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tutorials/sparkling-water/README.md

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export MASTER="local-cluster[3,2,4096]"
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bin/sparkling-shell --conf spark.executor.memory=2G
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```
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> Note: I would recommend to edit your `$SPARK_HOME/conf/log4j.properties` and configure log level to `WARN` to avoid flooding output with Spark INFO messages.
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2. Open Spark UI: You can go to [http://localhost:4040/](http://localhost:4040/) to see the Spark status.
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// And return resulting model
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dlModel
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}
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```
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```
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9. Initialize `H2OContext` and start H2O services on top of the Spark:
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```scala
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```scala
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h2oContext.openFlow
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```
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> At this point, you can go use H2O UI and see status of H2O cloud by typing `getCloud`.
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