September 2015
Intermediate to advanced
148 pages
3h 20m
English
Content preview from Apache Spark Graph ProcessingBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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The aggregateMessages operator
Once we have our graph ready, let's start our mission, which is aggregating the stats data in scoreGraph. In GraphX, aggregateMessages is the operator for that kind of job.
For example, let's find out the average field goals made per game by the winning teams. In other words, the games that the teams lost will not be counted. To get the average for each team, we first need to have the number of games won by the team and the total field goals that the team made in those games:
// Aggregate the total field goals made by winning teams type FGMsg = (Int, Int) val winningFieldGoalMade: VertexRDD[FGMsg] = scoreGraph aggregateMessages( // sendMsg triplet => triplet.sendToSrc(1, triplet.attr.winnerStats.fieldGoalMade) // mergeMsg ...
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