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@@ -142,6 +142,7 @@ $ kubectl logs spark-master
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15/06/26 14:15:55 INFO Master: Registering worker 10.244.1.15:44839 with 1 cores, 2.6 GB RAM
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15/06/26 14:15:55 INFO Master: Registering worker 10.244.0.19:60970 with 1 cores, 2.6 GB RAM
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```
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## Step Three: Do something with the cluster
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Get the address and port of the Master service.
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@@ -196,6 +197,7 @@ SparkContext available as sc, HiveContext available as sqlContext.
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>>> sc.parallelize(range(1000)).map(lambda x:socket.gethostname()).distinct().collect()
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['spark-worker-controller-u40r2', 'spark-worker-controller-hifwi', 'spark-worker-controller-vpgyg']
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```
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## Result
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You now have services, replication controllers, and pods for the Spark master and Spark workers.
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