9s
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    10.  Course Summary
    2m 45s


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