Graph Modeling on Apache Spark: Working with Apache Spark GraphFrames
Apache Spark
| Intermediate
- 13 videos | 1h 51m 32s
- Includes Assessment
- Earns a Badge
Apache Spark, which is a widely used analytics engine, also helps anyone modeling graphs to perform powerful graph analytics. GraphFrames, a Spark package, aids this process by providing various graph algorithm implementations. Use this course to learn about GraphFrames and the application of graph algorithms on data to extract insights. Explore how GraphFrames complements the Apache Hadoop ecosystem in processing graph data. Getting hands-on, construct and visualize a GraphFrame. Practice querying nodes and relationships in a graph and finding motifs in it. Moving along, work with the breadth-first search and the shortestPaths functions to find paths between graph nodes. And finally, apply the PageRank algorithm to arrive at the most relevant nodes in a network. Upon completion, you'll be able to use GraphFrames to analyze and generate insights from graph data.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Outline apache hadoop and its ecosystem, describe graphframes and their capabilities, and recognize where graphframes fit into the apache hadoop ecosystem
Download and install apache spark and set up your ide with graphframes
Construct a graphframe starting with the definition of its nodes and edges
Define functions to present a directed as well as an undirected graph
Demonstrate the identification of the most and the least-connected nodes in a graph
Apply filters on the nodes in a graph at the dataframe and the graphframe levels -
Apply filters on the edges of a graph and apply aggregation operations on them
Search for patterns of relationships between the nodes in a spark graphframe
Illustrate how to find chains of connections as well as cycles in a graphframe
Use the breadth-first search and the shortestpaths functions to find the shortest paths between nodes in a graph
Apply the pagerank algorithm to identify triangles of connections in a graph and calculate the page rank for a graph of connected web pages
Summarize the key concepts covered in this course
IN THIS COURSE
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2m 23s
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11m 51s
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3. Setting up PySpark and GraphFrames7m 26s
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4. Constructing a GraphFrame11m 46s
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5. Visualizing a GraphFrame10m 19s
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6. Calculating the Degrees of Nodes in a Graph6m 17s
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7. Filtering the Nodes in a GraphFrame9m 58s
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8. Filtering the Edges in a GraphFrame7m 54s
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9. Finding Simple Motifs in GraphFrames11m 45s
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10. Searching for Complex Patterns in Graphs10m 24s
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11. Finding the Shortest Paths between Nodes in a Graph12m 5s
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12. Applying the PageRank Algorithm7m 30s
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13. Course Summary1m 54s
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