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SparkR: Enabling Interactive Data Science at Scale
1.
SparkR: Enabling Interactive
Data Science at Scale Shivaram Venkataraman Zongheng Yang
2.
Fast ! Scalable
Flexible
3.
Statistics ! Packages
Plots
4.
Fast ! Scalable
Flexible Statistics ! Plots Packages
5.
Outline SparkR API
Live Demo Design Details
6.
RDD Parallel Collection
Transformations map filter groupBy … Actions count collect saveAsTextFile …
7.
R + RDD
= R2D2
8.
R + RDD
= RRDD lapply lapplyPartition groupByKey reduceByKey sampleRDD collect cache filter … broadcast includePackage textFile parallelize
9.
SparkR – R
package for Spark R RRDD Spark
10.
Example: word_count.R library(SparkR)
lines <-‐ textFile(sc, “hdfs://my_text_file”)
11.
Example: word_count.R library(SparkR)
lines <-‐ textFile(sc, “hdfs://my_text_file”) words <-‐ flatMap(lines, function(line) { strsplit(line, " ")[[1]] }) wordCount <-‐ lapply(words, function(word) { list(word, 1L) })
12.
Example: word_count.R library(SparkR)
lines <-‐ textFile(sc, “hdfs://my_text_file”) words <-‐ flatMap(lines, function(line) { strsplit(line, " ")[[1]] }) wordCount <-‐ lapply(words, function(word) { list(word, 1L) }) counts <-‐ reduceByKey(wordCount, "+", 2L) output <-‐ collect(counts)
13.
Demo: Digit Classification
14.
MNIST
15.
A b ||
Ax − b ||2 Minimize x = (ATA)−1ATb
16.
How does this
work ?
17.
Dataflow Local Worker
Worker
18.
Dataflow Local R
Worker Worker
19.
Dataflow Local R
Spark Context Java Spark Context JNI Worker Worker
20.
Dataflow Local Worker
R Spark Context Worker Java Spark Context JNI Spark Executor exec R Spark Executor exec R
21.
22.
From http://obeautifulcode.com/R/How-R-Searches-And-Finds-Stuff/
23.
24.
Dataflow Local Worker
R Spark Context Worker Java Spark Context JNI Spark Executor exec R Spark Executor exec R
25.
Pipelined RDD words
<-‐ flatMap(lines,…) wordCount <-‐ lapply(words,…) Spark Executor exec R Spark Executor R exec
26.
Pipelined RDD Spark
Executor exec R Spark Executor R exec Spark Executor exec R R Spark Executor
27.
Alpha developer release
One line install ! install_github("amplab-‐extras/SparkR-‐pkg", subdir="pkg")
28.
SparkR Implementation Very
similar to PySpark Spark is easy to extend 329 lines of Scala code 2079 lines of R code 693 lines of test code in R
29.
EC2 setup scripts
All Spark examples MNIST demo YARN, Windows support Also on github
30.
Developer Community 13
contributors (10 from outside AMPLab) Collaboration with Alteryx
31.
On the Roadmap
High level DataFrame API Integrating Spark’s MLLib from R Merge with Apache Spark
32.
SparkR RDD à
distributed lists Run R on clusters Re-use existing packages Combine scalability & utility
33.
SparkR https://github.com/amplab-extras/SparkR-pkg Shivaram
Venkataraman shivaram@cs.berkeley.edu Zongheng Yang zongheng.y@gmail.com SparkR mailing list sparkr-dev@googlegroups.com
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