Ad-hoc Learning

Browse our catalog of units to discover the topics you want to learn about. Use the search, tags and filters to find what you need.

DSE Version: 6.0
September 16, 2018

Cassandra-stress is great for stress testing your cluster for benchmarking or for load testing. In this unit, we will be showing you use cases for this nifty tool.

DSE Version: 6.0
August 2, 2018

DSE GraphFrames are great for performing bulk mutations. When you need to insert, update or delete a large number of vertices, edges, and properties, you can use DSE GraphFrames for the best efficiency. That includes bulk loading an existing dataset into DataStax Enterprise Graph initially. In this unit, you will learn about bulk mutations with DSE GraphFrames.

DSE Version: 6.0
August 2, 2018

In this unit, we will introduce some methods of the original GraphFrame API from Spark. We will work on the same examples that we also used in our presentation called Using Gremlin with DSE GraphFrames so that you can easily compare Gremlin and GraphFrame APIs.

DSE Version: 6.0
August 2, 2018

Gremlin is the preferred language when it comes to defining traversals in DataStax Enterprise Graph. This is also true for DSE GraphFrames. In this unit, we will describe a general strategy of using Gremlin API with DSE GraphFrames

DSE Version: 6.0
August 2, 2018

In this unit, you will be introduced to DSE GraphFrames. DSE GraphFrames is an alternative OLAP engine for DataStax Enterprise Graph. It is designed around our DataStax Enterprise Analytics offering and it enables a unique way of interacting with DataStax Enterprise Graph using various Spark APIs and tools.

DSE Version: 6.0
August 2, 2018

A Gremlin traversal can be executed using either real-time (OLTP) engine or analytic (OLAP) engine. The latter execution results in a Gremlin OLAP traversal. In this unit, you will learn about Gremlin OLAP traversals.

DSE Version: 6.0
August 2, 2018

Welcome to the Graph Analytics with DataStax Enterprise Graph course. Graph analytics is about delivering value from your graph data by combining and applying well-known analysis steps into a data analysis workflow, with the goal of doing data-driven decision making, information discovery, graph exploration, and all kinds of ad-hoc analysis.

DSE Version: 6.0
July 27, 2018

In this unit, we will be learning about bulking optimization. Bulking is the merging of multiple traversers into a single one.

DSE Version: 6.0
July 13, 2018

In this unit, we are going to discuss traversal behavior and predictability. You might be using DataStax Enterprise Graph because you anticipate having a large dataset. In this case, being able to rather and understand the characteristics of your graph is critical to developing traversals that will perform well at scale.

DSE Version: 6.0
July 13, 2018

Recommendation engines are a really good common use case for graph. In this unit, we see how we might build a recommendation engine for our KillrVideo project using Gremlin and DataStax Enterprise Graph.