From b92cacd9c46dd9da407eacad33a6fdb9acbf2ff2 Mon Sep 17 00:00:00 2001
From: msabhi <abhi.is2006@gmail.com>
Date: Sun, 4 Dec 2016 08:50:30 -0500
Subject: update diagram

---
 chapter/8/big-data.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

(limited to 'chapter/8')

diff --git a/chapter/8/big-data.md b/chapter/8/big-data.md
index cc11e28..1ca16aa 100644
--- a/chapter/8/big-data.md
+++ b/chapter/8/big-data.md
@@ -97,7 +97,9 @@ The properties that power RDD with the above mentioned features :
 - A compute function to do a computation on partitions.
 - Optionally, a Partitioner for key-value RDDs (e.g. to say that the RDD is hash-partitioned)
 - Optional preferred locations (aka locality info), (e.g. block locations for an HDFS file)
-
+<figure class="main-container">
+  <img src="./spark_pipeline.png" alt="MapReduce Execution Overview" />
+</figure>
 Spark API provide two kinds of operations on a RDD:
 Transformations - lazy operations that return another RDD.
 `map (f : T => U) : RDD[T] ⇒ RDD[U]` : Return a MappedRDD[U] by applying function f to each element
-- 
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