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H2O - The Killer-App on Spark

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By H2O.ai Team | minute read | June 25, 2014

Category: Uncategorized
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Spark H2o Spark H2o
object AirlinesDemo extends Demo {
 override def run(conf: DemoConf): Unit = {
 // Prepare data
 // Dataset
 val dataset = “data/allyears2k_headers.csv”
 // Row parser
 val rowParser = AirlinesParser
 // Table name for SQL
 val tableName = “airlines_table”
 // Select all flights with destination == SFO
 val query = “””SELECT * FROM airlines_table WHERE dest=”SFO” “””
 // Connect to shark cluster and make a query over prostate, transfer data into H2O
 val frame:Frame = executeSpark<a href="dataset, rowParser, conf.extractor, tableName, query, local=conf.local">Airlines</a>
 Log.info(“Extracted frame from Spark: “)
 Log.info(if (frame!=null) frame.toString + “\nRows: “ + frame.numRows() else “<nothing>“)</nothing>
 // Now make a blocking call of GBM directly via Java API
 val model = gbm(frame, frame.vec(“isDepDelayed”), 100, true)
 Log.info(“Model built!”)
 }
 override def name: String = “airlines”
}
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H2O.ai Team

At H2O.ai, democratizing AI isn’t just an idea. It’s a movement. And that means that it requires action. We started out as a group of like minded individuals in the open source community, collectively driven by the idea that there should be freedom around the creation and use of AI.

Today we have evolved into a global company built by people from a variety of different backgrounds and skill sets, all driven to be part of something greater than ourselves. Our partnerships now extend beyond the open-source community to include business customers, academia, and non-profit organizations.