From 2d1f1e8c36d7a091e369fafa4fc010edfcc4d5f5 Mon Sep 17 00:00:00 2001
From: Donne Martin <donne.martin@gmail.com>
Date: Tue, 9 Jun 2015 17:57:18 -0400
Subject: [PATCH] Added more info about the spark shell, context, and RDDs.

---
 spark/spark.ipynb | 16 +++++++++++-----
 1 file changed, 11 insertions(+), 5 deletions(-)

diff --git a/spark/spark.ipynb b/spark/spark.ipynb
index f619b7b..2f7b5ab 100644
--- a/spark/spark.ipynb
+++ b/spark/spark.ipynb
@@ -33,7 +33,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Start the pyspark shell:"
+    "Start the pyspark shell (REPL):"
    ]
   },
   {
@@ -44,14 +44,14 @@
    },
    "outputs": [],
    "source": [
-    "pyspark"
+    "!pyspark"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "View the spark context:"
+    "View the spark context, the main entry point to the Spark API:"
    ]
   },
   {
@@ -69,7 +69,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## RDDs"
+    "## RDDs\n",
+    "\n",
+    "Resilient Distributed Datasets (RDDs) are the fundamental unit of data in Spark.  RDDs can be created from a file, from data in memory, or from another RDD.  RDDs are immutable.\n",
+    "\n",
+    "There are two types of RDD operations:\n",
+    "* Actions: Returns values, data is not processed in an RDD until an action is preformed\n",
+    "* Transformations: Defines a new RDD based on the current\n"
    ]
   },
   {
@@ -1284,7 +1290,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.9"
+   "version": "2.7.10"
   }
  },
  "nbformat": 4,