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Apache Spark
Presenter: MH
http://bit.ly/mahboob
Spark Overview
● General purpose cluster computing system
● High-level APIs in Java, Scala, Python and R
● Supports general execution graphs
● Spark SQL
● MLlib
● GraphX
● Spark Streaming
Deployment Modes
● Amazon EC2:
○ scripts that let you launch a cluster on EC2 in about 5 minutes
● Standalone Deploy Mode:
○ launch a standalone cluster quickly without a third-party cluster manager
● Mesos:
○ deploy a private cluster using Apache Mesos
● YARN:
○ deploy Spark on top of Hadoop NextGen (YARN)
FAQ
Hadoop vs Spark
File system based | Memory based
Map-Reduce Paradigm | Any distributed computing workload
Details:
https://docs.google.com/document/d/1hcv3JOc009AVer6bVFEeGnHrt_Jb0v3v3g2qGPgRy1Y
The Spark Driver
Source:
http://mapr.com
Very good resource
https://mapr.com/ebooks/spark/
Downloadable as pdf
K-Means Clustering
First, decide the number of clusters k.
Then:
1. Initialize the center of the clusters
2. Attribute the closest cluster to each
data point
3. Set the position of each cluster to the
mean of all data points belonging to
that cluster
4. Repeat steps 2-3 until convergence
Create k points for starting centroids (often randomly)
While any point has changed cluster assignment
for every point in the dataset:
for every centroid
calculate distance between centroid and point
assign point to the cluster with the lowest distance
for every cluster calculate mean of points in that cluster
assign the centroid to the mean
Example 1
Applying k-Means Algorithm using Python
Program: kMeans.py*
Data: x-y coordinates in file testSet.txt
* Source: Chapter 10, Machine Learning in Action
Example 2
Applying k-Means Algorithm using Java API to Spark
Program: Spark_KMeans.java
Data: Random numbers in marks.txt
Example 3
https://mapr.com/ebooks/spark/08-machine-learning-mllib-spark-use-case.html
Techniques applied for NLP
● Hashing
● Stemming
● TF-IDF
● Naive Bayes
● Random Forest Regression
● Gradient Boosted Trees Regression
● Code repository: https://github.com/joebluems/Mockingbird/issues
Is Harper Lee’s Go Set a Watchman a discarded rough
draft that was to become the universally beloved
classic To Kill AMockingbird, or was it a truly separate
work?
Who is using Spark?
Source:
https://medium.com/ai
rbnb-
engineering/data-
infrastructure-at-
airbnb-8adfb34f169c
Spark @AirBnB
Spark is also an important tool for Airbnb. The team actually built something called
Airstream, which is a computational framework that sits on top of Spark Streaming and
Spark SQL, allowing engineersand the data team to get quick insights. Ultimately, for an
organization that depends on predictions and machine learning, something like Spark -
alongsideother open sourcemachinelearning libraries- iscrucial in theAirbnb stack.
Source:
https://www.packtpub.com/books/content/what-software-stack-does-airbnb-use
Thank You
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Apache spark presentation

  • 2. Spark Overview ● General purpose cluster computing system ● High-level APIs in Java, Scala, Python and R ● Supports general execution graphs ● Spark SQL ● MLlib ● GraphX ● Spark Streaming
  • 3. Deployment Modes ● Amazon EC2: ○ scripts that let you launch a cluster on EC2 in about 5 minutes ● Standalone Deploy Mode: ○ launch a standalone cluster quickly without a third-party cluster manager ● Mesos: ○ deploy a private cluster using Apache Mesos ● YARN: ○ deploy Spark on top of Hadoop NextGen (YARN)
  • 4. FAQ Hadoop vs Spark File system based | Memory based Map-Reduce Paradigm | Any distributed computing workload Details: https://docs.google.com/document/d/1hcv3JOc009AVer6bVFEeGnHrt_Jb0v3v3g2qGPgRy1Y
  • 7. K-Means Clustering First, decide the number of clusters k. Then: 1. Initialize the center of the clusters 2. Attribute the closest cluster to each data point 3. Set the position of each cluster to the mean of all data points belonging to that cluster 4. Repeat steps 2-3 until convergence Create k points for starting centroids (often randomly) While any point has changed cluster assignment for every point in the dataset: for every centroid calculate distance between centroid and point assign point to the cluster with the lowest distance for every cluster calculate mean of points in that cluster assign the centroid to the mean
  • 8. Example 1 Applying k-Means Algorithm using Python Program: kMeans.py* Data: x-y coordinates in file testSet.txt * Source: Chapter 10, Machine Learning in Action
  • 9. Example 2 Applying k-Means Algorithm using Java API to Spark Program: Spark_KMeans.java Data: Random numbers in marks.txt
  • 10. Example 3 https://mapr.com/ebooks/spark/08-machine-learning-mllib-spark-use-case.html Techniques applied for NLP ● Hashing ● Stemming ● TF-IDF ● Naive Bayes ● Random Forest Regression ● Gradient Boosted Trees Regression ● Code repository: https://github.com/joebluems/Mockingbird/issues Is Harper Lee’s Go Set a Watchman a discarded rough draft that was to become the universally beloved classic To Kill AMockingbird, or was it a truly separate work?
  • 11. Who is using Spark? Source: https://medium.com/ai rbnb- engineering/data- infrastructure-at- airbnb-8adfb34f169c
  • 12. Spark @AirBnB Spark is also an important tool for Airbnb. The team actually built something called Airstream, which is a computational framework that sits on top of Spark Streaming and Spark SQL, allowing engineersand the data team to get quick insights. Ultimately, for an organization that depends on predictions and machine learning, something like Spark - alongsideother open sourcemachinelearning libraries- iscrucial in theAirbnb stack. Source: https://www.packtpub.com/books/content/what-software-stack-does-airbnb-use