1. copy and grab pyspark folder under the standard spark distribution to your project folder
2. setup some bootstrap to take care the environments using the following code , I use 1.6.1 as an example. and you may create this as a module.
class Setup(object): def setupSpark(self): os.environ["SPARK_HOME"] = "/Users/and/Development/spark/spark-1.6.1-bin-hadoop2.6/" os.environ["PYSPARK_SUBMIT_ARGS"]="--master local[2]"; spark_home = os.environ.get("SPARK_HOME") spark_release_file = spark_home + "/RELEASE" if os.path.exists(spark_release_file) and "Spark 1.6.1" in open(spark_release_file).read(): pyspark_submit_args = os.environ.get("PYSPARK_SUBMIT_ARGS", "") if not "pyspark-shell" in pyspark_submit_args: pyspark_submit_args += " pyspark-shell" os.environ["PYSPARK_SUBMIT_ARGS"] = pyspark_submit_args sys.path.insert(0, spark_home + "/python") sys.path.insert(0, os.path.join(spark_home, "python/lib/py4j-0.9-src.zip")) return pyspark.SparkContext()
3. you are good to go
from lib.setup import Setup sc=Setup().setupSpark() print sc.parallelize(range(1,10)).count()
6 comments:
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