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authorMatei Zaharia <matei@databricks.com>2013-12-30 22:17:28 -0500
committerMatei Zaharia <matei@databricks.com>2013-12-30 22:17:28 -0500
commit0fa5809768cf60ec62b4277f04e23a44dc1582e2 (patch)
treefee16620755769a70975c41d894db43633b18098 /docs/python-programming-guide.md
parent994f080f8ae3372366e6004600ba791c8a372ff0 (diff)
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Updated docs for SparkConf and handled review comments
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1 files changed, 8 insertions, 7 deletions
diff --git a/docs/python-programming-guide.md b/docs/python-programming-guide.md
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@@ -131,15 +131,16 @@ sc = SparkContext("local", "App Name", pyFiles=['MyFile.py', 'lib.zip', 'app.egg
Files listed here will be added to the `PYTHONPATH` and shipped to remote worker machines.
Code dependencies can be added to an existing SparkContext using its `addPyFile()` method.
-You can set [system properties](configuration.html#system-properties)
-using `SparkContext.setSystemProperty()` class method *before*
-instantiating SparkContext. For example, to set the amount of memory
-per executor process:
+You can set [configuration properties](configuration.html#spark-properties) by passing a
+[SparkConf](api/pyspark/pyspark.conf.SparkConf-class.html) object to SparkContext:
{% highlight python %}
-from pyspark import SparkContext
-SparkContext.setSystemProperty('spark.executor.memory', '2g')
-sc = SparkContext("local", "App Name")
+from pyspark import SparkConf, SparkContext
+conf = (SparkConf()
+ .setMaster("local")
+ .setAppName("My app")
+ .set("spark.executor.memory", "1g"))
+sc = SparkContext(conf = conf)
{% endhighlight %}
# API Docs